Bangladesh University of Professionals | Masters in Information and Communication Technology (MICT)

Outline
Admission Criteria
General Guideline
Course List

Faculty: Faculty of Science & Technology (FST)

Department: Department of Information and Communication Technology

Program: Masters in Information and Communication Technology (MICT)

Course Outline

BUP AT A GLANCE

1. Introduction

Bangladesh University of Professionals (BUP), one of the public universities of Bangladesh, was established on 05 June 2008. The aim of the University was to facilitate professional degrees and to run undergraduate, graduate, and post-graduate degrees through its faculties, affiliated and embodied colleges, institutes, academy or organizations. BUP, with its unique features, is set up in a green landscape of Mirpur Cantonment located in Dhaka Metropolitan City. The University provides a tranquil, pollution-free, and secured campus life, and above all, a congenial academic atmosphere.

BUP deals with not only the education of the armed forces personnel but also the students of the civilian community from home and abroad. It welcomes those students who intend to dedicate their total attention and devotion to serious academic pursuits to build up a better tomorrow for the nation. BUP is committed to providing high-quality education that delivers real benefits for the students. Thus, BUP is the unique academic entity in the country, where blending between the civilian and the armed forces students of diverse skills, experience, exposure, and attitude is possible.

1. Motto

The motto of BUP is "Excellence through Knowledge".

1. Mission

To develop the civil and military human capital through advanced education and research to respond to the knowledge-based society of the contemporary world.

1. Vision

Bangladesh University of Professionals will emerge as a leading university for both professionals and general students through need-based education and research with global perspective.

1. Core Values

Integrity : Highest ethical and moral uprightness.

Discipline : Strict discipline in all activities.

Creativity : Creativity in all spheres.

Commitment : High quality academic standards.

Wisdom : Enhanced education and research.

1. Objectives
To become a leading public university in Bangladesh and in the region.
To promote knowledge in the field of science and technology, business, medicine, social science, strategy, and security.
To promote leadership and civil-military relationship.
To develop intellectual and practical expertise.
To provide the best possible academic atmosphere.
To preserve the spirit of national culture, heritage, and traditions.
To facilitate higher education in the Armed Forces.
To prepare the Faculty and Staff with necessary competencies.
To deliver competent professionals relevant to the demands of society.
To sustain collaborative relationships with communities and educational partners.
To provide efficient services to support programs, campus community, and quality of life.
1. Embodied Faculties

BUP offers and regulates degrees in multi-disciplinary dimensions in the field of science, technology, strategy, humanities, liberal education, business, social sciences, medical science, war and security studies, and other fields of knowledge through its following 05 faculties:

Faculty of Arts and Social Sciences (FASS)
Faculty of Business Studies (FBS)
Faculty of Security and Strategic Studies (FSSS)
Faculty of Science and Technology (FST)
Faculty of Medical Studies (FMS)
1. The Medium of Instructions

English is the medium of Instructions and Examinations in Bangladesh University of Professionals (BUP).

1. Address

Bangladesh University of Professionals
Mirpur Cantonment, Dhaka- 1216, Bangladesh
Tel:88-02-8000368, PABX 8000261-4
Fax: 88-02-8000443

E-mail: info@bup.edu.bd
Website: www.bup.edu.bd

2. Student Services

2.1 Guidance and Counseling

The guidance and counseling services are available to students on academic and other matters of interest as follows:

To give the student information on matters important to success in academic activities;
To get information about the student which will be of help in solving his/her problems,
To establish a feeling of mutual understanding between students and teachers,
To help the student work out a plan for solving his/her difficulties;
To help the student know himself better –his/her interests, abilities, aptitudes, andopportunities;
To encourage and develop special abilities and right attitudes;
To inspire successful endeavor toward attainment; and
To assist the student in planning for educational and vocational choices.

2.2 Students Adviser

A Faculty Member is assigned as Student Adviser for each section of a batch, who, as a routine matter, meets the students at least once a week and attends them whenever the students feel necessary.

2.3 Scholarship and Stipend

It is not applicable for professional master’s programs.

2.4 Internship/Placement (If Applicable)

There is an office in BUP named Counselling and Placement Center (CPC). This center assists students in finding suitable jobs as well as getting the internship. Besides, the CPC is also involved in arranging workshops and seminars to practice resume writing, interview techniques, job search skills, and presentation techniques.

There is a committee to provide the required assistance to the students for placement in different organizations as part of the internship program. The committee comprises the Dean of the Faculty, Chairman of the Department, respective Student Adviser, and Placement Officer. The Dean of the Faculty acts as a convener of this committee.

Respective professional master’s programs may have different internship/placement policies depending upon the requirement of the Department. They may also be a part of BUP Alumni Association.

2.5 Co-Curricular and Club Activities

From its inception, the students of BUP have been spontaneously participating in co-curricular and club activities to enhance their physical, intellectual, moral, and ethical development. The clubs are active and contribute successfully in arranging different university events and ensuring the quality/standard. They organize inter-batch/department competitions, inter-university and other competitions. They also organize different important events like cultural programs, sports, debates, etc., and participate in different events and competitions. The students of BUP are also connected with other universities through different clubs. The clubs that are currently functional in BUP are:

BUP Accounting Forum (Administered by Department of Business Administration in Accounting & Information Systems, FBS)
BUP Business & Communication Club (BUP BCC) (Administered by Department of Business Administration in Marketing, FBS)
BUP Career Club (Administered by Dept. of Business Administration -General, FBS)
BUP Cultural Forum (Administered by Dept of Sociology, FASS)
BUP Debating Club (BUPDC) (Administered by Dept of Public Administration, FASS)
BUP Development Leader's Club (BUPDLC) (Administered by Dept of Development Studies, FASS)
BUP Disaster Management Forum (BUPDMF) (Administered by Dept of Disaster and Human Security Management, FASS)
BUP Economics Club (Administered by Dept of Economics, FASS)
BUP Film Club (Administered by Dept of Mass Communication & Journalism, FSSS)
BUP Finance Society (BUPFS) (Administered by Department of Business, Administration in Finance & Banking, FBS)
BUP Global Affairs Council (Administered by Dept of International Relations, FSSS)
BUP Human Resource and Leadership Club (HRLC) (Administered by Department of Business Administration in Management Studies, FBS)
BUP Infotech Club (BUPITC) (Administered by Information and CommunicationTechnology, FST)
BUP Law & Moot Court Club (BUPLMCC) (Administered by Dept of Law, FSSS)
BUP Literature & Drama Club (Administered by Dept of English, FASS)
BUP Photography Society (BUPPS) (Administered by Dept of Mass Communication & Journalism, FSSS)
BUP Research Society (Administered by Dept of English, FASS)
BUP Robotics Club (Administered by Information and Communication Technology, FST)
Environmental Club of BUP (Administered by Environmental Science, FST)
IEEE BUP Student Branch (Administered by Information and Communication Technology, FST)
Quizzers Club of BUP (Administered by Dept of International Relations, FSSS)
BUP Computer Programming Club (Administered by Dept of Computer Science and Engineering, FST)

The number of clubs may increase to cover other important and interesting events/issues in the coming days. Students of the Professional Master’s programs may participate in the Co-Curricular and club activities.

2.6 Industry/Organization/Field Visits

Different departments of BUP organize visits to various organizations/places according to the requirements of their programs. Students of the professional master’s program will attend in such Industry/Organization/ Field visits as per their respective curriculum.

2.7 Guest Lectures/Seminars/Symposiums/Workshops/Exercises

Guest Lectures/Seminars/ Symposiums/Workshops/ Exercises on important and contemporary academic issues and lectures/presentations by eminent academicians/professionals/experts are organized throughout the academic year. Students of the professional master’s program may attend in such academic activities.

2.8 Admission Procedure

BUP seeks applications from prospective candidates, who fulfill admission qualifications for Masters in Information and Communication Technology (MICT) as specified in BUP Admission Guideline. The program is offered annually to graduate candidates only. The admission notice is circulated usually in the month of September/October of each year through media advertisement and BUP website notice board. The candidates are asked to apply through online. The detailed admission procedure has been spelled out in Admission Guideline, which is available in BUP website (www.bup.edu.bd).

2.8.1 Eligibility for Admission

For admission to the program leading to a Masters in Information Systems Security (MICT), an applicant must have:

A minimum GPA of 3.50 out of 5.00 or a first division or equivalent in any one of SSC and HSC or in equivalent examinations and must not have a GPA less than 2.50 out of 5.00 or a third division or equivalent in any of the aforementioned examinations.
At least 50% marks or a minimum GPA of 2.50 out of 4.0 or its equivalent in B.Sc. Engg. or equivalent in the relevant branch.

2.8.2 Admission Rules

For admission to the courses leading to the degree of M.Sc. Engg. /M. Engg.. in ICT, an applicant must have obtained a bachelor degree in CSE, EEE, EECE, ETE, ECE, ICE, ICT, IT, Software Engineering or relevant engineering background from any recognized university from home and abroad.

2.8.3 Selection Process

Every year admission circular is usually published in the month of September/October. Admission test is held on November. Selection of candidates is made basing on their standing in the combined merit list in the admission test.

Admission Test Marks includes:

Written Test (MCQ)	50%
Communication Test	15%
Marks from previous public examinations	35%

Written Test:

All candidates are required to attend a written admission test of 70 marks (which will be converted into 50%), where he/she will have to qualify. The written test will be of Multiple-Choice Question and will be conducted for 1 hour. The written test will cover the following topics along with marks distribution:

Admission Test Syllabus

Subject	Basic of Computer	Basic of ICT	English
Marks	25	30	15
Total Marks	70

Communication Test (Interview/Viva Voce):

The selected candidates need to appear for a communication test based on their written test result before the panel of communication test consisting of faculty members. 15% of total marks will be allotted. Academic Committee may edit/ fix its percentage time to time.

Marks from Past Public Examinations:

The results of past public examinations will carry 35% Marks, where 20% is from B.Sc. or equivalent exam and 15% from HSC and SSC exams. The marks are calculated in a simple linear distribution from candidates’ GPA.

2.9 Admission in the Program

The selected candidates from BUP must collect their Admission Form from the Department and complete admission/registration formalities within the given time frame by paying the required fees at the beginning of the academic year. The following rules will apply in this regard:

1. The candidate fails to complete admission formalities within the prescribed date andtime; his/her selection will be considered canceled.
2. The student who fails to attend the class within two weeks of the commencement of 1^st Semester/trimester class his/her admission will be considered canceled.

2.10 Tuition and other Fees

SL.	Category of fees/charges	M.Sc. Engg.	M.Engg.	Remarks
1.	Admission Fee	10,000.00	10,000.00	Once
2	Semester Registration Fee	1000.00	1000.00	Once
3	Course Registration Fee (100/ Cr)	3,600.00	3,600.00	As Per Cr Reg
4	Thesis / Project	45,000.00	22,800.00	As Per Cr Reg
5	Library Fee (500 /Sem)	2,000.00	2,000.00	Each semester
6	Computer Lab and Training Aid Fee (2000/Sem)	8,000.00	8,000.00	Each semester
7	Tuition Fee (2400 / Credit)	86,400.00	86,400.00	Each semester
8	Exam Fee/Course Registration Fee (1000/ Theory Credit)	18,000.00	30,000.00	Per subject
9	Grade Sheet Fee (500/Sem)	2,000.00	2,000.00	Each semester
10	Student Welfare Fee (1000/Sem)	4,000.00	4,000.00	Each semester
11	Cultural/Magazine Fee (150/Sem)	600.00	600.00	Each semester
12	Dissertation Fee (400 per credit)	7,200.00	2,400.00	As Per Cr Reg
13	Center Fee (1500/Sem)	6,000.00	6,000.00	Each semester
14	ID Card Fee	200.00	200.00	Once
15	Tie/Scraf /Souvenir	940.00	940.00	Once
16	BNCC	60.00	60.00	Once
Grand Total		1,95,000.00	1,80,000.00

All civil and military students (where applicable) will be required to pay tuition and other fees as under:

2.10.1 Additional Fees/Payments (As Required):

Ser	Subjects	Amount (Tk.)
1.	Re-admission	10,000.00
2.	Non-Collegiate (Per Subject)	5,000.00
3.	Late Registration Fee	1,500.00
4.	Special Final Exam	15,000.00
5.	Retake Course Fee	12,000.00
6.	Supplementary Exam Fee	8000.00

Note: Admission cancellation and refund of admission fee will be executed as per following: No amount of total admission fee will be refunded.

2.11 Review of Fee Structure

All fees will be reviewed as and when necessary by the university authority, and the students will be liable to pay the fees as per changed/reviewed fees.

2.12 Deadline for Submission of Fees/Dues

The students have to clear all the fees during the admission process after the publication of the selected candidates' list by the respective Faculty/Department. For subsequent semester/trimesters, the payment of all fees/dues must be maintained Semester/trimester wise, and the following rules will apply in this regard:

The semester/trimester fees are to be paid as per the policy of the respective program.
The students may pay their fees after 1^st 15 days within one-month time by paying a penalty of Tk. 500.00 for every 15 days.
If a student fails to pay the semester/trimester fees within one and a half months, his/her name will be dropped, and the student will have to apply for re-registration if he/she desires to continue his/her study. If approved, he/she may take re-admission, paying the required re-admission fee.

2.13 Course Load to Students

The students must register for the required number of courses per Semester/trimester offered by the respective professional programs. During each Semester/trimester, students are allowed to take/enroll in a maximum of two additional retake course. The students are allowed to retake a course twice and improve a course only once throughout his/her entire registration period. He/she must complete all the Professional Master’s courses within his/her valid registration period.

2.14 Credit Hour

The total time that a teacher must interact with students in a teaching-learning environment for a particular course is defined as credit hour. Precisely, it is the contact hour between the assigned teacher and students. All programs of BUP must consider 01 (One) Credit hour amounting to 14 to 15 contact hours. An ideal contact hour must fulfill the following prerequisites:

The prescribed contact hour must be fully utilized meaningfully to achieve the planned outcome of the intended lesson.
Following the lesson covered in the contact hour, double the time of contact hour must be allotted to the students for assignments, exercise, home-works, or any other suitable activities in order to validate the planned outcome of the lesson.

2.15 Conduct of Courses

Generally, an individual course teacher is assigned to design and teach a particular course in a semester/trimester. The following guidelines are followed for conducting different courses:

At the beginning of the semester/trimester, the course teacher prepares a course outline/ course kit according to the approved course curriculum, performance evaluation and grading system list of suggested textbooks/references, and a tentative schedule of classes, examinations, and events. He/she distributes a copy of the same course outline to each registered student for the course and must submit a copy to the Department's Office.
The students must appear one (01) Mid-Term Examinations in a semester/trimester as per the given schedule. As a rule, 'Retake' of Mid Term Examination is not allowed, except for sickness, hospitalization, or other unavoidable circumstances, provided the student has valid supporting documents, and he/she has been permitted by the course teacher and Chairman of the Department before the examination commences.
Students must submit Term Paper/Project Paper/Assignment (individual and group) assigned to them in a semester/trimester for each course.
Any fraction in the marks obtained is to be rounded up to the advantage of the student i.e. any fraction is to be rounded up to the next number.
In special circumstances, if the program is conducted online/internet-based, a separate module will be set after discussion with the faculty and the concerned persons subject to the approval of the dean of the faculty.

2.16 Class Attendance

Attendance in all classes is mandatory. A certain percentage of the total marks for each course is allotted for class attendance. If a student is to appear at the final examination, she/he must fulfill the criteria of being Collegiate (having 50% or more attendance). Students who become Dis-collegiate (having attendance below 50% attendance) will not be allowed to sit for the final examination. A student must obtain permission from the Chairman of the Department for any kind of absence due to valid reasons and must inform the Course Teacher and Program Coordinator. The marks distribution for attendance is given below:

Attendance	Marks
85% and above	10.0
75% < 85%	9.0
65% < 75%	8.0
55% < 65%	7.0
50% < 55%	6.0
Less than 50%	Dis-collegiate

Note: However, Departments can consider any kind of exceptional cases (regarding Dis-collegiate Policy) subject to the approval of Dean of the respective faculty.

3. Performance Evaluation System

3.1 Distribution of Marks for Evaluation

Letter grades are used to evaluate the performance of a student in a course. The following grading system is followed for performance evaluation of the students:

Remarks	Distribution
Final Exam	50%
Mid-term	20%
Class Test (Best 3 out of 4) (3 Class Test and 01 lab Test Mandatory)	10%
Lab Assessment	10%
Class attendance	10%
Total:	100%

The BUP authority reserves the right to review/revise the above grading system. However, depending on the nature of course, minor modifications can be made by respective course teacher, provided it is incorporated in the course outline.

3.1.1 Distribution of Marks for Evaluation (Theory Courses)

Letter grades (e.g., A+, A, A-, B+ etc.) are used to evaluate a student's performance in a course. The following mark distribution system can be followed for the performance evaluation of students. However, the respective Department can vary according to their book of the syllabus:

Grading Distribution	% of Total Grade Allocated
Class Attendance and Performance	The weightage of these items will be based on the approved book of the syllabus of the respective programs.
Mid Term Exam
Assignment
Term Paper (Book Review / Research Paper Writing)
Semester/trimester Final
Total

3.1.2 Distribution of Marks for Evaluation (Laboratory Courses)

The marks for the Laboratory courses are distributed according to the type of the laboratory course based on the respective Department's requirement. The distribution of the marks for three types of Laboratories is given below:

Marks Distribution for Laboratory

Category	Marks Distribution (%)
Lab test	The weightage of these items will be based on the approved book of the syllabus of the respective programs.
Quiz
Viva
Attendance
Home Assignment/Report
Class Performance/Observation
Total

Marks Distribution of Project-Based Laboratory

Category	Marks Distribution %
Project	The weightage of these items will be based on the approved book of the syllabus of the respective programs.
Quiz
Viva/Presentation
Attendance
Home assignment/report
Class Performance/Observation
Total

Marks Distribution of Programming Based Laboratory

Category	Marks Distribution (%)
Online Test – 1	The weightage of these items will be based on the approved book of the syllabus of the respective programs.
Online Test – 2
Viva
Attendance
Observation
Class Performance
Total

3.1.3 Research Monograph/Thesis/Internship/Project Report

In addition to the theoretical examination of the Research Monograph/Thesis/Internship/ Project Report to be submitted by the students, there shall also be an oral defense of the written work. Three (03) copies of the Thesis/Internship/ Project Report work shall be submitted to the examination committee. The Examination Committee shall appoint the examiners for the Research Monograph/Thesis/Internship/Project Report as per the requirements of their respective professional programs.

Evaluation of Research Monograph/Thesis/ Internship/Project Report (Written Work)	Oral Defense	In-Course/Continuous Assessment
The weightage of these items will be based on the approved book of the syllabus of the respective programs.	The weightage of these items will be based on the approved book of the syllabus of the respective programs.	The weightage of these items will be based on the approved book of the syllabus of the respective programs.

3.1.4 Resubmission of Research Monograph/Thesis/Internship/Project Report

For valid grounds such as lack of originality or plagiarism, the issue of Thesis/ Internship/ Project Report resubmission will be conducted as per the discretion of examiner(s) concern. In case of resubmitting the Thesis/Internship Report/ Project, the students will be given an additional 02 months to rectify/amend their work. Three (03) copies of the Thesis/Internship/ Project Report should be submitted again. The cost of the examination (e.g. remuneration of supervisors and examiners) will be paid by the student.

3.2 Grading System

Numerical Grade	Letter Grade		Grade Point
80% and above	A+	(A Plus)	4.00
75% to < 80%	A	(A Regular)	3.75
70% to < 75%	A-	(A Minus)	3.50
65% to < 70%	B+	(B Plus)	3.25
60% to < 65%	B	(B Regular)	3.00
55% to < 60%	B-	(B Minus)	2.75
50% to < 55%	C+	(C Plus)	2.50
45% to < 50%	C	(C Regular)	2.25
40% to < 45%	D	-	2.00
< 40%	F	-	0.00
-	W	-	Withdrawn

3.3 Calculation of GPA (Grade Point Average) and CGPA (Cumulative Grade Point Average)

Grade Point Average (GPA) is the weighted average of all the grade points obtained in all the courses passed/completed by a student. CGPA (Cumulative Grade Point Average) will be computed after each Semester/trimester to determine the academic standing of the student in the program. The four-step procedure that will be followed to calculate the CGPA of a student is given below:

Grade points earned in each course will be computed based on credit hours in that course and the individual grade earned in that course by multiplying both.
All subject grade points (determined at step "a") will be added to determine the total grade points earned.
Credits of all completed/passed courses (excluding the course for which the student applies for Supplementary Examination) will be added together to determine the total number of credits.
GPA will be determined by dividing the results of step 2 by the result of step 3.

3.3.1 Calculation of GPA

Grade Point Average (GPA) is the weighted average of the grade points obtained of all the courses passed/completed by a student. For example, if a student passes/completes n courses in a term having credits of С1, С2,....., Cn and his grade points in these courses are G1, G2, ....

Gn respectively, then

GPA=	Total Grade Point earned in a particular Semester/trimester
	Total Credits completed in the particular Semester/trimester

∑ C_iGi

GPA =

∑ C_i

A numerical example, Suppose, a student has completed five courses in a term

obtained the following grades:

Course Code	Credit(s) *(Ci)*	Grade	Grade Points *(Gi)*	*Points Earned (CixGi)*
5101	3	A+	4.00	12
5102	3	B	3.00	9
5103	3	A	3.75	11.25
5104	2	B+	3.25	6.5
5105	1	A-	3.50	3.5

Then his/her GPA for the term will be computed as follows:

3x4.00+3x3.00+3x3.75+2x3.25+1x3.50

Grade Point Average (GPA) Calculation =

3+3+3+2+1

= 3.52

When a course is repeated for improvement, the last result or grade point shall be counted for calculating GPA and CGPA. If the grade point obtained in improvement, is lower than the grade point obtained earlier, the earlier one (previous grade point) shall stand.
Performance in all courses, including the 'F' grade, shall be reflected in the Grade Sheet.

3.3.2 Cumulative Grade Point Average (CGPA) Calculation

Cumulative Grade Point Average (GPA) is the weighted average of the grade points obtained of all the courses passed/completed by a student. For example, if a student passes/completes n courses in a term having credits оf С1, С2,..., Cn and his grade points in these courses are G1, G2, ....Gn respectively, then

CGPA=Total earned points for all passed or completed coursesTotal number of Credit hours completed

=Summation of (Credit hours in a course × Grade point earned in that course)Total number of credit hours completed

=i=1nCi × Gii=1nCi

3.3.3 Rounding Off the GPA/CGPA

The GPA/CGPA is to be rounded off after two digits of the decimal. For example, to round off 3.465 and above after two decimal digits, it is to be rounded off as 3.47. To round off 3.464 and below after two decimal digits, it is to be rounded off as 3.46.

4. Promotion Policy

To be promoted from one semester to another, students must obtain a minimum CGPA (with a maximum number of ‘F’ Grade to be considered in each semester) /as mentioned in the table below:

Serial	02-years Masters Program
Serial	Semester (From & To)	Required Minimum CGPA (During the mentioned semester)	Number of ‘F’ Grade to be considered (in each semester)
1	1^st – 2^nd	2.50	* Maximum one (01) ‘F’ Grade
2	2^nd – 3^rd	2.50	* Maximum one (01) ‘F’ Grade
3	3^rd – 4^th	2.50	* Maximum one (01) ‘F’ Grade

Note: Star (*) marked will not be applicable for retake course

If a student gets ‘F’ grade in more than one (01) course in any semesters and/or fails to obtain required CGPA of 2.50 in a semester as mentioned above, he/she will automatically be relegated to the next batch, and such relegation more than twice entire the registration period will warrant permanent withdrawal of the student from the program. However, besides the retaking cources obtaining ‘F’ Grade, the relegated student will also have the option to improve or retake for rest of the courses.

5. Withdrawal Policies

5.1 Temporary Withdrawal

Temporary withdrawal means a student has voluntarily withdrawn himself/herself from a particular semester/trimester. In such case, the following rules will be maintained:

A student can withdraw himself/herself from a semester/trimester without penalty by applying to the authority minimum of four weeks before the commencement of the Semester/trimester.
A case of withdrawal is subject to the approval of the respective Dean.
Withdrawal is not allowed after the Midterm Examination during a semester/trimester.
A student will have to re-register their required courses by the next Semester/trimester with the next immediate batch.
The student can avail of such opportunity only once within their valid registration period.

5.2 Permanent Withdrawal

The term 'Permanent Withdrawal' stands for permanent and voluntary discontinuation of the student from the program. The implication of permanent withdrawal includes cancellation of admission and expiry of registration.

5.3 Withdrawal on Poor Performance

Students may be permanently withdrawn from the program because of their poor performance. A student is always advised to maintain a minimum CGPA. Any student failing to obtain the required CGPA as per promotion policy will be relegated to the next immediate batch. However, two (02) times relegation or three times failure in a course at any time throughout the entire valid registration period will warrant permanent withdrawal of the student from the program.

6. Examination Assessment System

BUP follows a single examiner system, and continuous assessment is done to evaluate a student in a semester/trimester. The following rules will apply for all tests and examinations:

Records of in-course (Midterm, Class tests, Attendance, Assignments etc.) will be evaluated by the teacher of the relevant course in a prescribed form (or online portal) showing the marks obtained by the students. The course teacher will display (i) one copy of the mark sheet on the notice board (or online) for information of the students (ii) send one copy to the Chairman of the Department (iii) send one copy to the Chairperson of the Examination Committee, and (iv) one copy to the Controller of Examinations at least one week before the commencement of the final examination. This timeframe needs to be strictly maintained.
The questions for the semester/trimester final examination will be set by the course teacher and submitted to the Moderation Committee of the respective Faculty. If more than one teacher can take a single course in different sections of a batch, then a combined set of question/s will have to be prepared through the Moderation Committee. The question setters of a particular course should not be the moderators of that specific course.

Note: Students with physical disabilities will get extra 10 minutes per hour in the examination.

6.1 Supplementary Examination

As a general rule, supplementary examinations of any kind are discouraged. However, if a student fails to appear in the scheduled Semester/trimester Final Examination for unavoidable and valid reasons; he/she may be allowed to appear at such examination based on the following guidelines under the grounds described below:

In case of a student's extreme compassionate ground or any other reason that the Chairman of the Department approves, he/she must appear the supplementary examination within 45 days from the date on which the particular examination was held.
The student should apply to the concerned Dean (through the respective Department) within seven days from the last examination with the required supporting documents describing the reasons for his/her inability to appear for the scheduled semester/trimester final examination. The Dean, if convinced, will forward to the office of the Controller of Examinations duly recommending approval and thereby allowing for making arrangements to conduct the examination on the respective course/subject.
The student will have to pay the required fees as per the University Policy for appearing at the supplementary examination and completing other examination formalities for the course(s) so appeared.
Not more than 'B+' (GPA 3.25) grade will be awarded to the student for supplementary examinations. However, special cases may be considered with prior approval of the respective Dean.
The existing rules of semester/trimester final examination will apply to the conduct of supplementary examinations e.g. question setting, moderation, evaluation, and result publication etc.

6.2 Improvement Policy

A student earning lower than 'B' Grade (i.e. lower than Grade Point 3.00) in any course(s), may choose to improve the grade by appearing at the improvement examination. In case of improvement examination, the following rules will be maintained:

The student must apply to the Dean for approval before at least one month of the commencement of the final examination and will get a chance to improve the grade of a course only once in a valid registration period.
The student must sit for only the Semester/trimester Final Examination with the immediate next batch.
If the grade point obtained by the student in the improvement examination is lower than the earlier obtained grade point, the earlier one (previous grade point) will stand.
Improvement examination for a course will not be allowed after graduation.
No improvement examination will be allowed for any practical course, viva voce, internship and 'Thesis’/project/dissertation and/or the like.

6.3 Retaking a Course

In case of retaking of course(s) of the Professional Master’s Program, students must complete the process within the valid registration period. A student will be allowed to retake only one (01) course in any semester/trimester of a particular year. They will be allowed to retake a course twice only throughout their entire registration period. Retaking a course (or grade) will be guided by the following rules:

A student earning an 'F' grade or being Dis-collegiate/Absent/Expelled from the examination will be required to retake the course offered in the immediate next batch or if the situation is considered reasonable/convenient. In this case, a student can continue with the immediate next available batch. Since achieving a passing grade in all courses is mandatory individually as the degree requirement.
The student will have to be allowed by the Dean of the Faculty and Chairman of therespective Department to sit for the examination. In case of retaking course(s), the following rules will be maintained:

The student must sit for all In-course and the Final examination.
For appearing in the examination for retaking a course, his/her class attendance is an important factor, which should be checked and ensured by the respective Chairman of the Department.

6.4 Registration Duration

The duration of registration period of Professional Master’s Program will be ‘Program Duration + 02 Years’. For example, if the LL.M Professional Program duration is 01 (one) year, then its registration period will be ’01 Year + 02 Years i.e. 03 (Three) years. The duration of registration period may be extended subject to the approval of Academic Council and the approved fees will be applied.

7. Awarding Professional Master’s Degree and Requirements

Students must fulfill all degree requirements within the valid registration period for the Professional Master’s program. The requirements are as follows:

Students must not have any 'F' grade.
Students must have a minimum CGPA of 2.50.
Minimum grade in the Internship/ Thesis/ Project/ Dissertation/ Research Monograph is C'.

8. Dismissals on Disciplinary Grounds

A student may be dismissed or expelled from the program for adopting unfair means (Copying in examinations/ to influence grades), unruly behavior, or any other breach of discipline. The implication of dismissal may include cancellation of admission and termination of registration.

9. Discipline and Code of Conduct

Adherence to strict discipline is considered a core concept of building future leaders. The students must abide by the rules, regulations, and code of conduct of the university. Students are forbidden to be members or organize students' organizations, clubs, society, etc., other than those set up by the University authority. They must maintain a peaceful and congenial atmosphere in the academic building, particularly adjacent to the classroom, library, faculty rooms, etc. The students will not be allowed to enter the classroom if they are contrary to the following rules:

Arriving late in the class.
Not wearing appropriate dress/attire as per the BUP dress code.
Any unfair means in exams/tests (The minimum punishment for unfair means in an examination is the cancellation of all courses of running Semester/trimester + 01 Semester/trimester Onwards).

Note: For the details, "The Students' Discipline Rules" is available on BUP website.

10. Other Breaches of Discipline

Academic Council may dismiss any student on the disciplinary ground if any form of indiscipline or unruly behavior is observed in him/her, disrupting the academic environment or program or being considered detrimental to BUP's image. Discipline Committee will process the matter. Zero tolerance to drug, violence, and Sexual Exploitation and Abuse (SEA).

11. Students' Redress Measures

If an examinee anticipates any discrepancies regarding his/her results/grade/marks, this will be brought to the notice of the Controller of Examinations through the Head of the Department within 30 (thirty) days from the date of publication of the result.

A certain amount of fee is required for the application of re-scrutiny. In case of re-scrutiny, the Controller of Examinations or his/her nominated teacher/officer will re-scrutinize the same whether there is any miscalculation of marks or any unmarked question of the script. In case of miscalculation, the Controller of Examinations or concerned officer will adjust the correct marks and finalize the result.
If any unmarked question of the script is found, then the concerned examiner will re-examine/ re-evaluate the unmarked question of the script. In that case, if the concerned examiner is not available, then the only unmarked question of the script will be examined/evaluated by any other examiner (alternative examiner).
After the scrutiny, the Controller of Examinations will republish the corrected result.

12. Executive Decision for Any Arising Situation

If this Academic Guideline does not explicitly or satisfactorily address any arising situation, in that case, the matter will be referred to the Vice Chancellor for a decision. Execution of such a decision will duly be reported to the Academic Council for information only.

13. Amendments

Any of the provisions of this guideline may be changed and/or new provisions added as per the University's Rules.

14. Conclusion

BUP Professional Master’s Academic Guideline-2023 is for the students, and it is to be followed for the best use of student's academic interests. It is the guide for the Faculty Members to assess the overall evaluation system of the students of BUP and acquaints themselves with BUP's rules and regulations.

PART TWO

DEPARTMENT OF INFORMATION AND COMMUNICATION TECHNOLOGY (ICT)

Introduction to ICT Department

The Department of Information and Communication Technology (ICT) at Bangladesh University of Professionals (BUP) is committed to excellence in education, research, and innovation. The department aims to develop skilled professionals and researchers by offering programs tailored to meet the challenges of the dynamic ICT landscape. With a curriculum emphasizing hands-on learning, theoretical foundations, and industry-aligned skills, the ICT Department nurtures talents capable of addressing global technological needs.

The department's vision is to advance ICT education through cutting-edge research, innovative teaching methodologies, and industry collaboration. Equipped with state-of-the-art labs and a dedicated faculty team, it strives to foster critical thinking, problem-solving, and leadership in the realm of technology.

The department stands as a beacon for aspiring technologists and researchers, preparing them to excel in academia, industry, and beyond. The department places special emphasis on:

Interactive classroom sessions and an uninterrupted curriculum to ensure effective learning.
Innovative teaching methods, blending the latest global trends with state-of-the-art facilities.
A balance of competent internal faculties and outsourced expert resource persons for specialized knowledge.
Regular guest lectures and visits to organizations, providing industry exposure.
A continuous feedback and assessment system to ensure academic excellence.
A culture of discipline, punctuality, and commitment in all aspects of academic life.
Adherence to a code of conduct and dress code that instills professionalism.
A focus on nurturing students as good human beings with the qualities of successful leaders.
Providing a tranquil, secure campus environment free from external disturbances.

Through these initiatives, the ICT Department at BUP prepares students to excel academically, professionally, and ethically, contributing significantly to both national and global ICT advancements.

2. Current Programs

The Department of ICT is running the following programs:

B.Sc. in Information and Communication Engineering (BICE)
M.Sc.Engg./M.Engg.in Information and Communication Engineering (MICE)
M.Sc.Engg./M. Engg. in Information Systems Security (MISS)
M.Sc.Engg./M. Engg. in Information and Communication Technology (MICT)

Programs	Duration	Total Courses Theory+ Laboratory	Credit on Courses	Industrial Attachment/ Dissertation Credit	Total Credit	Remarks
BICE	4 Years	42 +25	151	3+6	160	B.Sc. in ICE
MICE	1.5 Years	6/10	18/30	18/6	36	M.Sc. Engg. /M.Engg.
MISS	2 Years	8/12	22/34	18/6	40	M.Sc.Engg. / M.Engg.
MICT	2 Years	8/12	22/34	18/6	40	M.Sc. Engg. /M.Engg.

3. Faculty Members

All the programs of the Department of ICT are conducted by a group of esteemed and highly qualified faculty members. Details are in www.bup.edu.bd. Besides, experienced adjunct faculties from renowned universities are also engaged in academic activities of this department.

4. Mailing Address

Chairman, Department of ICT

Faculty of Science and Technology (FST)

Bangladesh University of Professionals (BUP)

Mirpur Cantonment, Dhaka-1216

Phone: 02-8000485, Fax: 88-02-8000443

E-mail: ict@bup.edu.bd

5. Masters in Information and Communication Technology (MICT)

5.1 Introduction

The Masters in Information and Communication Technology (MICT) is a dynamic two-year program designed to empower technology professionals with the expertise needed to lead and innovate in the rapidly evolving ICT landscape. The program equips students with advanced technical knowledge and practical skills to design, develop, and manage cutting-edge ICT solutions, addressing complex challenges in today’s interconnected world. With a focus on fostering innovation and adaptability, the curriculum emphasizes a blend of theoretical foundations and hands-on experience, preparing graduates to excel in diverse ICT roles across industries.

The MICT program offers a comprehensive curriculum that spans key areas such as data communication, cloud computing, artificial intelligence, IoT, and network systems. This multidisciplinary approach ensures graduates are proficient in integrating ICT solutions to drive organizational efficiency and innovation. Students are encouraged to engage in research and development projects, equipping them with the critical thinking and problem-solving skills necessary to navigate emerging technological trends.

Graduates of the MICT program bring exceptional value to various sectors, from telecommunications and finance to healthcare and smart city development. They are equipped to assume specialized roles such as Network Architects, Data Scientists, System Administrators, and ICT Consultants. Moreover, the program provides a strong foundation for leadership roles, including Chief Information Officer (CIO) and ICT Project Manager, where professionals oversee strategic planning, implementation, and maintenance of ICT systems at organizational and industry levels.

In an era where ICT drives global transformation, the MICT program stands out by producing professionals who are not only skilled in leveraging current technologies but are also visionaries capable of shaping the future of ICT. By bridging the gap between theoretical knowledge and real-world application, the program prepares graduates to excel in an increasingly interconnected and technology-dependent world.

5.2 Vision of the Program

To develop a world-standard program on information and communication technology through advanced education and research that equips professionals to tackle evolving technological challenges.

5.3 Mission of the Program

To equip students with hands on knowledge and skills necessary to maximize students’ potentials with a view to preparing an individual specialist on information and communication technology.

5.4 Program Objectives

To engage in cutting-edge education and research projects that contribute to solve real-world ICT challenges, promoting a culture of continuous learning and technological advancement.
To provide an immersive learning experience through hands-on labs, and industry collaborations that equip students with essential skills to excel as ICT specialists in diverse environments.
To empower students with the ability to lead projects and devise innovative solutions to complex technological issues, preparing them to be influential professionals in the global ICT landscape.

5.5 Learning Outcomes

Graduates with masters in ICT degree from BUP will be able to:

Possess a comprehensive understanding of ICT principles, frameworks, and methodologies, with specialized expertise in areas such as data communications, information security, network management, and emerging technologies.
Design, conduct, and critically analyze research that advances the field of ICT, demonstrating strong analytical skills to assess and apply findings to real-world applications.
Adept at identifying and solving complex ICT problems using innovative approaches, applying critical thinking to devise solutions for technical and organizational challenges.
Gain hands-on experience with the latest ICT tools, software, and hardware, allowing them to apply theoretical knowledge practically and adapt to diverse technological environments.
Understand the ethical implications and societal impact of ICT, making decisions that reflect responsible use of technology and considering privacy, security, and sustainability.
Skill in communicating complex ICT concepts to both technical and non-technical audiences, and in working effectively in teams, reflecting strong collaborative and interpersonal skills.
Lead ICT projects and manage teams, with skills in project planning, resource allocation, and strategic decision-making, equipping them for roles as influential professionals in the ICT field.

6. Course and Credit Related Information

6.1 List of all Core and Elective Courses with their Credit Distribution:

Sl.	Name of the Course	Theory (Credit)	Total Contact Hours
Core Courses
	MICT-1101 Computer Architecture & Operating System	3.0	48.00
	MICT-1102 Advanced Communication Network	3.0	48.00
	MICT-1103 Advanced Artificial Intelligence & Machine Learning	3.0	48.00
	MICT-1201 Advanced Cloud Computing	3.0	48.00
	MICT-1202 Broadband & Wireless Communication	3.0	48.00
	GED-1203 Research Methodology	1.0	32.00
	MICT-1204 Advanced Digital Signal Processing	3.0	48.00
Elective Courses (Information Technology)
	MICT-2001 Advanced Computer Network	3.0	48.00
	MICT-2003 Advanced Database Management System	3.0	48.00
	MICT-2005 Internet of Things (IoT)	3.0	48.00
	MICT-2007 Recent Trends in ICT	3.0	48.00
	MICT-2009 Information Security	3.0	48.00
	MICT-2011 Advanced Algorithm & Optimization	3.0	48.00
	MICT-2013 ICT Policy & Standards	3.0	48.00
	MICT-2015 Ethical Hacking & Intrusion Management	3.0	48.00
	MICT-2017 ICT Project Management	3.0	48.00
	MICT-2019 Advancement in Microprocessor Systems	3.0	48.00
	MICT-2021 Big Data Analytics	3.0	48.00

Elective Courses (Communication)
	MICT-2002 Advanced Optical Communication	3.0	48.00
	MICT-2004 Advanced Telecommunication Network	3.0	48.00
	MICT-2006 Cellular Mobile Communication	3.0	48.00
	MICT-2008 Advanced Data Communication	3.0	48.00
	MICT-2010 Advanced Digital Communication	3.0	48.00
	MICT-2012 Satellite & Radar Communication	3.0	48.00
	MICT-2014 Information Theory & Coding	3.0	48.00
	MICT-2016 Industrial Automation & Control	3.0	48.00
Elective Courses (Research work)
1.	MICT-2000 Thesis	18.0	--
2.	MICT-2001 Project	6.0	--

Note: Elective courses may be added or removed based on by the authority based on the availability of the resources and industry practice.

6.2 Summary

SL	YEAR	SEMESTER	DEGREE	NO. OF THEORY COURSES	THEORY (CR.)	THESIS/ PROJECT	CREDIT
1	First	1^st	M.Sc. Engg.	3	9	-	9
		1^st	M. Engg.	3	9	-	9
		2^nd	M.Sc. Engg.	4	10	-	10
		2^nd	M. Engg.	4	10	-	10
2	Second	1^st	M.Sc. Engg.	1	3	9	12
		1^st	M. Engg.	3	9	-	9
		2^nd	M.Sc. Engg.	-	-	9	9
		2^nd	M. Engg.	2	6	6	12
Total			M.Sc. Engg.		-	-	40
Total			M. Engg.				40

6.3 Course Designation System

Each course is designated by a maximum of four-letter code identifying the department offering the course followed by a three-digit number having the following interpretation:

The first digit (from left) corresponds to the year/level in which the course is normally taken by the students.
The second digit (from left) corresponds to the semester/ term in which the course is normally taken by the students.
The last two digits denote various courses.

The course designation for core course system is illustrated as Follows:

MICT-1101	Computer Architecture & Operating System

	Course Title
	Course Serial Number
	(Reserved for departmental use to denote course)
	Signifies 1^st Semester course Signifies 1^st Year course Department identification code

6.4 Semester-wise Course and Credit Distribution for M.Sc. Engg. Degree (Thesis group)

Year	Semester	Course Code	Course Name	Theory (Credit)	Total Credit Hour	Total Contact Hour
1^st	1^st	MICT-1101	Computer Architecture & Operating System	3.0	3.0	48.00
		MICT-1102	Advanced Communication Network	3.0	3.0	48.00
		MICT-1103	Advanced Artificial Intelligence & Machine Learning	3.0	3.0	48.00
	2^nd	MICT-1201	Advanced Cloud Computing	3.0	3.0	48.00
		MICT-1202	Broadband & Wireless Communication	3.0	3.0	48.00
		GED-1203	Research Methodology	1.0	2.0	32.00
		MICT-1204	Advanced Digital Signal Processing	3.0	3.0	48.00
2^nd	1^st	MICT-20**	Elective-I	3.0	3.0	48.00
	1^st	MICT-2000	Thesis	9.0	--	--
	2^nd	MICT-2000	Thesis	9.0	--	--

Note: The distribution of elective courses in different semesters may be changed by the authority based on the availability of the resources and industry practice.

6.5 Semester-wise Course and Credit Distribution for M. Engg. Degree (Project group)

Year	Semester	Course Code	Course Name	Theory (Credit)	Total Credit Hour	Total Contact Hour
1^st	1^st	MICT-1101	Computer Architecture & Operating System	3.0	3.0	48.00
		MICT-1102	Advanced Communication Network	3.0	3.0	48.00
		MICT-1103	Advanced Artificial Intelligence and Machine Learning	3.0	3.0	48.00
	2^nd	MICT-1201	Advanced Cloud Computing	3.0	3.0	48.00
		MICT-1202	Broadband & Wireless Communication	3.0	3.0	48.00
		GED-1203	Research Methodology	1.0	2.0	32.00
		MICT-1204	Advanced Digital Signal Processing	3.0	3.0	48.00
2^nd	1^st	MICT-20**	Elective-I	3.0	3.0	48.00
		MICT-20**	Elective-II	3.0	3.0	48.00
		MICT-20**	Elective-III	3.0	3.0	48.00
	2^nd	MICT-20**	Elective-IV	3.0	3.0	48.00
		MICT-20**	Elective-V	3.0	3.0	48.00
		MICT-2001	Project	6.0	--	--

Note: The distribution of elective courses in different semesters may be changed by the authority based on the availability of the resources and industry practice.

Detail syllabus is attached in Annex A

Teaching Strategy

Students gain knowledge and understanding through practical work that allows the exposure and exploration of underpinning theory and concepts. Guided reading and online content support students in developing their understanding of the subject area. An emphasis on formative feedback and tasks is built into all the first-year modules and may include participation in online activities, in order to practice and explore the topics covered in classes more fully.

Assessment Strategy

Students’ knowledge and understanding is assessed by a range of activities that include both formative (developed to provide feedback on learning) and summative (graded) tasks. A wide range of assessment methods are used. Tasks may involve traditional approaches such as case studies, assignments, presentations and term papers, time constrained tests and exams. (Details are given in page 19 of part one).

Thesis/ Project Related Guidelines

After the completion of the first semester, if a student gets CGPA greater than or equal to 3.25, he will be eligible to get a thesis. He can choose to do a project as well.
No eligibility criteria for project students.
If any student below CGPA 3.25 at the end of the first semester is interested to apply for thesis, he/she may apply to the Chairman with recommendation from the supervisor.
The Chairman will review the proposal through an internal Board of Officer and may/may not allow to pursue thesis.
1. Thesis
Research work for a thesis shall be carried out under the supervision of a full-time member of the staff belonging to the relevant department/ Institute of BUP/DU/BUET/MIST or any other university recognized by UGC. However, in special cases, a full-time member of the staff belonging to a department outside ICT may be appointed as Supervisor, if the research content of the thesis is within the field of specialization of the member of the staff. A Co-supervisor from within or outside the department may be appointed, if necessary. The thesis proposal of a student shall be submitted for approval of the Academic Committee after completion of at least 18 credit hours of course work.
If any change is necessary of the approved thesis (title, content, cost, Supervisor, Co- supervisor etc.) it shall be approved by the Academic Committee.
Eligible thesis students will be selected by the department. But thesis works will be done by individual students. It cannot be carried out in a group
The research work must be carried out in BUP or at a place(s) recommended by the Academic Committee. The work schedule and financial involvement should be mentioned in the research proposal for carrying out research work outside the University.
Every student shall submit to the Chairman, Department of ICT, through his/her Supervisor, required number of type written copies of his/her thesis in the approved format on or before a date to be fixed by the Supervisor concerned in consultation with the Chairman, Department of ICT.
The student shall certify that the research work was done by him/her and that this work has not been submitted elsewhere for the award of any other diploma or degree.
The thesis should demonstrate evidence of satisfactory knowledge in the field of research undertaken by the student.
Every student submitting a thesis in partial fulfillment of the requirements of a degree, shall be required to appear at an oral examination, on a date or dates fixed by the Supervisor concerned in consultation with the Chairman, Department of ICT and must satisfy the examiners that he/she is capable of intelligently applying the results of this research to the solution of problems, of undertaking independent work, and also afford evidence of satisfactory knowledge related to the theory and technique used in his/her research work.
The thesis dissertation should be original, and plagiarism free.The 25% or less similarity index is acceptable, as determined by Turnitin Plagiarism Checker. Self-plagiarism is acceptable.
1. 1. Thesis Lifecycle for Effective Management
Submission of thesis Proposal -Notice will be given for 2^nd semester students after 8 weeks and must be submitted within 2 weeks after 9 credits.
Supervisor confirmed-Within October.
Presentation of Title Confirmation - Notice given beginning of November and has to present a presentation on last November.
Follow-up form filling and submission – Every month twice.
Follow-up of Phase 1 – Present 1^stprogress presentation June 1^st week.
Follow-up of Phase 2 – Present 2^ndprogress presentation October 1^st week.
Pre-defense – October last week.
Final defense – November last week.
1. 1. Submission of Thesis

Every student submitting a thesis report in partial fulfillment of the requirement of a degree shall be required to appear at an oral examination, on a date or dates fixed by the Supervisor concerned in consultation with the Chairman, Department of ICT and must satisfy the examiners that he/she has gained satisfactory knowledge related to the project work.

1. 1. Examination Board for Thesis
An Examination Board for every student for thesis oral examination shall be approved by the Chairman, the Department of ICT on recommendation of the thesis Supervisor and to be forwarded to Dean, FST for final approval. The Supervisor shall act as the Chairman and the Chairman of the Department of ICT will be an ex-officio member of the Examination Board. The Board shall consist of at least four members including the Chairman, the Department of ICT and the Supervisor. The Examination Board shall be constituted as follows:

Supervisor	Chairman
Co-supervisor (if any)	Member
Chairman , Department of ICT (Ex-officio)	Member
One or two members from within the Department	Member
One external member from outside the student relevant institute/ Department	External

Note: If the Chairman of the department supervise any thesis work, then senior faculty member will be designated as an Ex-officio.

If any member of the Examination Board is unable to accept the appointment or must relinquish his/her appointment before the examination, Chairman, Department of ICT shall appoint another member in his/her place, on suggestion from the Supervisor. This appointment will be reported to the Academic Committee.
In case a student fails to satisfy the Examination Board in thesis and /or oral examination, the student shall be given one more chance to resubmit the thesis and/or appear in oral examination as recommended by the Board.

9.2 Project

Project work shall be carried out under the supervision of a full-time member of the staff belonging to the relevant department of BUP/DU/BUET/MIST or any other university recognized by UGC. However, in special cases, a full- time member of the staff belonging to a department outside ICT may be appointed as Supervisor, if the research content of the project work is within the field of specialization of the member of the staff. The title of the project, cost and the Supervisor shall be recommended by the Academic Committee for approval which will be reported to the Dean, FST. The project proposal of a student shall be submitted for approval of the Academic Committee after completion of minimum 18 Credits.
If any change is necessary to the approved thesis (Title, Content, Cost, Supervisor, Co- supervisor etc.) it shall be approved by the Academic Committee.
Eligible project students will be selected by the department. But project work will be done by individual students. It cannot be carried out in a group.
The project work must be carried out in BUP or at a place(s) approved by the Chairman, Department of ICT for approval by the Academic Committee. The work schedule and financial involvement should be mentioned in the project proposal for carrying out project work outside the BUP.
Every student shall submit to the Chairman, Department of ICT, through his/her Supervisor, required number of type written copies of his/her project report in the approved format before a date to be fixed by the Supervisor concerned in consultation with the Chairman, Department of ICT.
The student shall certify that the project work was done by him/her and the work has not been submitted elsewhere for the award of any other diploma or degree.
The project should demonstrate evidence of satisfactory knowledge in the field of project undertaken by the student.
Every student submitting a project report in partial fulfillment of the requirement of a degree shall be required to appear at an oral examination, on a date or dates fixed by the Supervisor concerned in consultation with the Chairman, Department of ICT.
The Project dissertation should be original, and plagiarism free.The 25% or less similarity index is acceptable, as determined by Turnitin Plagiarism Checker. Self-plagiarism is acceptable.

9.2.1 Project Lifecycle

Submission of project proposal -Notice will be given for 3^rdsemester students after 8 weeks and must be submitted within 2 weeks after completion of 18 theory credit hours.
Supervisor confirmation-Within March.
(c) Presentation of Title Confirmation - Notice given beginning of April and has to present a presentation on last April.
Follow-up form filling and submission – Every month once
(e) Follow-up of Phase 1 – Present 1^stprogress presentation Mid-September
(f) Follow-up of Phase 2 – Present 2^ndprogress presentation Mid-October
(g) Pre-defense – Mid-November
(h) Final defense – Mid-December

9.2.2 Submission of Project

Every student submitting a project report in partial fulfillment of the requirement of a degree shall be required to appear at an oral examination, on a date or dates fixed by the Supervisor concerned in consultation with the Chairman, Department of ICT and must satisfy the examiners that he/she has gained satisfactory knowledge related to the project work.

9.2.3 Examination Board for Project

An Examination Board for students for the project examination shall consist of at least four members including the Supervisor. The Supervisor shall act as the Chairman. The Academic Committee shall recommend the names of the examiners for approval of Dean FST. The Examination Board shall be constituted as follows:

Supervisor	Chairman
Co-supervisor (if any)	Member
Chairman, Department of ICT (Ex-officio)	Member
One or two members from within the Department	Member
One external member from outside the student relevant institute/ Department	External

Note: If the Chairman of the department supervise any thesis work, then senior faculty member will be designated as an Ex-officio.

If any member of the Examination board is unable to accept the appointment or has to relinquish his/her appointment before the examination, Chairman, Department of ICT shall appoint another member in his/her place on the recommendation of the relevant Academic Committee.
In case a student fails to satisfy the Examination Board in project report and /or presentation, the student can be given one more chance to resubmit the project report and/or appear in another examination as recommended by the Board.

9.3 Thesis/Project Evaluation

Total evaluation of the thesis/project will be out of 100 which will be done during the final defense.
The evaluation of the supervisor will carry out 50% of the final marks and the evaluation of the other board members will carry 50% of the final marks.

9.4 Re-Defense Fees for Thesis/Project

If any student cannot complete the project in their final semester, he/she can re-defend the project with the next batch. However, this will happen only after paying the re-defense fee and getting the approval of the departmental Chairman.

ANNEX-A

DETAIL COURSE CURRICULUM

CORE COURSES

MICT-1101: Computer Architecture & Operating System

Credit Hour: 3.0

Course Objectives:

Understand the principles and design of modern computer architecture.
Analyze the performance and efficiency of different computer systems.
Explore advanced topics in operating systems, including resource management and security.
Develop skills to implement and optimize operating system components.
Apply knowledge of computer architecture and operating systems to solve complex computing problems.

Course Outcomes:

Upon the completion of this course, students will be able to:

Demonstrate an understanding of the design and functionality of modern computer architecture.
Evaluate and improve the performance and efficiency of computing systems.
Implement and manage advanced operating system features.
Optimize operating system components for better resource utilization and security.
Solve complex problems related to computer architecture and operating systems.

Course Content:

Introduction to Computer Architecture: Instruction codes, formats, cycle, timing, etc.; Addressing modes; Types of instruction; RISC characteristics; CISC characteristics. Different types of data representation; Addition and subtraction; Multiplication algorithms; Division algorithms.
Memory Organization: Main memory; Auxiliary memory; Associative memory; Cache memory; Virtual memory; Memory management requirements and hardware.
Input-Output Organization: Input-Output Interfaces; Data transfer, Interrupts; Direct Memory Access (DMA); Input-output channel.
Fundamentals of parallel processing: Parallel processing; Pipelining; Vector processing; Multiprocessors; Array processors, Bit-slice processor Interconnection structures.
Introduction to OS: Operating system concepts, process schedule, deadlock and memory management.
Process Synchronization: Background, The Critical-Section Problem, Peterson’s Solution, Synchronization Hardware, Mutex Locks, Semaphores, Classic Problems of Synchronization and Monitors
Virtual Memory: Demand Paging, Copy-on-Write, Page Replacement, Allocation of Frames: Thrashing, Memory-Mapped Files and Allocating Kernel Memory.
Protection and security: Goals, Principles of Protection, Access Matrix, Access Control, Revocation of Access Rights, Program Threats, System and Network Threats, User Authentication, Implementing Security Defenses, Firewalling to Protect Systems and Networks, Computer-Security Classifications, An Example: Windows 7.
Virtual Machine: Features, Building Blocks, Types of Virtual Machines and Their Implementations, Virtualization and Operating-System Components, Hypervisors.
Distributed Systems: Advantages of Distributed Systems, Types of Network-based Operating Systems, Network Structure, Communication Structure, Communication Protocols, An Example: TCP/IP, Robustness, Design Issues, Distributed File Systems.

Laboratory and Case Study:

Memory Management

Implement and compare the performance of various page replacement algorithms like First-In-First-Out (FIFO), Least Recently Used (LRU), Optimal Page Replacement, and Second Chance.
Implement different memory allocation algorithms like First-Fit, Best-Fit, Worst-Fit, and Buddy Memory Allocation.
Implement a simple memory-mapped file system that maps a file directly into the virtual address space of a process.
Core OS Features and Deadlocks
Implement a simple file system with support for basic operations like create, read, write, delete, and directory manipulation.
Explore different file system layouts (e.g., FAT, NTFS, ext4) and their trade-offs.
Implement algorithms for deadlock detection (e.g., resource allocation graph) and prevention (e.g., resource ordering, banker's algorithm).
Process Synchronization with Locks
Implement a solution to the producer-consumer problem using mutex locks and semaphores.
Analyze the performance and correctness of different synchronization mechanisms.
Implement a solution to the dining philosophers problem using different synchronization techniques (e.g., mutex locks, semaphores, monitors).
Virtual Machines
Implement a simple user-level virtual machine using a language like C or assembly.
Explore the challenges of emulating system calls and hardware interrupts in a user-level environment.
Investigate the performance implications of virtualization and the techniques used to optimize virtual machine performance.

References:

John L. Hennessy, David A. Patterson, Computer Architecture: A Quantitative Approach, 6th Edition, Morgan Kaufmann, 2019.
Abraham Silberschatz, Peter B. Galvin, Greg Gagne, Operating System Concepts, 10th edition, Wiley, 2018
Andrew S. Tanenbaum, Herbert Bos, Modern Operating Systems, 4th edition, Pearson, 2015
David A. Patterson, John L. Hennessy, Computer Organization and Design, 5th Edition, Morgan Kaufmann, 2017.

MICT-1102: Advanced Communication Network

Credit Hour: 3.0

Course objectives:

To understand key networking models (OSI vs. TCP/IP) and their modern relevance.
To study data link layer functions, including framing, error detection, and MAC.
To understand IPv4/IPv6 addressing, subnetting, routing algorithms, and protocols (OSPF, BGP, NAT).
To explore wireless standards, cellular evolution (1G to 5G), mobility, and power management.
To learn network security fundamentals, cryptographic techniques, key security protocols, and defense against common attacks.
To understand VPC architecture, cloud connectivity (Direct Connect, SD-WAN), and key 5G/6G features and use cases.

Course Outcomes:

Upon the completion of this course, students will be able to:

Explain the key differences between circuit-switched and packet-switched networks and articulate the significance of OSI and TCP/IP models in network design.
Demonstrate the ability to configure and troubleshoot Ethernet technologies, including VLANs and link aggregation, within various networking environments.
Create efficient IP addressing schemes and apply appropriate routing algorithms and protocols to facilitate optimal network communication.
Assess the key characteristics of various wireless standards and cellular architectures, demonstrating an understanding of handover mechanisms and mobility management.
Identify potential security threats and apply cryptographic techniques and security protocols to safeguard network communications effectively.
Competence in deploying AI-based solutions to optimize network management, improve fault detection, and automate routine network operations across distributed cloud architectures.
Design IoT and M2M communication systems using LPWAN technologies, ensuring energy efficiency and extended connectivity.

Course Content:

Introduction to Communication Networks: Evolution of Communication Networks: From Circuit-Switched to Packet-Switched, Key Networking Models: OSI vs. TCP/IP, Network Architecture: Core, Edge, and Access Networks, Switching and Routing Basics (Circuit Switching, Packet Switching), Traffic Types: Voice, Video, Data, Multimedia.
Data Link Layer and Ethernet Technologies: Data Link Layer Functions (Framing, Error Detection/Correction, MAC), Ethernet Evolution: Fast Ethernet, Gigabit Ethernet, 10/100/400 Gbps Ethernet, VLANs (Virtual LANs) and Spanning Tree Protocol (STP), Link Aggregation, Ethernet Flow Control, and Power over Ethernet (PoE).
Network Layer: IP Addressing, Routing, and Switching: IPv4 and IPv6 Addressing: Structure, Subnetting, and Supernetting, Routing Algorithms: Distance Vector, Link State, Path Vector, Protocols: OSPF, BGP, RIP, EIGRP, IS-IS, Network Address Translation (NAT) and Private/Public Ips, MPLS (Multi-Protocol Label Switching) and Traffic Engineering.
Transport Layer Protocols: TCP vs. UDP: Key Differences, Use Cases, and Performance, Congestion Control Mechanisms (AIMD, Fast Retransmit, ECN), TCP Variants (Reno, Vegas, Cubic) and Their Impact on Performance, Flow Control, Error Detection, and Error Recovery Mechanisms, Quality of Service (QoS) and Traffic Prioritization at the Transport Layer.
Wireless and Mobile Networks: Wireless Standards: IEEE 802.11 (Wi-Fi), 802.15 (Bluetooth), 802.16 (WiMAX), Cellular Networks: From 1G to 5G (Architecture, Key Technologies, Frequency Bands), Handover Mechanisms and Mobility Management in Cellular Networks, Wireless Ad Hoc and Sensor Networks: Routing and Power Management, Satellite Networks and Free-Space Optical (FSO) Communications.
Network Security and Cryptography: Network Security Principles: CIA (Confidentiality, Integrity, Availability), Symmetric vs. Asymmetric Cryptography, Hash Functions, Digital Signatures, Security Protocols: SSL/TLS, IPSec, VPNs, WPA3, Network Attack Vectors: DoS/DDoS, Phishing, Eavesdropping, Spoofing, Firewall Technologies, Intrusion Detection/Prevention Systems (IDS/IPS).
Cloud and Edge Networking: Cloud Networking: Virtual Private Clouds (VPC), Direct Connect, and Cloud-based WANs, SD-WAN: Architecture, Application, and QoS in Cloud Environments, Edge Computing and Mobile Edge Computing (MEC), Network Management in Distributed Cloud Architectures, AI and Machine Learning in Cloud and Edge Networks.
Emerging Technologies in Communication Networks: 5G/6G Networks: Key Features (eMBB, URLLC, mMTC) and Use Cases, Internet of Things (IoT) and Machine-to-Machine (M2M) Communication, Low-Power Wide-Area Networks (LPWAN): LoRa, NB-IoT, Sigfox, AI-Driven Networking: AI and ML Algorithms for Network Optimization, Quantum Networking: Fundamentals and Future Prospects.

Laboratory and Case Study:

Network Simulation and Topology Design: Design and simulate a complex network topology using tools like Cisco Packet Tracer or GNS3.
Basic Routing Protocols Configuration: Configure and compare routing protocols like RIP, OSPF, and EIGRP.
VLAN Configuration and Trunking: Implement Virtual LANs (VLANs) and configure trunking between multiple switches.
QoS Configuration for Voice and Video Traffic: Configure Quality of Service (QoS) for prioritizing voice and video traffic over data traffic.
Wireless LAN Configuration and Security: Set up and secure a Wireless LAN with WPA3 encryption.
IP Addressing and Subnetting Lab: Perform IP subnetting and configure a network with custom subnets.
Traffic Analysis and Network Troubleshooting Using Wireshark: Capture and analyze network traffic using Wireshark to troubleshoot connectivity issues.

Required Tools and Software:

Physical Devices: Use of routers, switches, and access points (where feasible).
Simulation Tools: Cisco Packet Tracer, GNS3, and Mininet.
Network Analysis Tools: Wireshark for real-time packet capture and analysis.

References:

James Kurose and Keith Ross, Computer Networking: A Top-Down Approach, 8^th Edition, Pearson, 2021.
William Stallings, Data and Computer Communications, 10^th Edition, Pearson, 2013.
Thomas Erl, Ricardo Puttini, and Zaigham Mahmood, Cloud Computing: Concepts, Technology & Architecture, 1^st Edition, Prentice Hall, 2013.
Wan Lei, Ning Ge, and Jie Zhang, 5G System Design: Architectural and Functional Considerations and Long-Term Research, 1st Edition, Springer, 2019.

MICT-1103: Advanced Artificial Intelligence & Machine Learning

Credit Hour: 3.0

Course Objectives:

To master the various techniques of Artificial Intelligence and Machine Learning.
To formulate security problems and to select appropriate AL and ML strategies to solve them.
To analyze the applicability of AL and ML tools for different security problems.
To design solutions for small to medium scale problems.

Course Outcomes:

Upon completion of this course, students will be able to:

Demonstrate the understanding of the concepts of AL and ML including supervised, unsupervised and reinforcement learnings.
Apply AL and ML tools and techniques to security problems.
Compare the benefits, limitations and tradeoff between different algorithms and select the appropriate measure.
Develop defense solutions for various kinds of cybersecurity applications.

Course Content:

1. 1. 1. Artificial Intelligence: Stages of designing an AI-based product with a focus on specifics such as the cost metrics and technical requirements of an AI software development plan; A brief Introduction Artificial intelligence (AI) and its applications in cyber security; Impact and challenges of AI in cyber security; Intelligent agents, Uninformed search, Informed search, Constraint satisfaction, Game-playing, Logical agents, Propositional logic, First-order logic, Inference in first-order logic, Resolution, Logic programming, Planning, Plan execution, Uncertainty, Probability theory, Probabilistic inference, Bayesian networks and associated inference algorithms, Optimal decisions under uncertainty, optimal sequential decisions, Learning agents, Inductive learning, Decision trees.
    2. Machine Learning: Supervised Learning: Linear regression and classification, Model assessment and cross-validation, Introduction to optimization, Nonlinear regression (neural nets and Gaussian processes), Boosting and feature selection. Neural Network, Back-propagation algorithm and other training algorithms. Regularizations. Practical aspects of Neural Network.; Unsupervised Learning: Nearest neighbors and K-means, Hierarchical Clustering and Density based Clustering. The EM algorithm, Mixture models for discrete and continuous data, Temporal methods: Hidden Markov models; Boltzmann machines and Random field; Reinforcement Learning: Basic of Sequential Decision Making, Markov Decision Process, Dynamic Programming, Monte Carlo method, Bellman Equations, Q-learning; Deep Learning: Introduction to Deep Learning, Convolutional Neural Network, Residual Network, Adversarial Network, Deep Q-learning.

Laboratory and Case Study:

Malware threat detection with machine learning models (K-means, Decision Tree, Random Forest).
Phishing attack detection with Logistic Regression, Decision Tree.
Automatic Intrusion Detection using ML models.
Email Spam Detection using AI techniques.
DDos network traffic Analysis.
Anomaly or Fruad Detection, e.g. Network Anomaly Detection.
Breaking Captchas with Convolutional Neural Network.

References:

Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, 4th Edition, Pearson, 2021
C. Bishop, Pattern Recognition and Machine Learning, 1st Edition, Springer, 2006
Ian Goodfellow, Y. Bengio and Aaron Courville, Deep Learning, MIT Press, 2016
Richard S. Sutton and Andrew Barto, Reinforcement Learning: An Introduction, 2nd Edition, MIT Press, 2018
Michael I. Jordan, An Introduction to Probabilistic Graphical Models, MIT Press, 2002
David L. Poole and Alan K. Mackworth, Artificial Intelligence: Foundations of Computational Agents, Cambridge University Press, 2010
R.O. Duda, P. E. Hard, and D. G. Stork, Pattern Classification, 2nd Edition, Wiley, 2001
Soma Halder and Sinan Ozdemir, Hands-On Machine Learning for Cybersecurity, Packt Publisher, 2022

MICT-1201: Advanced Cloud Computing

Credit Hour: 3.0

Course Objectives:

To Provide a comprehensive understanding of the principles and advanced concepts in cloud computing.
To Explore the architecture, services, and deployment models of cloud computing, including advanced topics such as serverless computing, edge/fog computing, and microservices.
To design, deploy, and manage scalable cloud-based solutions using modern technologies.
To Evaluate the latest trends in cloud security, privacy, and governance.
To analyze cloud computing platforms and manage workloads using cloud orchestration and automation tools.
To Study the economics of cloud services, including pricing models, cost optimization, and cloud resource management.

Course Outcomes:

Upon the completion of this course, students will be able to:

Demonstrate a comprehensive understanding of cloud computing principles.
Analyze serverless computing architectures and their advantages in building scalable and cost-effective applications.
Understand the key components of cloud architecture, such as virtualization, networking, and storage.
Understand the principles of microservices architecture and their benefits in building complex distributed systems.
Implement strategies for ensuring the scalability, reliability, and performance of cloud applications.
Analyze the importance of data privacy and compliance regulations in cloud computing.

Course Content:

Cloud Computing Foundations: Evolution of Cloud Computing: From Virtualization to Cloud, Cloud Service Models: IaaS, PaaS, SaaS, Deployment Models: Public, Private, Hybrid, and Community Clouds,Cloud Economics: Pay-per-Use Model, Cost Efficiency.
Advanced Cloud Infrastructure and Virtualization: Virtualization Concepts: CPU, Memory, I/O Virtualization, Resource Management and Scheduling in Cloud Environments, Software-Defined Networking (SDN) and Software-Defined Storage (SDS), Serverless Computing: Concepts, Architectures, and Applications, Edge and Fog Computing: Architectures and Design Criteria.
Overview of Major Cloud Providers: AWS, Azure, Google Cloud, Cloud-Native Applications: Kubernetes, Docker, Microservices, Cloud Orchestration: Managing Complex Workflows, Serverless Platforms: AWS Lambda, Google Functions, Data Management in the Cloud: Distributed Databases, NoSQL, Object Storage.
Cloud Security, Privacy, and Governance: Security in the Cloud: Data Encryption, Identity and Access Management (IAM), Regulatory Compliance: General Data Protection Regulation (GDPR), Data Residency, Privacy and Confidentiality in Cloud Platforms, Threat Modeling and Risk Management, Disaster Recovery and Business Continuity in Cloud Environments.
Cloud Automation and Cost Management: Cloud Resource Provisioning and Auto-scaling, Monitoring and Optimization Techniques, Cloud Cost Management and Optimization: AWS Pricing Models, Reserved Instances, Cloud Automation Tools: Terraform, Ansible, CloudFormation

Laboratory and Case Study:

Case Study 1: Cloud Computing Foundations

Scenario 1: Transitioning from On-Premises to Cloud for a Small Business.

Scenario 2: Comparing Cloud Service Models, IaaS, PaaS, and SaaS in terms of control, scalability, and security for a Government Project.

Case Study 2: Advanced Cloud Infrastructure and Virtualization

Scenario 1: Virtualizing a University’s Data Center.

Scenario 2: Implementing Software-Defined Networking (SDN) for a Telecom

Company.

Case Study 3: Cloud Platforms and Services

Scenario 1: Building a Multi-Region Cloud Application for a FinTech Startup.

Scenario 2: Design a serverless architecture using AWS Lambda and S3 for an Event-Driven Application.

Case Study 4: Cloud Security, Privacy, and Governance

Scenario 1: Design a secure cloud architecture for storing sensitive healthcare data in a Cloud-Based Healthcare System.

Scenario 2: Implement data governance policies to ensure General Data Protection

Regulation (GDPR) Compliance.

Case Study 5: Cloud Automation and Cost Management

Scenario 1: Automating Cloud Resource Provisioning and Evaluate the cost savings from auto-scaling and resource optimization.

Scenario 2: Optimizing Cloud Costs for a SaaS Provider and Monitor cloud spending

based on usage patterns.

References:

Thomas Erl and Ricardo Puttini and Zaigham Mahmood, Cloud Computing: Concepts, Technology & Architecture, Pearson, 2023.
Mark Buckwell, Security Architecture for Hybrid Cloud: A Practical Method for Designing Security Using Zero Trust Principles, Apress, 2023.
John Arundel and Justin Domingus, Cloud Native DevOps with Kubernetes: Building, Deploying, and Scaling Modern. Applications in the Cloud, O'Reilly Media, 2024.
Kevin L. Jackson and Scott Goessling, Architecting Cloud Computing Solutions: Build Cloud Strategies That Align Technology and Economics while Effectively Managing Risk, Packt Publishing, 2023.
Kai Hwang and Sameer Sharma, Cloud Computing for Machine Learning and Cognitive Applications, MIT Press, 2022.

MICT-1202: Broadband & Wireless Communications

Credit Hour: 3.0

Course Objectives:

To gain foundational knowledge on wireless communication principles, including access techniques like TDMA and FDMA, and spread spectrum techniques (DSSS, FHSS, THSS).
To understand the structure of modulators/demodulators, error probabilities, and how systems perform under interference or jamming.
To explore multiple access interference, performance metrics (e.g., BER), and multi-user detection techniques.
To learn about detectors like matched filters, MMSE, SIC, PIC, MAP, and MLSE for optimized communication performance.
To understand channel models, fading types, delay/Doppler/angle spreads, and their effects on signal transmission.
To learn about single and multiple antenna systems (SISO, SIMO, MISO, MIMO), their capacities, and techniques like space-time block coding (STBC).
To study the principles of OFDM, including synchronization issues and performance challenges.
To learn about broadband wireless standards (IEEE 802.x) and mobile standards (4G, 5G, beyond).

Course Outcomes:

Upon the completion of this course, students will be able to:

Analyze various wireless multiple access techniques and the impact of spread spectrum techniques on signal robustness and system security.
Develop proficiency in detecting and mitigating multiple access interference (MAI) using various detector techniques and performance analysis based on Bit Error Rate (BER) and efficiency.
Gain a deep understanding of how radio signals propagate through mobile channels, handle different fading scenarios, and implement effective channel models.
Learn to calculate and improve system capacity for various antenna configurations (SISO, SIMO, MISO, MIMO) and apply coding and diversity schemes for improved signal quality.
Become proficient in OFDM communication, addressing synchronization and power issues, and understand the evolution and technical specifications of modern wireless standards.

Course Content:

Overview of broadband wireless communications, multiple access techniques - TDMA, FDMA. Spread spectrum techniques - direct sequence spread spectrum (DSSS), FHSS, THSS, modulator and demodulator structure, probability of error, jamming margin, decoding, performance in the presence of interference, PN sequence, CDMA, MC-CDMA, UWB transmission.
Multi-user detection: multiple access interference, detector performance measure - BER, asymptotic efficiency, near-far resistance; detectors - matched filter detector, de-correlator detector, MMSE detector, SIC, PIC, MAP and MLSE detectors.
Propagation in mobile radio channels; channel models, fading, large scale and small-scale fading, flat fading and frequency selective fading channel, fast fading and slow fading channel; delay spread, Doppler spread and angle spread; channel autocorrelation functions, scattering function, correlated and uncorrelated scattering (US), WSS and WSSUS model.
Multiple antenna systems, capacity of SISO, SIMO, MISO and MIMO systems, ergodic capacity, outage capacity, STBC, OSTBC, QOSTBC, spatial multiplexing (SM) scheme, SM detection techniques, diversity and diversity combining techniques.
Multi-carrier communications; Orthogonal FDM (OFDM), OFDM transceivers. Special issues of OFDM - cyclic prefix, timing offset, frequency offset, synchronization, peak power problem, Broadband wireless standards: IEEE 802 (IEEE 802.3, 802.4, 802.5, 802.11, 802.16 etc.), Mobile cellular standards: 4G, 5G and beyond.

Laboratory and Case Study (MATLAB simulation may be given):

As a case study or lab, CDMA (DS-SS) technique can be checked by the students for two or three user-system.
Detailed investigation of a popular path loss model.
A case study or design of an IEEE 802.3 or 802.4 based LAN.
As a case study, a SIMO/MISO and MIMO system can be designed by students and check the performance of the system.
A MIMO OFDM system will be established and performance of the system will be evaluated.

References:

Theodore S. Rappaport, Wireless Communications: Principles and Practice, 2^nd Edition. Prentice Hall, 2002.
David Tse and Pramod Viswanath, Fundamentals of Wireless Communication, Cambridge University Press, 2005.
Ezio Biglieri, Robert Calderbank, and Anthony Constantinides, MIMO Wireless Communications, Cambridge University Press, 2007.
Ramjee Prasad, OFDM for Wireless Communications Systems, Artech House, 2004.
Erik Dahlman, Stefan Parkvall, and Johan Sköld, 5G NR: The Next Generation Wireless Access Technology, Academic Press (an imprint of Elsevier), 2018.

GED-1203: Research Methodology

Credit Hour: 1.0

Course Objectives:

To develop a comprehensive understanding of research methodologies and techniques.
To acquire the skills necessary to design, conduct, and analyze research studies effectively.
To master data collection methods, such as surveys, interviews, observations, and experiments.
To develop skills in writing research proposals, literature reviews, and research reports.
To cultivate critical thinking and problem-solving abilities in the context of research.
To interpret and communicate research findings effectively.

Course Outcomes:

Upon the completion of the course, the students will be able to:

Gain a deep understanding of research methodologies and techniques, including various research designs, data collection methods, data analysis techniques, and ethical considerations.
Analyze research questions, design effective research studies, and solve research-related problems.
Conduct research independently, from formulating research questions to interpreting and communicating findings.
Select appropriate research designs based on research questions and objectives.
Evaluate research studies, including assessing the validity and reliability of research instruments and methods.
Effectively use LaTeX software to create professional-quality documents, including research papers, presentations, and theses.

Course Content:

Fundamental Concept of Research: Definition, role of research, steps of research, purpose/objectives of research, research questions, research problems, research hypothesis, Bias in Research, characteristics, and types of research, scientific method, Current trends, practices, and professional standards of applied research in different fields.
Basic terminologies and issues in research: Variables, types of variables, properties, and relationships between research, Inductive and deductive research, basic statistical terms used in research, quantitative and qualitative research tools, and research fallacies.
Research process: Problem identification, literature review, research design, measurement and scaling techniques, questionnaire design, data collection, sampling and sample design, and Report writing.
Data and methods of data collection: data, data vs information, types of data, sources of data, primary data collection methods, secondary data collection methods, qualitative and quantitative data collection techniques, Sampling Process stages, sampling distribution, different probability sampling methods, Statistics and Parameters.
Processing and analysis of data: Data processing, univariate analysis, bivariate analysis, multivariate analysis, hypothesis testing, mathematical problems on hypothesis testing, characterization of data, accuracy and precision.
Correlation analysis: Different correlation analysis, Test of hypothesis: mean test, proportion test, variance test, chi-square testing, ANOVA, Cause and effect analysis; regression, simple linear and multiple linear regression, categorical regression, Selection of appropriate statistical tools.
Ethics in Research: Code and Policies of Research, Ethical Principles, Plagiarism in Research, Ethical Decision Making in Research, Conduct of Ethical Research.
Research report/proposal writing: Research report/proposal writing and segments of a research report.

Laboratory and Case Study:

Quartiles Journal and Predatory Journals: To get ideas Standards and Predatory journals, impact factor, indexing, citation etc.
Reference management software (Mendeley Software, Zotero Software etc.): Papers download form online and offline, library form, Keeping notes, citations and references in the manuscript with different styles.
Latex software: Use Latex software in writing manuscripts through Overleaf.
Online data collection, Processing, Presentation and Analysis: Sources of data sets, download of data from reliable sources, Reliability check, Data processing in Google Colab (Data Reading, Cleaning, Integration, Transformation, Reduction, Discretization), Data Presentation (Quantitative, Qualitative, Univariate table, Bi-variate table, Multivariate table etc.) and data analysis.
Writing of Research Report and Proposal: Writing a journal/ conference paper /poster presentation/research report using latex, writing of synopsis.

References:

Andrew J. Friedland, Carol L. Folt, Writing Successful Science Proposals, 2 edition, Yale University Press; June, 2009.
Scott Berkun, The Myths of Innovation, O'Reilly Media, 2010.
Pedhazur, E. J. and Schmelkin, L. P. Measurement, Design and Analysis: An Integrated Appoach, Psychology Press, 2013.

MICT-1204: Advanced Digital Signal Processing

Credit Hour: 3.0

Course Objectives:

To deepen understanding of advanced DSP concepts, including complex signal transformations, multi-rate signal processing, and spectral estimation techniques.
To learn advanced methods for designing and implementing digital filters, including FIR, IIR, adaptive filters, and multi-dimensional filtering.
To understand and apply time-frequency analysis techniques such as wavelets and Fourier transform.
To analyze and implement advanced algorithms for signal enhancement, noise reduction, and system identification.
To apply advanced DSP techniques to solve complex problems in various fields such as communications, biomedical engineering, audio and image processing, and control systems.
To gain expertise in using software tools like MATLAB, Python, and DSP processors for simulation, analysis, and implementation of DSP algorithms.

Course Outcomes:

Upon the completion of this course, students will be able to:

Gain a deep understanding of complex DSP theories and be able to apply them in advanced signal processing tasks.
Design and implement advanced digital filters for various applications, including real-time processing.
To apply advanced time-frequency analysis techniques to analyze non-stationary signals in various domains.
Develop and implement advanced DSP algorithms for tasks such as noise reduction, signal enhancement, and data compression.
To apply advanced DSP techniques to real-world problems in fields like communications, biomedical engineering, audio processing, and more.
Achieve hands-on experience with DSP software tools and will be able to use them effectively for simulation, analysis, and algorithm development.

Course Content:

Review on FIR filters and all-pole IIR lattice filters and their implementation.
Random processes; auto-correlation; cross-correlation; and power spectrum estimation.
Adaptive filtering: review of the LMS and RLS algorithms, adaptive lattice-ladder filters, frequency-domain adaptive filtering methods, variable step-size adaptive filters, application of adaptive filtering.
Power spectrum estimation: Review of parametric techniques for power spectrum estimation, high resolution methods.
Multirate signal processing, filter banks: Cosine modulated filter banks, para unitary QMF banks, multidimensional filter banks, emerging applications of multirate signal processing.
Time frequency analysis; short-time Fourier transform; and wavelet transform.

Laboratory and Case Study:

Assignment on sampling, quantization, and signal conditioning requirements for a given DSP applications (will be set by respective course teacher).
Application of FFT for spectrum analysis, convolution, and correlation using MATLAB/ Python/DSP processors.
Application of FFT for filtering using MATLAB/ Python/DSP processors.
Design digital filters based on Z transform using MATLAB/ Python/DSP processors.
Design lowpass, highpass, bandpass, and bandstop FIR filters using the Kaiser window,frequency sampling and optimal design methods.
Design lowpass, highpass, bandpass, and bandstop IIR filters using Butterworth and Chebyshev prototypes.
Design and Implementation of Adaptive filters using MATLAB/ Python/DSP processors.

References:

John G. Proakis and Dimitris G. Manolakis, Digital Signal Processing: Principles, Algorithms, and Applications, 4th Edition, 2006, Pearson, ISBN: 978-0131873742.
M. Vetterli, J. Kovacevic, and V. K. Goyal, Foundations of Signal Processing, Cambridge, 2014.
Bernard Widrow and Samuel D. Stearns, Adaptive Signal Processing, 1st Edition, 1985, Pearson, ISBN: 978-0130040299.
Fredric J. Harris, Multirate Signal Processing for Communication Systems, 1st Edition, 2004, Prentice Hall, ISBN: 978-0131465114.
Sanjit K. Mitra, Digital Signal Processing: A Computer-Based Approach, 4th Edition, 2010, McGraw-Hill Education, ISBN: 978-0077366766.
Kay, S. M., Theory and Application, Modern Spectral Estimation, Prentice-Hall 2005.

ELECTIVE COURSES

MICT-2001: Advanced Computer Network

Credit Hour: 3.0

Course Objectives:

To provide an overview of advanced computer network functions.
To provide required skill to efficiently configure and deploy different devices in a network.
To provide an overview of network virtualization and cloud environment.

Course Outcomes:

Upon the completion of this course, students will be able to:

Understand and explain the principles of a layered protocol architecture.
Understand, explain and calculate digital transmission over different types of communication media.
Deploy and manage switch in a LAN and WAN.
Deploy and manage enterprise routers WAN or Data Center.
Deploy and manage firewalls to defend a network.
Understand the use of AI and ML in network optimization.

Course Content:

Network Architecture and Protocol Design: Study of network layering principles, protocol design, and architectural models (e.g., OSI and TCP/IP). In-depth analysis of modern network architectures, such as Software-Defined Networking (SDN) and Network Function Virtualization (NFV). Protocol stacks and the evolution of networking standards. Data center network architectures and network protocols.
High-Speed Networks and Performance Optimization: Techniques for achieving high throughput, low latency, and minimal packet loss in high-speed networks. Concepts like congestion control, Quality of Service (QoS), and traffic engineering. Optimization of data flow, bandwidth management, and buffering strategies for modern high-speed applications.
Network Security and Privacy: Advanced network security protocols (TLS, IPsec, VPNs). Emerging threats and security mechanisms for protection against attacks (e.g., DDoS, MITM, packet sniffing). Privacy-enhancing technologies and cryptographic protocols for secure data transmission.
Internet of Things (IoT) Networking: IoT architecture, protocols (e.g., MQTT, CoAP), and standards. Energy-efficient networking and data routing for IoT devices. Security and privacy concerns in IoT networks and strategies to mitigate them.
Network Virtualization and Cloud Networking: Virtual LANs (VLANs), Virtual Private Networks (VPNs), and network slicing. Cloud networking principles, including the integration of cloud resources with traditional networks. Security and management of virtualized network infrastructures.
Advanced Routing and Switching Techniques: Algorithms and protocols for efficient routing and switching (OSPF, BGP, MPLS). Advanced topics in routing such as Segment Routing, SD-WAN, and routing for large-scale networks. Adaptive and scalable routing mechanisms for dynamic and complex network environments.
Machine Learning and AI for Network Optimization: Applications of machine learning for network traffic analysis, anomaly detection, and predictive maintenance. Intelligent resource allocation, fault management, and dynamic network adaptation using AI. Challenges of applying AI/ML in networking, including data requirements, model deployment, and scalability.
Edge Computing and Content Delivery Networks (CDN): The role of edge computing in reducing latency and enhancing service delivery. Architecture and operation of CDNs and their role in improving content availability and performance. Integration of edge networks with core networks and the challenges of distributed data processing.
Next-Generation Network Protocols and Trends: Exploration of new protocols like QUIC, HTTP/3, and Multipath TCP. Emerging technologies such as 6G, satellite-based internet, and mesh networking. Analysis of current and future trends in networking, including quantum networking, network automation, and zero-trust architectures.

Laboratory and Case Study:

Lecture-1 (Configuration of a managed. switch for LAN and WAN).
Lecture-3 (Configuration of a Firewall in WAN, and Data Center environment).
Lecture-7 (Configuration of an enterprise router in Data Center environmen).

References:

Andrew S. Tannenbaum, Computer Networks, Pearson Education, 2011.
Uyless Black, Computer Networks: Protocols, Standards, and Interfaces, PHI, 2008.
James F. Kurose, Keith W. Ross, Computer Networking: A Top-Down Approach, 2018.
Jim Doherty, SDN and NFV Simplified: A Visual Guide to Understanding Software Defined Networks and Network Function Virtualization, 2016.
Rajkumar Buyya, Amir Vahid Dastjerdi, Internet of Things: Principles and Paradigms, 2016.
William Stallings, Network Security Essentials: Applications and Standards, 2016.
Éric Gaussier, Giovanni Maria Galati, Mehdi Amine Khorsand, Radu State, Machine Learning for Networking: Basics, Concepts & Applications, 2018.
Rajkumar Buyya, Mukaddim Pathan, Athena Vakali, Content Delivery Networks: Fundamentals, Design, and Evolution, 2008.
Byrav Ramamurthy, Next-Generation Internet: Architectures and Protocols, 2011.

MICT-2002: Advanced Optical Communication

Credit Hour: 3.0

Course Objectives:

To gain a comprehensive understanding of the basic principles of optical communication, including light propagation through fibers and optical waveguides.
To study and analyze ray theory and mode theory, as well as how light behaves and propagates within different types of fibers, including specialty fibers.
To understand various fiber impairments such as fiber loss, chromatic dispersion, birefringence, and polarization mode dispersion (PMD), and explore techniques for compensating these impairments.
To examine critical components in optical communication systems such as transmitters, receivers, optical amplifiers, filters, and advanced modulation/detection schemes.
To get familiar with optical network architectures (AON, PON, SONET/SDH) and explore advanced transmission technologies such as WDM, OTDM, and OFDM.

Course Outcomes:

Upon the completion of this course, students will be able to:

Understand of the theoretical and practical aspects of optical communication, enabling them to design and analyze optical systems.
Assess fiber characteristics such as loss, dispersion, and nonlinearities, and understand how this affect signal transmission.
Implement compensation techniques for chromatic dispersion and other impairments, ensuring efficient transmission in optical systems.
Analyze receiver performance, calculate bit error rates (BER), sensitivity, and understand factors leading to sensitivity degradation in optical communication systems.
Gain an understanding of advanced optical networking technologies (WDM, OFDM, OTDM) and network protocols (AON, PON, SONET/SDH), preparing them for practical work in the field.

Course Content:

Introduction to optical communication, Ray theory and mode theory of light propagation, FSO communication, Different types of fibers, specialty fibers, Wave Equation and Coupling Modes in optical waveguide, Fiber loss, Chromatic dispersion, Birefringence and PMD Chromatic dispersion compensation, Higher order dispersion.
Fiber nonlinearities: SPM, XPM, FWM, Optical transmitters and receivers, Optical Amplifiers, Optical Filters, Advanced Optical Modulation and Detection Schemes, Receiver noise analysis, BER calculation, Sensitivity calculation, Sensitivity degradation.
Introduction to Soliton transmission, Optical networks, AON, PON, SONET/SDH, OFDM, OTDM and WDM transmission systems.

Laboratory and Case Study:

Analog and digital signal transmission through fiber-optic link.
Characterization of single-mode fibers and multimode fibers and testing their data transmission capacity.
Measurement of fiber loss and chromatic dispersion for different types of fibers (SSMF, DSF etc.) using measuring equipment.
A case study on an optical network design and performance test, like access network (AON and/or PON).

References:

Gerd Keiser, Optical Fiber Communications, 5th Edition, McGraw-Hill Education, 2021.
Gerd Keiser, Optical Fiber Communications, 5th Edition, McGraw-Hill Education, 2021.
Ivan P. Kaminow, Tingye Li, Alan E. Willner, Optical Fiber Telecommunications Volume VIB: Systems and Networks, 6th Edition, Academic Press, 2013.
John M. Senior, Optical Fiber Communications: Principles and Practice, 3rd Edition, Pearson Education, 2009.

MICT-2003: Advanced Database Management Systems

Credit Hour: 3.0

Course Objectives:

To analyze advanced concepts of database management systems and their applications in real-world scenarios.
To design and implement complex database solutions using modern technologies and methodologies.
To evaluate and optimize database performance in distributed and cloud environments.
To explore emerging trends in database technologies, including NoSQL, NewSQL, and big data systems.
To develop critical thinking skills in solving database-related problems in various domains.

Course Outcomes:

Upon the completion of this course, students will be able to:

Demonstrate advanced knowledge of database management systems, including relational, NoSQL, and NewSQL databases.
Design and implement complex database schemas and applications using industry-standard methodologies (e.g., ER modeling, normalization).
Optimize database performance by tuning SQL queries, indexing, and partitioning techniques.
Evaluate and select appropriate database technologies for specific use cases, considering factors like scalability, performance, and cost.
Implement distributed database solutions using technologies like Hadoop, Spark, and cloud-based database services.
Analyze and troubleshoot database performance issues using monitoring and profiling tools.
Apply data mining and machine learning techniques to extract insights from large datasets.

Course Content:

Advanced Relational Database Concepts: Review of relational model and normalization, Advanced SQL features (recursive queries, windowing functions), Query optimization and execution plans, Concurrency control and transaction management, Recovery techniques and logging.
Distributed and Parallel Databases: Distributed database architecture and design, Data fragmentation, replication, and allocation, Distributed query processing and optimization, Parallel database systems and architectures, Consistency models and distributed transactions.
NoSQL and NewSQL Databases: Introduction to NoSQL databases, Types of NoSQL databases (key-value, document, column-family, graph), NewSQL databases and their characteristics, CAP theorem and its implications, Consistency models in distributed NoSQL systems.
Big Data Management and Analytics: Introduction to big data concepts, Hadoop ecosystem and MapReduce paradigm, Distributed file systems (HDFS), Data warehousing and OLAP in big data context, Stream processing and real-time analytics.
Cloud Database Management: Cloud computing models (IaaS, PaaS, SaaS), Database-as-a-Service (DBaaS) offerings, Scalability and elasticity in cloud databases, Security and privacy concerns in cloud databases, Performance tuning and monitoring in cloud environments.
Emerging Trends in Database Systems: AI and ML-driven query optimization, AI and machine learning in database management, Data mining and knowledge discovery in databases (KDD), Blockchain databases and their applications.

Laboratory and Case Study:

Advanced Relational Database Concepts

Case Study 1: E-commerce Platform Optimization

Scenario 1: Optimize complex queries for product recommendations based on user

behavior.

Scenario 2: Implement efficient concurrency control for high-volume order processing.

Distributed and Parallel Databases

Case Study 2: Global Banking System

Scenario 1: Design a distributed database architecture for a multinational bank.

Scenario 2: Implement parallel query processing for real-time fraud detection.

NoSQL and NewSQL Databases

Case Study 3: Social Media Analytics Platform

Scenario 1: Choose appropriate NoSQL database(s) for storing and analyzing social

media data.

Scenario 2: Implement a NewSQL solution for real-time trending topic analysis.

Big Data Management and Analytics

Case Study 4: IoT-based Smart City Management

Scenario 1: Design a big data pipeline for processing and analyzing sensor data from

various city services.

Scenario 2: Implement real-time analytics for traffic management and public

transportation optimization.

Cloud Database Management

Case Study 5: SaaS-based Customer Relationship Management (CRM) System

Scenario 1: Migrate an on-premises CRM database to a cloud-based DBaaS solution.

Scenario 2: Implement scalability and performance optimization for a global CRM

platform.

Emerging Trends in Database Systems

Case Study 6: Blockchain-based Supply Chain Management

Scenario 1: Design a blockchain database for tracking product authenticity and

provenance.

Scenario 2: Implement a multi-model database solution for integrating traditional and blockchain-based supply chain data.

References:

Ramakrishnan, R., & Gehrke, J., Database Management Systems (3rd Edition), McGraw-Hill Education, 2003.
Silberschatz, A., Korth, H. F., & Sudarshan, S., Database System Concepts (6th Edition), McGraw-Hill Education, 2010.
Elmasri, R., & Navathe, S. B., Fundamentals of Database Systems (7th Edition), Pearson Education, 2016.
Abiteboul, S., Hull, R., & Vianu, V., Foundations of Databases, Addison-Wesley, 1995.
Stonebraker, M., & Hellerstein, J. M., Readings in Database Systems (4th Edition), Morgan Kaufmann, 2005.

MICT-2004: Advanced Telecommunication Network

Credit Hour: 3.0

Course objectives:

To understand the evolution of telecommunication networks from PSTN to 6G and key advancements.
To learn OSI and TCP/IP models' roles and functions in network communication.
To understand digital modulation, signal encoding, compression, channel coding, and multiplexing techniques.
To study cellular network architecture and evolution from 1G to 6G, focusing on technologies and mobility management.
To compare circuit-switched and packet-switched networks, IMS, VoIP technologies, and protocols like SIP and RTP.
To explore broadband access (xDSL, fiber optics, wireless), optical communication (WDM, OTN), and next-gen networks (SDN, NFV, 5G slicing).

Course Outcomes:

Upon the completion of this course, students will be able to:

Describe how telecommunication networks have evolved from PSTN to 6G, including the key technologies driving these changes.
Map real-world telecommunication scenarios to the OSI and TCP/IP models and understand the role of each layer in efficient communication.
Demonstrate proficiency in applying digital modulation, channel coding, and multiplexing techniques (e.g., QAM, FEC, TDM) to design basic communication systems.
Explain cellular architecture, the technologies behind 1G to 6G networks, and how frequency reuse, handover, and mobility management are achieved.
Set up basic IP-based telephony systems, using VoIP protocols like RTP and SIP, and understand network convergence through VoLTE and VoWiFi.
Evaluate different broadband access technologies (xDSL, fiber, wireless), explain the fundamentals of optical communication, and describe the principles of next-generation networks like SDN and NFV.

Course Content:

Fundamentals of Telecommunication Networks: Evolution of Telecommunication Networks (From PSTN to 6G), OSI and TCP/IP models: Role of each layer in telecommunications, Telecommunication Network Topologies: Mesh, Star, Ring, Hybrid, Network Services: Voice, Data, and Multimedia.
Digital Communication Systems: Digital Modulation Techniques: QAM, PSK, FSK, Signal Encoding and Compression (PCM, DPCM), Channel Coding (FEC, Hamming Codes, Reed-Solomon), Multiplexing Techniques: TDM, FDM, OFDM, Spread Spectrum and CDMA.
Mobile Communication and Cellular Networks (1G to 6G): Cellular Architecture: Cells, Clusters, Frequency Reuse, Evolution of Mobile Networks: 1G to 6G (Key Technologies, Data Rates, Frequency Bands), GSM, GPRS, EDGE, UMTS, LTE, 5G and Beyond (6G Vision), Modulation, Channel Access, and Multiple Access Techniques (TDMA, CDMA, OFDMA), Handover Mechanisms, Roaming, and Mobility Management.
Core Network Architectures and IP-Based Telephony: Circuit-Switched vs Packet-Switched Networks, IMS (IP Multimedia Subsystem) Architecture, Voice over IP (VoIP), RTP, SIP, H.323 Protocols, Call Setup, Signaling, and Session Management (SS7, SIP), Network Convergence: VoLTE, VoWiFi.
Broadband Access Networks: xDSL Technologies (ADSL, VDSL), Fiber Optic Networks (FTTH, FTTN), Cable Broadband (HFC Networks), Wireless Broadband: WiMAX, LTE-A, 5G NR, Passive Optical Networks (PON, GPON).
Optical Communication and Networks: Fundamentals of Optical Fiber Communication (Single-mode vs Multi-mode), Wavelength Division Multiplexing (WDM, DWDM, CWDM), Optical Transport Networks (OTN), Optical Amplification, Dispersion, and Attenuation Management, Free Space Optical (FSO) Communication.
Next-Generation Networks (NGN): Architecture of NGN (Softswitch, Media Gateways), SDN (Software-Defined Networking) and NFV (Network Function Virtualization), Network Slicing and QoS in 5G Networks, Edge Computing and MEC (Mobile Edge Computing).
Satellite Communication Systems: Satellite Orbits (LEO, MEO, GEO), Satellite Communication Fundamentals (Uplink, Downlink, Transponders), VSAT, MSS, and FSS Systems, Satellite Applications: GPS, Satellite Internet, Broadcasting, Challenges in Satellite Communication (Latency, Atmospheric Effects).
Telecommunication Network Security: Threats in Telecommunication Networks (Denial of Service, Eavesdropping), Security Protocols: IPsec, SSL/TLS, SRTP, Firewalls, IDS/IPS, and VPNs in Telecom Networks, Security in 5G Networks (Authentication, Encryption, Privacy), Telecom Fraud Prevention (SIM Cloning, Bypass Fraud).

Laboratory and Case Study:

1. 1. 1. PSTN Network Simulation and Call Flow Analysis: Simulate a simple PSTN network (analog/digital) using software like Cisco Packet Tracer or a basic hardware setup. Analyze call flows, signaling (e.g., DTMF tones), and bandwidth requirements for simplex, half-duplex, and full-duplex communication.
    2. DSL Performance and Signal Quality Analysis: Measure the performance of Digital Subscriber Line (DSL) connections over copper pairs. Evaluate noise, attenuation, and power levels in the local loop using simple test equipment and tools.
    3. TDM and FDM Multiplexing Techniques: Simulate and compare Frequency Division Multiplexing (FDM) and Time Division Multiplexing (TDM) using a network simulator. Analyze the advantages and disadvantages of each for different transmission media.
    4. Optical Fiber Communication: Power Loss and Signal Degradation: Set up an optical fiber communication link and measure power loss, signal degradation, and the impact of distance and connectors on signal quality.
    5. Satellite Communication System Analysis: Simulate or model a basic satellite communication network (NGSO or GSO). Investigate concepts like uplink, downlink, frequency bands, and latency.
    6. PLMN Signaling Protocols in Cellular Networks (1G to 5G): Compare the signaling protocols used in different generations of cellular networks (1G, 2G, 3G, 4G, and 5G). Simulate and analyze how signaling impacts call setup, data transfer, and channel management.
    7. ISDN Architecture and Call Setup Simulation: Simulate a basic ISDN network, including call setup and subscriber access. Evaluate how SS7 signaling works in an ISDN environment using tools like GNS3.
    8. VoIP Network Setup and Performance Analysis: Configure a basic VoIP network using open-source tools (e.g., Asterisk). Measure performance in terms of packet loss, jitter, and latency compared to traditional PSTN.
    9. Addressing and Routing Simulation: Set up networks using both Ipv4 and Ipv6 addressing schemes. Compare the routing techniques, subnetting, and performance for each protocol.
    10. Mobile Communication Systems: Simulate a basic 5G network using a network simulator. Explore key concepts such as channel management, frequency bands, and latency improvements over previous generations.

Required Tools and Software:

Cisco Packet Tracer/GNS3: For PSTN, VoIP, ISDN, and routing simulations.
Wireshark: To analyze network traffic, signaling, and performance metrics.
Matlab/Simulink: For signal analysis and coding techniques (e.g., PCM, TDM).
NS-3/OMNeT++: For complex simulation tasks like 5G and satellite communications.

References:

T. Anttalainen, Introduction to Telecommunications Network Engineering, Artech House, Boston, 1999.
J. Bellamy, Digital Telephony, John Wiley & Sons, 1991, 580 pp.
T. Saadawi, Fundamentals of Telecommunication Networks, John Wiley & Sons, Inc., 1994.
M.P. Clark, Networks and Telecommunications, John Wiley & Sons, 1991.
R. L. Freeman, Telecommunication System Engineering, John Wiley & Sons, Second Edition, 1989.
Pramode K. Verma, ISDN Systems: Architecture, Technology and Applications, Prentice Hall, 1990.
William Stallings, strong>Advances in ISDN and Broadband ISDN, IEEE Comp. Soc. Press, 1993.
B. G. Lee, Broadband Telecommunications Technology, Artech House, Boston, 1996.
P.-G. Fontolliet, Telecommunication Systems, Artech House, 1986
ITU-T Recommendations given in CCITT Blue Books related to PSTN, ISDN, Data Networks, etc.
Hemani Kaushal, V.K. Jain, Subrat Kar . Free Space Optical Communication.

MICT-2005: Internet of Things (IoT)

Credit Hour: 3.0

Course Objectives:

To understand various physical phenomenon of different types of sensors (magnetic, optical, bio, chemical, radiation, electrical and mechanical etc.) and microsystems.
To design complete systems using sensors with appropriate electronic interface.
To explore the challenges and solutions related to security, privacy, and ethical considerations in IoT, ensuring the protection of data and devices.
To study the application of IoT in various domains, such as smart cities, healthcare, industrial automation, agriculture, and environmental monitoring.
To gain practical experience through projects, labs, and case studies, allowing students to apply theoretical knowledge to real-world IoT scenarios.

Course Outcomes:

Upon the completion of this course, students will be able to:

Proficient in using IoT technologies, including programming microcontrollers, configuring sensors, and working with IoT communication protocols.
Design, develop, and deploy end-to-end IoT solutions, from device-level programming to cloud integration and data analysis.
Equip with problem-solving skills to identify challenges in various industries and apply IoT solutions to address them effectively.
Gain a strong understanding of the security and privacy challenges in IoT and will be able to implement best practices to safeguard IoT systems.
Achieve hands-on experience with IoT projects, demonstrating their ability to work on real-world applications and contribute to the industry.
Demonstrate an interdisciplinary understanding of IoT, combining knowledge of hardware, software, data science, and business applications.
Prepare for careers in IoT-related fields, with the skills necessary to work in roles such as IoT developer, system architect, data analyst, or IoT security expert.

Course Content:

Internet in General and Internet of Things: Layers, Protocols, Packets, Services, Performance Parameters of a Packet Network as well as Applications such as Web, Peer-to-peer, Sensor networks, and Multimedia.
IoT Definitions: Overview, Applications, Potential and Challenges, and Architecture.
IoT Protocols: HTTP, CoAP, MQTT, AMQP, 6LoWPAN. IoT Data and the IoT Cloud Infrastructure. Performance and Security in IoT. IoT examples: Case Studies, e.g., Sensor Body-Area-Network and Control of a Smart Home.
Sensors and Actuators: Basic sensor technology, Sensor systems; Smart sensors basics; Smart sensors: Characteristics; Smart sensors architectures; Smart sensors buses and interfaces; Smart sensors software; Data acquisition methods for smart sensors; Virtual sensor systems; Smart sensors for electrical and non-electrical variables.
Sensor networks architectures: Single node architecture; Multi node architectures; Design principles; Energy efficient topologies; Wired sensor networks and wireless sensor networks; Applications.
Communication protocols: Physical layer; MAC protocols; Link layer protocols; Localization and positioning; Routing protocols; Transport layer; Data gathering and processing: Protocols for gather information; Data processing techniques.
Energy management: Energy consumption of sensor nodes; energy harvesting; Techniques for reducing consumption and communication energy; Energy aware routing.
IOT Security, reliability and fault-tolerance: Security and privacy protection; Reliability support; Fault-tolerance; Sensor networks standards; platforms and tools: IEEE 802.15.4 and IEEE 802.11; Berkeley motes; Operating systems.

Laboratory and Case Study:

Hands on integration of different temperature sensors with microcontroller.
Interfacing Air Quality Sensor (e.g. MQ135) - display data on LCD, switch on LED when data sensed is higher than specified value.
Use Node MCU to upload free data from Environmental Sensors to Cloud Server.
IOT based Home Automation System on a local and a Live Server.
Smoke and Gas Detection Using MQ2 Sensor and Thing Speak or Blynk IOT Platforms.
Case study on application of IOT in healthcare industry.
Case study on application of IOT in smart city.
Case study on application of IOT in garments industry in Bangladesh.
Case study on application of IOT in surveillance.
Case study on application of IOT in agriculture.

References:

1. 1. 1. N. V. Kirianaki, S. Y. Yurish, N. O. Shpak V. P. Deynega: Data Acquisition and Signal Processing for Smart Sensors, John Wiley, 2004.
    2. H. Karl, A. Willig: Protocols and Architectures for Wireless Sensor Networks, John Wiley, 2005.
    3. M. Ilyas, I. Mahgoub (ed.): Handbook of Sensor Networks: Compact Wireless and Wired Sensing Systems, CRC, 2004.
    4. Arshdeep Bahga and Vijay Madisetti, Internet of Things: A Hands-On Approach, 1st Edition, 2014, VPT (Universities Press), ISBN: 978-0996025515.
    5. Olivier Hersent, David Boswarthick, and Omar Elloumi, The Internet of Things: Key Applications and Protocols, 2nd Edition, 2012, Wiley, ISBN: 978-1119994350.
    6. Peter Waher, Mastering Internet of Things: Design and Create Your Own IoT Applications Using Raspberry Pi, Arduino, and ESP8266, 1st Edition, 2018, Packt Publishing, ISBN: 978-1788397483.

MICT-2006: Cellular Mobile Communication

Credit Hour: 3.0

Course objectives:

To understand cellular systems' essential principles, including their structure, function, and operation.
To understand the diverse propagation models and speech coders utilized in mobile communication is essential.
To gain an understanding of the techniques employed in mobile communication for managing multiple access and mitigating interference."

Course Outcomes:

Upon the completion of this course, students will be able to:

Exploring the fundamental concepts of cellular radio technology, including cell structure, frequency reuse, and handoff procedures.
Identifying and analyzing various propagation effects such as reflection, diffraction, and scattering in wireless communication environments.
Gaining insight into the specific technical requirements and standards governing mobile systems, including network architecture, frequency bands, and modulation schemes.
Categorizing and explaining different multiple access techniques used in mobile communication, such as TDMA, CDMA, and FDMA.
Providing an overview of the prevailing cellular mobile communication standards, such as GSM, CDMA2000, and LTE, including their technical specifications and historical evolution.
Evaluating and discussing a range of methodologies aimed at enhancing cellular capacities, such as vectorization, microcell deployment, and advanced antenna technologies.

Course Content:

1. 1. 1. Introduction to Cellular Mobile Radio Background and History: Conventional Mobile Radio Versus Cellular Mobile Radio; Features of Cellular Radio; Digital Cellular Radio; Trends in the Use of Cellular Services.
    2. Mobile Radio Environment: Lowpass Equivalent Representation: Bandpass Signals and Linear Bandpass Systems; Multipath Propagation: Path Loss, Doppler Effect, Rayleigh Fading and Rician Fading; Statistics of Slow and Fast Fading; Classification of Channels: Time Dispersion and Frequency-Selective; Fading, Frequency Dispersion and Time-Selective Fading; Mathematical Modeling of Fading Multipath Channels.
    3. Diversity Schemes and Combining Techniques: Diversity Schemes: Space, Frequency, Polarization, Field Component, Angle, Time, and Multipath Diversity; Combining Techniques: Selective, Switched, Maximal-Ratio, Equal-Gain and Baseband Combining.
    4. Capacity Analysis of Multiple Access Methods: Spectral Efficiency of FDMA, TDMA and CDMA Systems, The Qualcomm CDMA, Capacity Equation; Bit Rate Capacity of FDMA, TDMA and CDMA Systems in Single-Cell and Multicell Environment.
    5. Cellular System: GSM, CDMA Cellular System, 3G CDMA System, 4G mobile system, 5G Wireless System. Next-Generation Mobile Communication.

Laboratory and Case Studies:

Signal Propagation and Path Loss Analysis: Experiment with different environments (urban, rural) to measure signal strength and analyze path loss using various models (e.g., Hata, Okumura).
Cellular Network Simulation: Use network simulation tools (e.g., NS-3, OPNET) to design and analyze cellular network topologies and performance metrics.
Interference Management: Study and implement techniques for managing interference, such as frequency reuse, power control, and interference cancellation.
Handovers and Mobility Management: Simulate handover scenarios in a cellular network and analyze the impact on service continuity and quality of experience.
5G Network Features: Explore and test key features of 5G networks such as massive MIMO, beamforming, and ultra-low latency.
Deployment Challenges in Urban Areas: Analyze a real-world case where cellular networks were deployed in a densely populated urban area, focusing on challenges such as interference, coverage, and capacity.
Evolution from 4G to 5G: Study the transition from 4G to 5G technology in a specific region or network, examining the changes in architecture, services, and performance.
Impact of IoT on Cellular Networks: Explore how the proliferation of IoT devices affects cellular network design and performance, including issues related to scalability and resource allocation.
Case Study on Network Security: Investigate a case where cellular network security was compromised, analyzing the vulnerabilities exploited and the measures taken to address them.
Rural Connectivity Solutions: Examine solutions for providing cellular connectivity in rural or underserved areas, including the use of low-cost infrastructure and satellite backhaul.
Quality of Experience (QoE) Analysis: Study a case where QoE was a critical factor, such as in a high-density event (e.g., sports stadium), and analyze how network design and management strategies impacted user satisfaction.

References:

C. Y. Lee and William, “Mobile Cellular Telecommunications,” 2nd Ed, McGraw Hill. 2001.
Mischa Schwartz, “Mobile Wireless Communications”, Cambridge Univ. Press, UK, 2005.
Mobile Communication Hand Book”, 2^nd Edition, IEEE Press. 2002.
Theodore S Rappapor.t, “Wireless Communication Principles and Practice,” 2^nd Ed, Pearson Education. 2002.
Lawrence Harte, “3G Wireless Demystified”, McGraw Hill Publications. 2000.
Kaveh Pahlavan and Prashant Krishnamurthy, “Principles of Wireless Networks,” PHI.2000.

MICT-2007: Recent Trends in ICT

Credit Hour: 3.0

Course Objectives:

To understand various physical phenomenon of different types of sensors (magnetic, optical, bio, chemical, radiation, electrical and mechanical etc.) and microsystems.
To design complete systems using sensors with appropriate electronic interface.
To explore the challenges and solutions related to security, privacy, and ethical considerations in IoT, ensuring the protection of data and devices.
To study the application of IoT in various domains, such as smart cities, healthcare, industrial automation, agriculture, and environmental monitoring.
To gain practical experience through projects, labs, and case studies, allowing students to apply theoretical knowledge to real-world IoT scenarios.
To examine the ethical implications of emerging ICT technologies and their impact on privacy, security, and society.

Course Outcomes:

Upon the completion of this course, students will be able to:

Demonstrate a comprehensive understanding of the latest advancements and emerging technologies in ICT.
Critically analyze the impact of ICT on various societal sectors, including business, education, healthcare, and government.
Utilize a variety of ICT tools and platforms effectively to support learning, research, and professional development.
Identify and analyze ethical dilemmas related to ICT, such as privacy concerns, data security, and intellectual property issues.

Course Contents:

A Recent Trends in ICT (Information and Communication Technology) course typically covers emerging technologies, innovations, and trends shaping the ICT landscape. This course structure ensures students are exposed to the most up-to-date developments in ICT, equipping them with knowledge and skills relevant to current and future industry demands.

Here's a breakdown of the possible course contents (NOT limited to):

Introduction to ICT Trends: Overview of ICT evolution, Historical context and impact on society, Key drivers of technological change.
Expandable AI: Introduction to Expandable AI, Scalability in AI Models, Modular AI Architectures, Transfer Learning and Domain Adaptation, Federated Learning, AI in Edge Computing, Ethics, Fairness, and Bias in Expandable AI, AI in Dynamic and Real-Time Environments, Emerging Trends in Expandable AI.
Augmented Reality (AR), Virtual Reality (VR), and Metaverse: Overview of AR/VR technologies and devices, Applications in gaming, education, healthcare, and training, Trends in immersive technology development, Challenges in AR/VR adoption (cost, usability, content creation).
Blockchain Technology: Introduction to blockchain and distributed ledger technology, Cryptocurrencies and smart contracts, Blockchain use cases beyond finance (supply chain, healthcare, etc.), Trends in decentralized applications (dApps) and NFTs, Challenges and future directions in blockchain.
5G and Next-Generation Networks: Evolution of mobile networks (from 4G to 5G), 5G architecture and key technologies (e.g., massive MIMO, beamforming), Applications of 5G (IoT, autonomous vehicles, smart cities), Challenges in 5G deployment (spectrum, security), Trends towards 6G and beyond.
Digital Transformation and Industry 4.0: Concepts of digital transformation in business and industry, Technologies driving Industry 4.0 (IoT, AI, robotics, etc.), Impact on manufacturing, supply chain, and business models.
Green ICT and Sustainability: Trends in energy-efficient computing and ICT systems, Role of ICT in promoting sustainability (smart grids, telecommuting, etc.), Green data centers and energy management in ICT, Environmental impact of emerging technologies
Ethics and Societal Impact of ICT: Ethical considerations in AI, data privacy, and cybersecurity, ICT and digital divide issues, Impact of ICT on employment and workforce dynamics, Regulatory and policy trends in ICT.
Emerging ICT Startups and Innovations: Analysis of recent ICT startups and innovations, Investment trends and venture capital in ICT, Challenges and opportunities for entrepreneurs in the ICT space.

Laboratory and Case Study:

Case study on developing AR/VR applications using tools like Unity or Unreal Engine, and evaluating user interaction and experience.
Case Study on reviewing the use of VR in remote training and education, including effectiveness, cost, and user feedback.
Case Study on evaluating a recent high-profile data breach (e.g., the Uber data breach) to understand how it occurred, the response, and the lessons learned for improving security measures.
Creating and managing a private blockchain using platforms like Hyperledger or Ethereum. Tasks might include developing smart contracts and exploring consensus mechanisms.
Case Study on analyzing the adoption of blockchain technology in supply chain management, focusing on transparency, traceability, and efficiency improvements.
Case Study on investigating the deployment of 5G technology in a specific region or sector (e.g., healthcare or manufacturing) and assessing its impact on service delivery and operational efficiency.
Practical applications of recent trends in ICT.
Group or individual projects analyzing or implementing a trend.

References:

Dr. P. Pachaiyappan, Current Trends in ICT and Education (Volume - 1), AkiNik Publications, 2022.
Russell, S., & Norvig, P., Artificial Intelligence: A Modern Approach, Pearson Education, 2021.
Bahga, A., & Madisetti, V., Internet of Things: A Hands-On Approach, McGraw-Hill Education, 2021.
Buyya, R., Lee, C.-K., & Venugopal, T., Cloud Computing: Principles and Paradigms, Wiley-IEEE Press, 2010.
Komando, K., Cybersecurity: The Essential Guide to Staying Safe Online, Penguin Random House, 2021.
Wallach, W., & Allen, C., Ethics in the Age of AI, Oxford University Press, 2018.

MICT-2008: Advanced Data Communication

Credit Hour: 3

Course Objectives:

To explain the OSI model, TCP/IP stack, network topologies, and key network devices and types.
To understand data transmission principles, encoding/decoding, data link protocols, and error detection methods.
To differentiate between TDM, FDM, and WDM multiplexing techniques.
To learn advanced routing/switching protocols (OSPF, BGP, VLAN), IPv4/IPv6 addressing, and subnetting.
To understand wireless communication standards, mobile network protocols, encryption, VPNs, firewalls, IDS, and secure communication protocols.

Course Outcomes:

Upon the completion of this course, students will be able to:

Describe the OSI model, TCP/IP stack, and configure basic network devices in various topologies
Encode and decode digital data, select appropriate transmission media, and explain the relationship between bandwidth, bit rate, and baud rate.
Use error detection and correction methods, as well as flow control mechanisms, to ensure data reliability and efficiency in communication.
Design network systems using TDM, FDM, or WDM and make informed decisions about the appropriate switching techniques (circuit vs packet) for various scenarios.
Configure advanced routing, switching, and wireless protocols, demonstrating proficiency in subnetting and network addressing in both wired and wireless environments.
Implement security protocols, firewalls, and VPNs, while applying QoS and traffic management techniques to optimize multi-service networks for voice, video, and data traffic.

Course Content:

Introduction to Data Communication Fundamentals: OSI Model and TCP/IP Stack, Network Topologies, Devices (Routers, Switches, Hubs), Types of Networks (LAN, WAN, MAN, PAN), Physical Layer and Data Link Layer protocols (Ethernet, PPP).
Data Communication Techniques: Data transmission, Data encoding and decoding, Digital data communication techniques, Data link control, HDLC, Multiplexing, Transmission media, Signal Bandwidth, Bit Rate, and Baud Rate.
Error Detection, Correction, and Flow Control: Error Detection Techniques (CRC, Parity Check), Error Correction Techniques (Hamming Code, Reed-Solomon), Flow Control Mechanisms (Stop-and-Wait, Sliding Window).
Multiplexing and Switching Techniques: Time Division Multiplexing (TDM), Frequency Division Multiplexing (FDM), Statistical Multiplexing, Wavelength Division Multiplexing (WDM), Circuit Switching vs Packet Switching (MPLS, ATM) .
Advanced Networking Protocols and Standards: Routing Protocols (OSPF, BGP, RIP, EIGRP), Switching Protocols (STP, VTP, VLAN), IPv4/IPv6 Addressing and Subnetting, Transport Protocols: TCP, UDP, SCTP, SMTP.
Wireless and Mobile Data Communication: 802.11 (Wi-Fi) Standards, Wi-Fi 6, Cellular Networks (LTE, 5G), Mobile IP and Handover Techniques, Wireless Security Protocols (WPA3, EAP, RADIUS).
Optical and Satellite Communication: Fiber Optic Communication (Wavelength Division Multiplexing), Free-Space Optical Communication (FSO), Satellite Communication Fundamentals (LEO, MEO, GEO).
Network Security in Data Communication: Encryption Techniques (Symmetric vs Asymmetric), VPNs, Firewalls, and Intrusion Detection Systems (IDS), SSL/TLS, IPsec, HTTPS, Secure Protocols for Data Communication (SSH, SFTP).
Quality of Service (QoS) and Traffic Management: QoS Mechanisms (DiffServ, IntServ), Traffic Shaping, Policing, and Prioritization, Bandwidth Allocation in Multi-service Networks (Voice, Video, Data), Performance Monitoring and Optimization, Cloud Connectivity: VPN, MPLS, Direct Connect.

Laboratory and Case Study:

OSI Model and TCP/IP Stack Simulation: Simulate a basic TCP/IP network using Cisco Packet Tracer or GNS3. Visualize the encapsulation and de-encapsulation process across OSI layers by sending data between two nodes.
Signal Encoding Techniques and Transmission: Implement digital encoding techniques like Manchester or Differential Manchester coding in MATLAB or a hardware simulator. Analyze the signals' performance in terms of noise resistance and transmission efficiency.
Error Detection and Correction in Data Transmission: Simulate data transmission with built-in error using CRC (Cyclic Redundancy Check) or Hamming Code algorithms. Inject errors and verify the detection/correction process.
Time Division Multiplexing (TDM) and Frequency Division Multiplexing (FDM): Simulate both TDM and FDM in a software environment. Transmit multiple signals over a single communication link, observe the bandwidth utilization, and compare performance metrics.
VLAN Configuration and Traffic Isolation: Configure VLANs (Virtual Local Area Networks) on a set of switches using Cisco Packet Tracer or physical hardware. Observe how traffic is isolated between different VLANs and measure performance under different configurations.
IPv6 Addressing and Subnetting: Design and configure an IPv6 network using a simulator like GNS3 or Packet Tracer. Assign IP addresses, perform subnetting, and test connectivity using ping and traceroute commands.
Wireless Network Configuration (Wi-Fi): Set up a Wi-Fi network using 802.11 standards, configure security protocols (WPA2/WPA3), and measure signal strength, bandwidth, and interference using available software or a Wi-Fi analyzer.
MPLS Traffic Engineering and QoS: Simulate an MPLS (Multi-Protocol Label Switching) network and configure traffic engineering features like QoS prioritization. Analyze the performance for different types of traffic (voice, video, data).

Required Tools and Software:

GNS3/Cisco Packet Tracer: For network simulations, routing, and VLAN configurations.
Wireshark: For packet analysis and protocol inspection.
MATLAB/Simulink: For signal processing, multiplexing, and error correction tasks.

References:

A. Forouzan, Data Communications and Networking, 5^th Edition, McGraw-Hill Education, 2012.
Andrew S. Tanenbaum, David J. Wetherall, Computer Networks, 5^th Edition, Pearson, 2010.
William Stallings, Data and Computer Communication, 10^th Edition, Pearson, 2013.
John G. Proakis, Masoud Salehi, Fundamentals of Communication Systems, 2^nd Edition, Pearson, 2013.
Behrouz A. Forouzan, TCP/IP Protocol Suite, 4^th Edition, McGraw-Hill Education, 2009.
William Stallings, Network Security Essentials: Applications and Standards, 6^th Edition, Pearson, 2020.
Jean Walrand, Pravin Varaiya, High-Performance Communication Networks, 2nd Edition, Morgan Kaufmann, 2000.

MICT-2009: Information Security

Credit Hour: 3.0

Course Objectives:

To understand how Information Security can counteract attempts to attack an individual’s “info sphere,” the person’s sensitive information.
To provide the fundamental skills and understanding needed to manage risk & recover disaster.
To acknowledge the students about the fundamentals of cryptography and how cryptography serves as the central language of information security.
To understanding how issues of privacy affect information security.
To gain the fundamental knowledge of Cyber Security and commonly used terms in Cyber Security.
To Understand Cyber Security / Information Security Architecture.
To know how vulnerabilities, occur and how to limit your exposure to them.
To gain a fundamental understanding of what an attack/threats are and how to identify and prevent them from occurring.
To know the international laws in securing cyberspace.

Course Outcomes:

Upon completion of this course, graduates will be able to:

Demonstrate a basic understanding of the practice of Information Security, especially in evaluation of information security risks across diverse settings including the Internet and WWW based commerce systems, high bandwidth digital communications and funds transfer services.
Acknowledge the ethical considerations in all judgments and decisions in academic and professional settings.
Utilize software packages (for example Maple) to explore the intricacies of cryptography, demonstrating comprehension of the use of these and other tools in Information Security.
Possess a fundamental knowledge of Cyber Security.
Understand what a vulnerability is and how to address most common vulnerabilities.
Know basic and fundamental risk and disaster management principles as it relates to Cyber Security.
Demonstrate and apply knowledge of current trends in ICT security, particularly those that relate to security protocols and policy, cryptography, malware, digital forensics, and legal evidence.
Investigate emerging security trends and their application to professional practice.
Apply skills in the identification of security threats, implementation of secure system properties, security testing, and incident response.

Course Content:

1. 1. 1. Introduction to Information Security / cyber security: The Need for Security; Information Security Standards and Frameworks, Cyber security models (the CIA triad, the star model), Types of Cyber-attacks; Attack motives that drives an attacker; Methods of cyber-attack & attack vectors; Cybercrime, Cyber harassment, Cyber warfare, Cyber surveillance, Issues making cyber security difficult, Cloud Computing and Distributed Computing, Blockchain Technology for cybersecurity.
    2. Legal, Ethical, Professional Issues in Information Security: Types of Risks and Risk Management Frameworks (RMF); Disaster recovery plan and procedures, National ICT Act & Policy, National Information security policy guideline, government and private sector role’s in securing cyberspace, International laws in securing cyberspace.
    3. Access Control & Identity and Access Management: Protection Domains, Access Control Lists, User Privilege in Database Systems; Authentication: Authentication using a physical object, Authentication using biometrics; Control physical and logical access to assets; manage identification and authentication of people, devices, and services; federated identity with a third-party service; implement and manage authorization mechanisms; manage the identity and access provisioning lifecycle; implement authentication systems.
    4. Cryptography: Symmetric Cryptography, Public Key Cryptography: RSA cryptosystem–Key distribution – Key management –Diffie Hellman key exchange-ElGamal cryptosystem Elliptic curve arithmetic-Elliptic curve cryptography. Symmetric Key Ciphers: DES–Block cypher Principles of DES – Strength of DES – Differential and linear cryptanalysis - Block cypher design principles – Block cypher mode of operation – Evaluation criteria for AES – Advanced Encryption Standard-RC4–Key distribution. Message Authentication and Integrity: Authentication requirement – Authentication function –MAC–Hash function–Security of hash function and MAC – SHA –Digital signature and authentication protocols–DSS- Entity Authentication: Biometrics, Passwords, Challenge Response protocols- Authentication applications - Kerberos, X.509. Security Practice and System Security: Electronic Mail security–PGP, S/MIME –IP security – Web Security - SYSTEM SECURITY: Intruders–Malicious software – viruses – Firewalls.
    5. Asset Security: Asset Security, Data Management: Determine and Maintain Ownership, Data Standards, Longevity and Use, Classify Information and Supporting Assets, Asset Management, Protect Privacy, Ensure Appropriate Retention, Determine Data Security Controls, Standards Selection.
    6. Security Engineering: Security Engineering, The Engineering Lifecycle Using Security Design Principles, Fundamental Concepts of Security Models, Information Systems Security Evaluation Models, Security Capabilities of Information Systems, Vulnerabilities of Security Architectures, Database Security, Software and System Vulnerabilities and Threats, Vulnerabilities in Mobile Systems, Vulnerabilities in Embedded Devices and Cyber-Physical Systems, The Application and Use of Cryptography, Site and Facility Design Considerations, Site Planning, Implementation and Operation of Facilities Security.
    7. Configuration Management & Systems Hardening: OS, Database Management Systems, Networking Solutions and Devices, Software, Secure Systems, Trusted Computing Base, Firewalls, Antivirus and Anti-Antivirus Techniques, Digital Signatures, Code Signing, Jailing, Model-Based Intrusion Detection Systems, Encapsulating Mobile Code, Java Security.

Laboratory and Case Study:

Case Study on Cybersecurity and Risk Framework.
Case Study on Identity and Access Management architecture design and Risk Assessment.
Case Study on Security Architecture and Engineering.
Configuration Review and Hardening of different Operating Systems.
Configuration Review and Hardening of different Database Management Systems.
Configuration Review and Hardening for Network Devices, i.e., Router, Switch.
Configuration Review and Hardening for Security Solutions, i.e., Firewall, Email Security, Anti-DDOS, Sandbox, Web Proxy, etc.
Hardening and Configuration Review Lab for Utility and Security Solutions.
Course Final Project Assignment on Systems Hardening and Configuration Review.

References:

Michael E. Whitman, Herbert J. Mattord, Principles of Information Security, Cengage Learning, 2021.
Jason Andress, The Basics of Information Security, Wiley, 2018.
David Sutton, Cyber security: A practitioner’s guide, Wiley, 2021.
P.W. Singer, Allan Friedman, Cyber security and Cyber war: What Everyone Needs to Know, Oxford University Press, 2014.
Mark Rhodes-Ousley, Information Security: The Complete Reference, McGraw-Hill, 2013.
Don Franke, Cyber Security Basics: Protect your organization by applying the fundamentals, CRC Press, 2019.

MICT-2010: Advanced Digital Communication

Credit Hour: 3.0

Course objectives:

To provide a comprehensive understanding of advanced digital communication systems and their underlying principles.
To develop a strong foundation in the mathematical and statistical tools necessary for analyzing and designing digital communication systems.
To understand the fundamental concepts of digital communication systems, including modulation, demodulation, channel coding, and synchronization.
To integrate contemporary communication systems and is instrumental in facilitating the advancement of forthcoming communication technologies, which will prepare students for the future of digital communication.

Course Outcomes:

Upon completion of this course, students will be able to:

Understand fundamental and advanced digital communications concepts.
Ascertain the minimum bit rate required for encoding continuous-valued signals, considering a predefined maximum distortion level in the context of source coding.
Explain the trade-offs between complexity and quality in practical systems and quantify how close practical quantization and channel-coding algorithms can reach the theoretical limits provided by information theory.
Create scalar, vector quantization, and linear predictive coding schemes for practical signals. Furthermore, they can comprehend and apply contemporary channel coding concepts and digital modulation schemes in practical problem scenarios, which will help them understand the course content's real-world applications and feel prepared for the challenges of their future careers.

Course content:

1. 1. 1. Introduction: Digital communication system (description of different modules of the block diagram), Complex baseband representation of signals, Gram-Schmidt orthogonalization procedure, M-ary orthogonal signals, bi-orthogonal signals, simplex signal waveforms.
    2. Modulation: Pulse modulation and Digital transmission. Receiver in additive white Gaussian noise channels.
    3. Coding: Data compression techniques (Huffman coding, arithmetic coding, Lempel-Ziv coding), Rate-distortion theory, Error detection and correction codes (Hamming codes, cyclic codes, convolutional codes, turbo codes, LDPC codes), Channel capacity theorem.
    4. Coherent and noncoherent demodulation: Matched filter, Correlator demodulator, square-law, and envelope detection; Detector: Optimum rule for ML and MAP detection Performance: Bit-error rate, symbol error rate for coherent and noncoherent schemes.
    5. Band-limited channels: Pulse shape design for channels with ISI: Nyquist pulse, Partial response signaling (duobinary and modified duobinary pulses), demodulation; channels with distortion: Design of transmitting and receiving filters for a known channel and for a time-varying channel (equalization); performance: symbol by symbol detection and BER, symbol and sequence detection, Viterbi algorithm.
    6. Synchronization: Different synchronization techniques (Early Late Gate, MMSE, ML, and spectral line methods). Communication over fading channels.

Laboratoey and Case Studty:

Generate and demodulate various digital modulation schemes (ASK, FSK, PSK, QAM). Analyze the bit error rate (BER) performance of different modulation schemes under different noise conditions.
Implement Hamming codes, cyclic codes, or convolutional codes. Analyze the error correction capability of different codes.
Implement Direct Sequence Spread Spectrum (DSSS) and Frequency Hopping Spread Spectrum (FHSS) systems. Analyze the interference rejection capabilities of spread spectrum techniques.
Implement an adaptive modulation and coding scheme based on channel conditions.
Simulate communication systems using MATLAB or Python. Analyze the performance of different system parameters (e.g., modulation scheme, coding rate, SNR).
Use Software-Defined Radio (SDR) platforms (e.g., GNU Radio, Ettus Research USRP) to implement real-world communication systems.

Reference:

T. Cover and J. Thomas, Elements of Information Theory, 2/e, Wiley, 2006
R. G. Gallager, Principles of Digital Communication, Cambridge Univ. Press, 2008.
A. Lapidoth, A Foundation in Digital Communication, Cambridge Univ. Press, 2009.
S. Lin and D. Costello, Error Control Coding, 2/e, Prentice Hall, 2004.
J. G. Proakis and M. Salehi, Digital Communications, 5/e, McGraw-Hill, Prentice Hall, 2007.
B. Sklar, Digital Communications: Fundamentals and Applications, 2/e, Prentice Hall, 2001.

MICT-2011: Advanced Algorithm & Optimization

Credit Hour: 3.0

Course Objectives:

To understand the theory of optimization methods and algorithms developed for solving various types of optimization problems.
To develop and promote research interest in applying optimization techniques in problems of Engineering and Technology.
To apply the mathematical results and numerical techniques of optimization theory to concrete Engineering problems.

Course Outcomes:

At the completion of this course, students will be able to:

Apply optimization methods to engineering problems including developing a model.
Define the optimization problems.
Apply optimization methods and e xplore the solution and interpret the results.
Develop the ability to choose and justify optimization techniques that are appropriate for

solving realistic engineering problems.

Course Content:

Optimization Problems; The Simplex Algorithm; Duality; Computational Considerations for the Simplex Algorithm; The Primal-Dual Algorithm; The Primal-Dual Algorithms for Max-Flow and Shortest Path: Ford-Fulkerson and Dijkstra; Primal-Dual Algorithms for Min-Cost Flow; Algorithms and Complexity; Efficient Algorithms for the Max-Flow Problem; Algorithms for Matching; Weighted Matching; Spanning tree and Matroids; Integer Linear Programming; A Cutting-Plane Algorithm for Integer Linear Programs; NP-Complete Problems; More About NP-Completeness; Approximation Algorithms; Unconstrained non-linear optimization problems; Constrained nonlinear optimization problems; Multi objective optimization problems; Evolutionary optimization algorithms; Adaptive Genetic Algorithm; Bayesian statistics as optimization technique; Artificial neural network; Optimization methods for inverse problems; Solving optimization problems using MATLAB.

Laboratory and Case Study:

Implement the simplex method to solve linear programming problems. Experiment with different initial feasible solutions and pivot rules.
Formulate the dual of a given linear program. Solve both the primal and dual problems and verify the duality theorem.
Implement the Ford-Fulkerson algorithm to find the maximum flow in a given network. Experiment with different flow augmentation paths.
Implement the cutting-plane algorithm to solve integer linear programming problems. Experiment with different cutting plane generation strategies.
Experiment with different branching strategies and node selection rules. Implement the branch-and-bound algorithm to solve integer linear programming problems.
Implement gradient descent, Newton's method, and quasi-Newton methods to solve unconstrained optimization problems.
Implement penalty methods, barrier methods, and Lagrange multiplier methods to solve constrained optimization problems. Experiment with different penalty parameters and barrier functions.
Implement a genetic algorithm and particle swarm optimization algorithm to solve optimization problems.

References:

Christos H. Papadimitriou, Combinatorial Optimization: Algorithms and Complexity, Dover Publications, 1998.
Donald L. Kreher and William Lawrence Kocay, Graphs, Algorithms, and Optimization, Chapman and Hall/CRC, 2014.
Rajesh Kumar Aurora, Optimization Algorithms and Applications, Cambridge University Press, 2010.

MICT-2012: Satellite & Radar Communications

Credit Hour: 3.0

Course Objectives:

To learn about the basic principles, components (earth and space segments), and subsystems that enable satellite communication.
To gain insights into satellite link analysis, link budget, and design considerations for satellite communication systems, including VSAT and mobile satellite networks.
To study the applications of satellite communication, including satellite internet, digital broadcast TV, and satellite navigation systems (e.g., GPS, INMARSAT).
To learn the fundamental concepts of radar, including radar bands, subsystems, and key components like transmitters and receivers.
To study the radar equation, radar cross section, and the impact of noise, clutter, and distributed targets on radar performance.
To gain knowledge of advanced radar systems, including Doppler radar, Moving Target Indication (MTI), and Synthetic Aperture Radar (SAR) for enhanced detection and imaging.

Course Outcomes:

Upon the completion of this course, students will be able to:

Describe the roles of antennas, transponders, and satellite orbits in the satellite communica.tion process
Perform satellite link analysis and calculate link budgets for efficient satellite communication system design.
Explain the practical uses of satellite systems in areas like GPS navigation, mobile satellite communication, and digital TV broadcasting.
To explain the operation of radar systems and their subsystems, including how radar bands are utilized for different applications.
Use the radar equation and analyze factors like radar cross section, noise, and clutter to assess radar detection capabilities.
Gain an understanding of advanced radar techniques, such as Doppler and SAR, and how they are used in modern applications like target tracking and high-resolution imaging.

Course Content:

Introduction to satellite communication, Satellite components: earth segment and space segment, antennas, Satellite subsystems, Satellite frequency bands, satellite orbits, satellite types, satellite earth station, transponders, satellite link analysis, link design and link budget, satellite networks, satellite internet, multiple access techniques for satellite communication, VSAT technologies, VSAT network configurations, Mobile satellite system: IRID/VM, INMARSAT etc., Digital broadcast satellite TV, satellite navigation and GPS.
Introduction to radar, radar bands, radar subsystems and components, radar equation, radar cross section, distributed targets, information contents in radar signals, noise and clutter, detection and tracking, Doppler and MTI radar, radar transmitter and receivers, Synthetic aperture radar.

Laboratory and Case Study:

One/two-day visit to satellite earth station and students will submit report individually based on the visit.
Design of (or introducing to) Satellite (space segment) and explore the operation of all components including transponder.
Detection, identification, and classification of objects/targets using different radar systems.
Detection of fixed targets and moving targets using parabolic/patch antenna.

References:

Timothy Pratt, Charles W. Bostian, and Jeremy E. Allnutt, Satellite Communications, 2^nd Edition, John Wiley & Sons, 2003.
Gerard Maral and Michel Bousquet, Satellite Communications Systems: Systems, Techniques and Technology, 5^th Edition, John Wiley & Sons, 2009.
Merrill I. Skolnik, Introduction to Radar Systems, 3^rd Edition, McGraw-Hill Education, 2001.
Bassem R. Mahafza, Radar Systems Analysis and Design Using MATLAB, 3^rd Edition, Chapman and Hall/CRC, 2013.
Mark A. Richards, Fundamentals of Radar Signal Processing, 2^nd Edition, McGraw-Hill Education, 2014.

MICT-2013: ICT Policy & Standards

Credit Hour: 3.0

Course Objectives:

To understand the foundational concepts of ICT policy and regulation.
To examine the structure and functions of regulatory frameworks in ICT.
To explore the importance of ICT standards and the role of standardization bodies.
To analyze spectrum policy and its significance for emerging ICT technologies.
To assess ICT policy approaches for digital inclusion and bridging the digital divide.
To investigate privacy, data protection, and security standards in ICT policy.

Course Outcomes:

Upon the completion of this course, students will be able to:

Define ICT policy, explain its scope, and articulate its historical evolution.
Understand the importance of global and regional ICT policy frameworks such as ITU, OECD, and WTO, and their role in economic and social development.
Gain an understanding of the role of key regulatory bodies like the ITU and national regulatory authorities.
Identify key standardization bodies (ITU, IEEE, IETF, etc.) and explain the process of ICT standards development and enforcement.
Understand of the fundamentals of spectrum management, including frequency allocation and spectrum licensing and explore the policy considerations for emerging technologies like 5G and IoT.
Evaluate ICT policies aimed at promoting digital inclusion and bridging the digital divide, including policies for rural connectivity, gender inclusivity, and accessibility for marginalized groups.
Gain insights into global data protection frameworks such as GDPR and CCPA, and the role of ICT security standards like ISO/IEC 27001 and NIST.
Predict future trends and challenges in ICT policy and standardization.

Course Content:

Introduction to ICT Policy and Regulation: Overview of ICT Policy: Definitions, Scope, and Importance, Historical Evolution of ICT Policy and Regulatory Frameworks, Global and Regional ICT Policy Frameworks (ITU, OECD, WTO), The Role of ICT in Economic Development and Social Transformation, Key Stakeholders: Governments, Industry, Civil Society, and International Organizations.
Regulatory Frameworks for ICT: International Telecommunication Union (ITU) and Its Role in ICT Regulation, National Regulatory Frameworks: The Role of Telecom Regulatory Authorities, ICT Regulations: Licensing, Spectrum Management, Infrastructure Sharing, Convergence of Telecom, Media, and ICT Regulations, Role of National Legislation: Telecommunications Acts, Data Protection Laws, and Competition Laws.
ICT Standards Development and Standardization Bodies: Importance of Standards in ICT: Interoperability, Innovation, and Global Trade, Key Standardization Bodies: ITU, IEEE, IETF, ISO, 3GPP, ETSI, W3C, Standardization Processes: Development, Adoption, and Enforcement of Standards, Examples of ICT Standards: GSM, 3G, 4G, 5G, Wi-Fi, Ethernet, IPv6, Open Standards vs. Proprietary Standards: Pros and Cons.
Spectrum Policy and Management: Basics of Spectrum: Frequency Allocation and Its Importance for ICT, International Spectrum Management: Role of ITU and World Radiocommunication Conferences (WRC), National Spectrum Management: Spectrum Licensing, Auctions, and Dynamic Spectrum Sharing, Spectrum Policy for Emerging Technologies: 5G, IoT, and Future Networks, Case Studies in Spectrum Allocation: Examples from Developed and Developing Countries.
ICT Policy and Digital Inclusion: The Digital Divide: Defining and Measuring Digital Exclusion, ICT Policy Approaches to Bridging the Digital Divide, Universal Access Policies and Universal Service Funds (USF), Rural Connectivity: Public-Private Partnerships and Infrastructure Development, Gender, Disability, and Marginalized Groups in ICT Policy: Promoting Inclusive Digital Access.
Privacy, Data Protection, and ICT Security Standards: Data Protection Frameworks: GDPR (Europe), CCPA (California), and Global Privacy Standards, ICT and Cybersecurity Policy: Regulatory Approaches to Cybersecurity and National Security, ICT Security Standards: ISO/IEC 27001, NIST Cybersecurity Framework, PCI DSS, Encryption, Authentication, and Data Sovereignty in ICT Policy, Case Studies: Data Breaches, Cyber Attacks, and Responses from Governments.
Intellectual Property Rights (IPR) in ICT: Overview of Intellectual Property (IP) Laws and Their Relevance to ICT, Patents, Copyright, Trademarks, and Trade Secrets in the ICT Sector, IPR Challenges in Software Development and ICT Standardization, Open-Source Software and Licensing: Opportunities and Challenges, Global IP Treaties: TRIPS Agreement (WTO), WIPO, and Their Role in ICT.
Competition Policy in the ICT Sector: Overview of Competition Policy: Objectives and Tools (Antitrust, Market Regulation), Market Dominance and Anti-Competitive Practices in the ICT and Telecom Sectors, Mergers and Acquisitions in ICT: Regulatory Considerations, Net Neutrality: Policy Debates and Regulatory Responses, Case Studies: ICT Competition Policy in the U.S., EU, and Developing Countries.
Internet Governance and ICT Policy: The Role of ICANN and IANA in Internet Governance, The Multi-Stakeholder Model of Internet Governance, Policy Issues in Domain Name System (DNS) Management and IP Addressing, Content Regulation, Censorship, and Freedom of Expression Online, Internet Policy Challenges: Cross-Border Data Flows, Content Moderation, and Privacy.
Policy for Emerging ICT Technologies: Policy Frameworks for 5G Deployment: Spectrum Allocation, Network Slicing, and Latency Requirements, Internet of Things (IoT): Regulatory Challenges for M2M Communications, Artificial Intelligence (AI) in ICT: Ethical and Policy Considerations, Blockchain and Cryptocurrencies: Regulatory Challenges and Opportunities, ICT and Smart Cities: Policy Frameworks for Connected Infrastructure.
ICT Policy for Sustainable Development: ICT and the UN Sustainable Development Goals (SDGs), Green ICT Policies: Energy Efficiency and Reducing Carbon Footprint in ICT Infrastructure, ICT for Disaster Management and Crisis Response: Policy Approaches and International Cooperation, E-Government, E-Education, E-Health: Policies for Digital Transformation in Public Services, The Role of Telecom in Socioeconomic Development: Case Studies from Developing Nations.
ICT Policy Case Studies and Regulatory Analysis: Comparative Analysis of National ICT Policies (U.S., EU, India, China, etc.), Policy Challenges in Broadband Deployment and Regulation, Impact of ICT Policy on Digital Services: OTT (Over-the-Top) Media, Cloud Computing, and VoIP, Regulatory Frameworks for Cross-Border Data Transfers and Privacy Protection, The Role of ICT Policy in Crisis Situations (e.g., COVID-19): Digital Infrastructure and Connectivity.
Future Trends in ICT Policy and Standards: 6G and Beyond: Policy Implications for Future Communication Networks, Quantum Computing and ICT Policy: New Frontiers in Data Processing and Security, Space-Based Communication Networks: Policy Challenges for Satellite Internet and IoT, AI Regulation in ICT: Navigating Ethical, Legal, and Security Concerns, Policy Responses to ICT Disruption: Managing Technological Change and Social Impact.

Laboratory and Case Study:

Case study on net neutrality policies in the U.S. vs. EU.
Case study on spectrum allocation for 5G networks.
Case study on GDPR and Its global impact.
Case study on internet governance – The role of ICANN and multi-stakeholder models.
Analyze the ICT regulatory framework of Bangladesh.
Proposal for revising national ICT policy of Bangladesh.
Analyze data privacy laws in different countries and compare with Bangladesh.

References:

Stuart Minor Benjamin, Howard Shelanski, James B. Speta, Philip J. Weiser, Telecommunications Law and Policy, 5^th Edition, Carolina Academic Press, 2019.
William H. Dutton, Mark Graham, and Victoria Nash, The Oxford Handbook of Internet Governance, 1^st Edition, Oxford University Press, 2014.
Heather E. Hudson, Global Communications: Opportunities for Trade and Aid, 1^st Edition, Indiana University Press, 1997.
ICT Regulation Toolkit, World Bank and International Telecommunication Union (ITU), Online Resource (Continuously Updated).
Robert Hall and Harry Laros, ICT Regulation: Transforming Public-Private Ecosystem, 1^st Edition, CRC Press, 2018.
Ian J. Lloyd, Information Technology Law, 8^th Edition, Oxford University Press, 2020.
Eric Brousseau, Meryem Marzouki, and Cécile Méadel, Governance, Regulation, and Powers on the Internet, 1^st Edition, Cambridge University Press, 2012.

Alan J. Marcus and Mark J. McHenry, The Politics of Spectrum Management: Policy, Technology, and Reform, 1^st Edition, Cambridge University Press, 2013.

MICT-2014: Information Theory & Coding

Credit Hour: 3.0

Course Objectives:

To understand the fundamental principles of information theory from both intuitive and mathematical perspectives.
To learn the concepts of entropy, information rate, and channel capacity, and how they relate to data transmission and compression.
To implement and analyze various source and channel coding algorithms.
To explore error control coding techniques, including linear block codes, convolutional codes, and Reed-Solomon codes.
To gain knowledge of multimedia compression techniques, such as MP3, JPEG, MPEG, and wavelet-based compression.
To implement key algorithms in MATLAB, including source encoding, channel encoding, and decoding techniques.

Course Outcomes:

Upon the completion of this course students will be able to:

Demonstrate an understanding of the core principles of information theory, including the concepts of entropy, mutual information, and data redundancy, from both theoretical and practical perspectives.
Apply the concepts of entropy, information rate, and channel capacity to analyze real-world communication systems, understanding how these metrics influence data transmission efficiency and compression.
Implement and evaluate source and channel coding algorithms such as Huffman coding and Turbo codes, analyzing their performance in terms of compression efficiency and error correction capabilities.
Design and implement error control coding techniques, including linear block codes, convolutional codes, and Reed-Solomon codes, to improve the reliability of data transmission over noisy communication channels.
Analyze and apply multimedia compression algorithms (e.g., MP3, JPEG, MPEG, and wavelet-based methods) for efficient data storage and transmission, understanding their trade-offs in terms of compression ratios and quality.
Develop and test key algorithms in MATLAB for source encoding, channel encoding, and decoding, with a focus on improving both the accuracy and efficiency of these techniques in real-world applications.

Course Content:

Information conveying system, information theory from intuitive and engineering point of view, entropy, information rate, source coding theorem.
Discrete memoryless channel, channel capacity, information capacity theorem, rate distortion theory, source coding-Shannon Fano algorithm, Huffman coding, Lampel-Ziv coding, Run-length encoding, music.
Image and video compression like MP3 JPEG, MPEG, wavelet based image compression.
Introduction to error control coding, linear block coding, RS code, CRC code, convolution coding, state and Trellis diagram.
Multistage coding technique, Sequential and Veterbi decoding, system application example, Cryptography and Coding theory, Applications of Cryptography in Secure Communication.
MATLAB code on source encoding, channel coding and multimedia compression.

Laboratory and Case Study:

Calculate entropy and mutual information for given data sets.
Simulate basic data compression methods, such as Huffman Coding, using a coding platform in MATLAB or Python.
Analyze and compress images using basic JPEG coding.
Implement Hamming and Reed-Solomon codes for a noisy channel in MATLAB or similar computing tool.
Simulate error detection and correction using MATLAB or Python.
Calculate and analyze channel capacity for BSC and BEC in MATLAB.
Implement Lempel-Ziv algorithms for a text data stream in MATLAB.
Simulation with audio or image compression using transform coding methods.

Required Tools and Software:

MATLAB, Python (NumPy, SciPy), or a similar computing tool.
Libraries: SciPy and NumPy for Python, or specialized libraries for encoding and decoding (e.g., PyLDPC for LDPC codes).

References:

Thomas M. Cover and Joy A. Thomas, Elements of Information Theory, 2^nd edition, Wiley-Interscience, 2006.
David J.C. MacKay, Information Theory, Inference, and Learning Algorithms, 1^st edition, Cambridge University Press, 2003.
Khalid Sayood, Introduction to Data Compression, 5^th edition, Morgan Kaufmann, 2017.
Shu Lin and Daniel J. Costello, Error Control Coding, 2^nd edition, Pearson, 2004.

MICT-2015: Ethical Hacking & Intrusion Management

Credit Hour: 3

Course Objectives:

To apply a common ethical hacking methodology to carry out a penetration test
To analyze the relationships and dependencies between various penetration testing tools within a comprehensive assessment process.
To discuss how the tools interrelate with each other in an overall penetration testing process.
To implement countermeasures for various types of attacks.
To analyze how penetration testing, and ethical hacking fit into a comprehensive enterprise information security program; and demonstrate ethical behavior appropriate to security-related technologies.

Course Outcomes:

Upon completing the course, the students will be able to:

Have a solid understanding of the fundamental principles, methodologies, and objectives of penetration testing.
Learn about common ethical hacking frameworks and methodologies (e.g., OSINT, reconnaissance, scanning, enumeration, exploitation).
Effectively use a variety of penetration testing tools and techniques.
Identify and address security vulnerabilities in systems and networks.
Plan, execute, and report on penetration tests.
Analyze security risks and make informed recommendations.
Develop a strong sense of ethical responsibility and adhere to professional standards in their penetration testing activities.

Course Content:

Introduction to Ethical Hacking Concepts: Types, and Phases, What is Hacking, Why Ethical Hacking is Necessary, Scope and Limitations of Ethical Hacking, Information Security Controls, Information Assurance (IA), Information Security Management Program, Threat Modeling, Enterprise Information Security Architecture (EISA), Network Security Zoning, Defense in Depth- Information- Security-Policies, Types of Security Policies, What is Vulnerability Assessment?, Types of Vulnerability Assessment, Network Vulnerability Assessment Methodology, Vulnerability Research Websites, Penetration Testing, Comparing Security Audit, Vulnerability Assessment, and Penetration Testing, Blue Teaming/Red Teaming, Hacking Phases, Scan for Vulnerability, Vulnerability Scanning, Vulnerability Scanning Tool, Nessus, Network Vulnerability Scanners, Vulnerability Scanning Tools for Mobile, Draw Network Diagrams, Drawing Network Diagrams, Network Discovery Tool, Network Topology Mapper and Network View, Network Discovery Tools for Mobile, Gaining Access, Maintaining Access, Clearing Tracks, Information at Hand Before System Hacking Stage.
Intrusion Detection & Penetration Testing: Intrusion management tools, Penetration Testing / Hacking Methodology, Steps in Penetration Testing, Cracking Passwords, Password Cracking, Types of Password Attacks, Non-Electronic Attacks, Active Online Attack, Dictionary, Brute Forcing and Rule-based Attack, Password Guessing, Default Passwords, Active Online Attack, Trojan/Spyware/Keylogger, Example of Active Online Attack Using USB Drive, Hash Injection Attack, Passive Online Attack, Wire Sniffing, Man-in-the-Middle and Replay Attack, Offline Attack, Rainbow Attacks, Tools to Create Rainbow Tables: rtgen and Winrtgen, Distributed Network Attack. Active Directory Penetration Testing, Denial of Service: Introduction, Attacks, Preventing DoS/DDoS; Buffer Overflow: Introduction, Testing vulnerability, Attacks, Countermeasures. Web Application Penetration Testing.

Laboratory and Case Study:

Labs on Reconnaissance using different OSINT Tools i.e: google dork, maltego etc.
Labs on Scanning Network, Systems, Application, Database using different scanning Tools i.e: Nmap. GFI Langurd, Nessus, Nexpose etc.
Labs on Enumeration using different Tools.
Vulnerability Assessment using different Tools i.e: Nmap. GFI Langurd, Nessus, Nexpose etc.
System hacking using different PT tools i.e: Nmap. Metasploit, Burpsuite, core impact, saint etc.
Privilege Escalation PT using different PT tools i.e: Nmap. Metasploit, Burpsuite, core impact, saint etc.
Script writing and Analysis.
Course Final Project Assignment on systems and Infrastructure VAPT.

References:

Georgia Weidman, Penetration Testing: A Hands-On Introduction to Hacking, No Starch Press, 2014.
Wolf Halton, ‎Bo Weaver, ‎Juned Ahmed Ansari, Penetration Testing: A Survival Guide, Wiley, 2018.
Lee Allen, ‎Kevin Cardwell, Advanced Penetration Testing for Highly-Secured Environments, Wiley, 2021.
EC-Council, Certified Ethical Hacker Version 9 Study Guide, First Edition, Wiley, 2018.

MICT-2016: Industrial Automation & Control

Credit Hour: 3.0

Course Objectives:

To learn the fundamental principles behind advanced control strategies such as state-space representation, nonlinear control, and adaptive control.
To explore the application of artificial intelligence and machine learning techniques in automation, including predictive maintenance and process optimization.
To acquire advanced knowledge in robot kinematics, dynamics, and path planning.
To understand advanced PLC programming techniques and integrate PLCs with other control systems and embedded controllers.
To conduct reliability analyses and develop strategies for maintaining and improving the reliability of automation systems.
To understand ethical considerations and professional industrial automation and control standards.

Course Outcomes:

Upon the completion of this course, students will be able to:

Demonstrate a thorough understanding of advanced control theories, including state-space representation, nonlinear control, adaptive control, and model predictive control (MPC).
Apply artificial intelligence and machine learning techniques to improve automation processes, including predictive maintenance and process optimization.
Demonstrate advanced PLC programming skills and integrate PLCs with other control systems, data acquisition, real-time control and embedded controllers.
Demonstrate the ability to program and integrate industrial robots, including collaborative robots (cobots) for various applications.
Design and implement advanced robot kinematics, dynamics, and path planning algorithms.
Perform reliability analysis and develop strategies for maintaining and improving system reliability.
Navigate ethical considerations and adhere to professional standards in industrial automation.

Course content:

Introduction to Industrial Automation: History and Evolution, Early automation, Modern advancements, Current Trends, Industry 4.0, Smart Manufacturing, Applications and Benefits.
Control Systems Fundamentals: Types of Control Systems, Open-loop vs. closed-loop control, Discrete vs. continuous control, Control Theory Basics, Feedback and feedforward control. Stability and performance metrics
Advanced Control Strategies: PID Control, Tuning methods, Adaptive PID, State-Space Representation, State-space models and their applications, Observability and controllability, Model Predictive Control (MPC), Optimal Control, Robust Control, Nonlinear Control, Lyapunov stability, Feedback linearization.
Programmable Logic Controllers (PLCs): PLC Architecture and Operation, PLC Programming Languages, PLC Networking and Communication, PLC-Based System Design-Integration with SCADA and MES systems, Real-time control and data acquisition, PLC and Embedded Systems, Combining PLCs with embedded controllers.
Intelligent Control Systems: Artificial Intelligence in Automation, Machine learning for predictive maintenance, Neural networks for process control, Fuzzy Logic Control.
Industrial Robotics and Automation: Advanced Robot Kinematics and Dynamics, Inverse kinematics and dynamics, Trajectory planning, Robot Path Planning and Motion Control, Algorithms for path planning, Motion control techniques, Collaborative Robots (Cobots). Integration with Control Systems, Process Control and Optimization.
Project Management and Industry Practices: Project Lifecycle Management, Planning, execution, and control, Cost Management and Budgeting, Estimating and controlling project costs, Ethics and Professional Responsibilities, Ethical issues in automation, Professional standards and practices.

Laboratory and Case Study:

Design controllers (e.g., PID, adaptive, or robust controllers) using MATLAB tools.
Implement discrete control systems using MATLAB and Simulink, focusing on PLC simulation.
Simulate a SCADA (Supervisory Control and Data Acquisition) system to monitor and control industrial processes.
Model and control a robotic arm, using MATLAB for kinematics and dynamics analysis.
Implement control strategies for the modeled system and evaluate their performance.
Design and implementation of a complete automation system for a simulated industrial process.
Analysis of automation projects in various industries.
Case study on industrial robotics and automation in an automotive assembly line.
Field visits on observing automation in action at industrial sites (if applicable).

References:

Ogata Katsuhiko, Modern Control Engineering, 5th Edition (2010), ISBN: 978-0136156734.
Gene Franklin, J. Da Powell, and Michael Workman, Digital Control of Dynamic Systems, 4th Edition (2015), ISBN: 978-0133496591.
Benjamin Kuo and Farid Golnaraghi, Automatic Control Systems, 9th Edition (2017), ISBN: 978-1118324561.
B. Wayne Bequette, Process Control: Modeling, Design, and Simulation, 3rd Edition (2022), ISBN: 978-0136717210.
Da-Wei Gu, Petros A. Ioannou, and Feng Lin, Control System Design with MATLAB, 1st Edition (2003), ISBN: 978-0131016035.
Bruno Siciliano and Lorenzo Sciavicco, Robotics: Modelling, Planning and Control, 1st Edition (2009), ISBN: 978-1846286414
John J. Craig, Introduction to Robotics: Mechanics and Control, 3rd Edition (2004), ISBN: 978-0201543612.
Andrew G. Schmidt, MATLAB Robotics: A Practical Guide for Robot Simulation and Design, 1st Edition (2021), ISBN: 978-0367335087.
Eric W. Johnson, Simulink for Robotics: A Guide to Using Simulink in Robotics Research and Development, 1st Edition (2018), ISBN: 978-1788835050.
Frank Lamb, Industrial Automation: Hands-On, 1st Edition (2015) ISBN: 978-0128022273.

MICT-2017: ICT Project Management

Credit Hour: 3.0

Course Objectives:

To provide a comprehensive understanding of the fundamental principles and practices of project management, specifically tailored to ICT projects.
To provides an understanding of the purpose, methods, and benefits of schedule management, process management, scope management, and cost management by exposing the student to the concepts, practices, processes, tools, and techniques.
To develop the ability to apply various project management methodologies and tools to address complex ICT challenges.
To develop a comprehensive understanding of quality management and assurance principles, methodologies, and strategies, with a focus on key industry standards.
To explore the emerging trends in project management, including the role of AI and automation in optimizing project delivery.

Course Outcomes:

Upon the completion of this course, students will be able to:

Efficiently select projects based on defined method.
Perform critical analysis and design a project.
Schedule and control a project including crashing and leveling.
Optimize resource utilization and management.
Apply risk management principles.
Manage and control cost.
To understand how AI and automation can optimize project management tasks.

Course Content:

Introduction to project management. Basics of project management, triple constant, program and portfolio management, project life cycle.
Designing, evaluation and selection of a project. Business case, theory of change, feasibility studies, project charter, various methods of evaluation and selection of project.
Scope management. Planning scope management, requirement collection, defining scope, CRS, SRS, WBS, validation and control of scope; Basics of software estimation, effort estimation techniques, COSMIC Full function points; software process and process models, choice of process models and mental delivery, rapid application development, Agile methods, extreme programming, SCRUM, managing interactive processes, Agile estimation.
Schedule management. Activities, network (AoA, AoN), critical path, slack, PERT/CPM, probability using z-table, scheduling and Gantt chart, crashing a project, KANBAN.
Resource management. Resource loading, resource leveling, RAM, RACI, resource histogram, Staffing Pattern.
Cost management. Cost-benefit evaluation technology, cost estimation, budgeting and controlling cost, EMV (Earned Value Management), CPI/SPI/S-Curve
Risk management. identify risk, risk evaluation, risk response plan, ERM, strategic risk management.
Release and Change management. Change request, change evaluation, change approval, change implementation, change review, types of changes; release planning, release build, release deployment, release review, release types.
Quality management. Quality assurance and quality control, quality factors; Components of Quality Assurance, Test Plan, Pre-project components. Maintenance and external participants; Defect removal effectiveness, Different kinds of Testing; quality metrics, Cost of quality, Cause-effect diagram, quality control chart, 7-run rule, check sheet, pareto chart, flow chart, six sigma.
AI and Automation in Project Management: How AI and automation can optimize project management tasks, such as risk analysis, resource allocation, and performance; hybrid project management approaches, combining traditional and agile methodologies to adapt to different project needs, usages of ChatGPT/PMI Infinity.

Laboratory and Case Study:

Lecture-4 (Lab Classes on Microsoft Project for Schedule management).
Lecture-8 (Lab Classes Jira, Github).
Lecture-7 (Case Study on Risk Framework).
Lecture-9 (Lab Classes Labs on postman & Selenium).

References:

Jack R. Meredith & Samuel J. Mantel, Project Management – A Managerial Approach, 8th edition, Wiley, 2020.
Kathy Schwalbe, Information Technology Project Management, 9th edition, Cengage Learning, 2021.
James Cadle & Donald Yeates, Project Management for Information Systems, 4th edition, Prentice Hall, 2003.
Mark Tolbert and Susan Parente, Hybrid Project Management: Using Agile with Traditional PM Methodologies to Succeed on Modern Projects, Wiley, 2018.
Peter Taylor, AI and the Project Manager: How the Rise of Artificial Intelligence Will Change Your World, Wiley, 2021.
Project Management Institute (PMI), A Guide to Project Management Body of Knowledge (PMBOK® Guide), 7th edition, 2021.
Ken Schwaber & Jeff Sutherland, The SCRUM Guide- the definitive guide to SCRUM: The rules of Game, Scrum Guides, 2020.

MICT-2019: Advancement in Microprocessor Systems

Credit Hour: 3.0

Course Objectives:

To equip students with a comprehensive understanding of ARM microprocessor architecture, including RISC/CISC philosophies, ARM processor families, and development history.
To gain proficiency in ARM assembly language programming, covering essential instruction sets, data processing, branching, and memory access techniques.
To guide students in using C programming for ARM-based applications, focusing on optimization, data structures, peripheral interfacing, and efficient memory management.
To provide hands-on experience in developing and troubleshooting ARM-based embedded applications, such as timers, PWM, ADC, DAC, UART, and communication interfaces (I2C, SPI).
To introduce students to advanced ARM topics, including memory management units, virtual memory, exception handling, and ARM optimization techniques for high-performance applications.

Course Outcomes:

Upon the completion of this course, students will be able to:

Demonstrate knowledge of ARM design philosophy, processor architecture, and data flow models, with an ability to distinguish ARM from other microprocessor architectures.
Analyze, and debug ARM assembly programs, efficiently using ARM instruction sets and assembly programming techniques.
Develop and optimize C programs for ARM-based systems, utilizing ARM’s core registers, memory structures, and embedded system peripherals.
Design and implement ARM-based interfaces for real-time applications, handling I/O operations, communication protocols, and timing functions effectively.
Gain an understanding of memory management units, multitasking, and caching techniques within ARM architecture, applying this knowledge to optimize embedded applications.

Course Content:

Introduction: Need of advance microprocessors, Difference between RISC and CISC, RISC Design philosophy, ARM Design Philosophy, History of ARM microprocessor, ARM processor family, Development of ARM architecture.
The ARM Architecture and Programmers Model: The Acorn RISC Machine, ARM Core data flow model, Architectural inheritance, The ARM7TDMI programmer’s model: General purpose registers, CPSR, SPSR, ARM memory map, data format, load and store architecture, Core extensions, Architecture revisions, ARM development tools.
ARM Instruction set: Data processing instructions, Arithmetic and logical instructions, Rotate and barrel shifter, Branch instructions, Load and store instructions, Software interrupt instructions, Program status register instructions, Conditional execution, Multiple register load and store instructions, Stack instructions, Thumb instruction set, advantage of thumb instructions, Assembler rules and directives, Assembly language programs for shifting of data, factorial calculation, swapping register contents, moving values between integer and floating point registers.
Programming for ARM: Overview of C compiler and optimization, Basic C data types, C Looping structures, Register allocations, function calls pointer aliasing, structure arrangement, bitfields, unaligned data and Endianness, Division, floating point, Inline functions and inline assembly, Portability issues. C programs for General purpose I/O, general purpose timer, PWM Modulator, UART, I2C Interface, SPI Interface, ADC, DAC.
Memory management units: Moving from memory protection unit (MPU) to memory management unit (MMU), Working of virtual memory, Multitasking, Memory organization in virtual memory system, Page tables, Translation look aside buffer, Caches and write buffer, Fast context switch extension.
Advanced Topics: Advanced Microprocessor Bus Architecture (AMBA) Bus System, User peripherals, Exception handling in ARM, ARM optimization techniques.

Laboratory and Case Study:

Write assembly programs using ARMv7 ISA to manipulate strings (e.g., reversing, concatenation, searching) and setup interrupt handler.
Write an assembly program using ARMv7 ISA to interface with simple IO. For example, write a program that will calculate the area and perimeter of a rectangle and print in the 7-segment display. Take integer inputs for both sides of the rectangle.
Display “Hello” and “World” separately in the seven-segment display. When the passcode 0101 is pressed in the push button KEY [3..0], the word will be replaced with the other one such as “Hello” will be replaced with “World”.
Program GPIO registers to perform simple digital I/O input (interfacing push button) and output (interfacing LED).
Program GPIO registers to perform an Interrupt. For example, implement a timer that counts (e.g. 0-F) with an Interrupt button. When the Interrupt button is pressed, the timer is reset to 0 and starts counting.
Implement a four-bit counter with external switches that will display a hex number (e.g. 0-F) based on four-bit binary inputs.
Program RTC to generate periodic alarm interrupts to toggle an LED and activate a buzzer.
Case study on security vulnerabilities in ARM systems and implement security measures to protect against attacks.
Case study on analyzing the performance of an ARM-based system and identify bottlenecks. Implement optimization techniques to improve performance.

References:

Steve Furber, ARM System-on-Chip Architecture, 2^nd Edition, Addison-Wesley Professional, 2000.
Joseph Yiu, The Definitive Guide to ARM Cortex-M3 and Cortex-M4 Processors, 3^rd Edition, Newnes (an imprint of Elsevier), 2013.
ARM Assembly Language: Fundamentals and Techniques, William Hohl and Christopher Hinds, 2^nd Edition, CRC Press, 2014.
Jonathan W. Valvano, Embedded Systems: Real-Time Interfacing to ARM Cortex-M Microcontrollers, Edition: 2^nd Edition, CreateSpace Independent Publishing, 2016.

MICT-2021: Big Data Analytics

Credit Hour: 3.0

Course Objectives:

To obtain an overview of Big Data & Hadoop including HDFS and YARN (Yet Another Resource Negotiator).
To gain comprehensive knowledge of various tools that fall in the Spark ecosystem.
To understand how to ingest data in HDFS using Sqoop & Flume.
To program Spark using Pyspark, and identify the computational trade-offs in a Spark application.
To model data through statistical and machine learning methods.
To use the power of handling real-time data feeds through a publish-subscribe messaging system like Kafka.
To gain exposure to many real-life industry-based projects, like banking, telecommunication, social media, and in the government field.

Course Outcomes:

Upon completing the course, the students will be able to:

Apply data wrangling, cleaning, and preprocessing techniques to manage large datasets.
Demonstrate proficiency in big data frameworks (Hadoop, Spark) and NoSQL databases (Cassandra, MongoDB) for storing and processing large volumes of data.
Implement security measures such as encryption, access control, and anonymization to protect big data systems.
Understand and address ethical issues, including privacy concerns and algorithmic biases, in the context of big data analytics.
Demonstrate the ability to tackle real-world big data problems by designing a comprehensive solution.

Course Content:

Introduction to Big Data Processing: What is Big Data? What is Hadoop? How Hadoop Solves the Big Data Problem? Hadoop’s Key Characteristics; Hadoop Ecosystem and HDFS; MapReduce and its Advantage; Rack Awareness and Block Replication; YARN and its Advantage; Hadoop Cluster and its Architecture; What is Spark? Why Spark is needed? How Spark differs from other frameworks?
Large-Scale Data Processing With PySpark: Spark - RDDs, DataFrames, Spark SQL; PySpark + NumPy + SciPy, Code Optimization, Cluster Configurations; Linear Algebra Computation in Large Scale; Distributed File Storage Systems.
Data Modeling and Optimization Problems: Introduction to modeling: numerical vs. probabilistic vs. Bayesian; Introduction to Optimization Problems; Batch and stochastic Gradient Descent; Newton’s Method; Expectation-Maximization, Markov Chain Monte Carlo (MCMC).
Large-Scale Supervised Learning: Introduction to Supervised learning; Generalized Linear Models and Logistic Regression; Regularization; Support Vector Machine (SVM) and the kernel trick; Outlier Detection; Spark ML library.
Large-Scale Unsupervised Learning: Introduction to Unsupervised learning; K-means / K-medoids; Gaussian Mixture Models; Dimensionality Reduction; Spark MLlib for Unsupervised Learning.
Large Scale Text Mining: Latent Semantic Indexing; Topic models; Latent Dirichlet Allocation; Spark ML library for NLP.
Understanding Apache Kafka and Apache Flume: Basic Flume Architecture; Flume Sources; Flume Sinks; Flume Channels; Flume Configuration; Core Concepts of Kafka; Kafka Architecture; Understanding the Components of Kafka Cluster; Configuring Kafka Cluster; Integrating Apache Flume and Apache Kafka.
Apache Spark Streaming: Why Streaming is Necessary? Drawbacks in Existing Computing Methods; What is Spark Streaming? Spark Streaming Features; Spark Streaming Workflow; Streaming Context & Dstreams; Transformations on Dstreams; Slice, Window and ReduceByWindow Operators; Stateful Operators.
Spark GraphX: Key concepts of Spark GraphX; GraphX algorithms and their implementations.

Laboratory and Case Study:

Explore techniques for data extraction from various sources. Use tools like Apache Flume or Apache Sqoop to ingest data into the big data platform.
Integrate big data with traditional relational databases. Explore methods for connecting and querying data across different storage systems.
Implement storage solutions for big data using NoSQL databases. Create key-value, graph, document, and column-family data models.
Set up a Hadoop cluster and explore HDFS. Upload, download, and manipulate data within the distributed file system.
Execute Hadoop MapReduce jobs on a cluster. Monitor and analyze the progress of job flows using Hadoop tools.
Run a Big Data Processing pipeline on Google Cloud (or Amazon AWS).
Implement Big Data code in Apache Spark (in PySpark).
Run Supervised and Unsupervised machine learning on Large-Scale Data.
Flume Commands and Setting up Flume Agent.
Case study on Big Data in i) Healthcare-Predictive analytics for patient care, genomics, and epidemiology; or ii) Finance-Fraud detection, risk analysis, and high-frequency trading; or iii) Retail and Marketing-Customer segmentation, personalization, and recommendation engines.

References:

Balamarugan Balusamy, Nandhini Abirami R, Seifedine Kadry and Amir Gandomi, Big Data: Concepts, Technology and Architecture, Wiley, 2017.
Bill Chambers and Matei Zaharia, Spark: The Definitive Guide: Big Data Processing Made Simple, O'Reilly, 2016.
Ramcharan, K., Sundar, K., Alla, S, Applied data science using PySpark: Learn the end-to-end predictive model-building cycle, Apress, 2020.
Han, J., Kamber, M., Pei, J., Data mining: Concepts and techniques, Morgan Kaufmann, 2011.
Michael Minelli, Big Data, Big Analytics: Emerging Business Intelligence and Analytics Trends for Today’s Businesses, Wiley, 2013.

General Info

Intake: Once in a Year
Application Duration: 25 October - 10 December2024
Written Test and Viva Voce: 27 December 2024 (1100 hrs -1200 hrs)
Class Start: 24 January 2025
Method of Application: Online
Course Duration: 2 (two) years, 4 (four) semesters
Total Credit Hours: M. Sc. Engineering (Theory: 22 Cr. + Thesis: 18 Cr.) & M. Engineering (Theory: 34 Cr. + Project: 6 Cr.)
Total Course Fee : M. Sc. Engineering - TK. 1,95,000.00 & M. Engineering - TK. 1,80,000.00 which may be re-fixed by the authority.

Eligibility for Admission

(1) A minimum GPA of 3.50 out of 5.00 or a first division or equivalent in any one of SSC and HSC or in equivalent examinations

(2) Must not have a GPA less than 2.50 out of 5.00 or a third division or equivalent in any of SSC and HSC or in equivalent examinations

(3) At least 50% marks or a minimum GPA of 2.50 out of 4.0 in B.Sc. in CSE, EEE, EECE, ETE, ECE, ICE, IT, CS, SWE, or equivalent in the relevant discipline.

Admission Test Syllabus

1) Basic of Computer 25 Marks
2) Basic of ICT 30 Marks
3) English 15 Marks
Total= 70 Marks

Exam Type

MCQ (1 Hour)

Weightage

1) Written(MCQ) – 50%
2) Viva- 15%
3) Previous Exam- 35% (B.Sc.-20% and SSC/HSC-15%)

Contact Information

Program Co-Coordinator, MICT , Dept. of ICT, FST, BUP, Phone- 01769021816 (09am-05pm), Email: mict@bup.edu.bd

Others Information

Course Interaction Time: Friday & Saturday (09:00 am – 06.00 pm)

Masters in Information and Communication Technology (MICT)
Introduction
The Department of Information and Communication Technology (ICT) is one of the pioneer departments of this university providing top-quality educations in Information and Communication technology at its graduate programs. ICT is the leading booming sector in present day. It is already declared as a thrust sector in Bangladesh. Keeping this in mind, the department offers ICT courses to produce Information and Communication technology specialist.
Master’s in information and Communication Technology (MICT) program is designed to produce graduates with solid foundation in Information and Communication Technology skills and knowledge that can be applied across a wide range of application. It focuses on the systems development aspects of employment in the Information and Communication Technology profession. Students gain extensive experience in developing information and communication technology to address the needs of modern organizations.
Vision of the Program
The vision of the Masters of Information and Communication Technology (MICT) program is to create future leaders in information and communication technology by focusing on training, research, and innovation in ICT related fields.

Mission of the Program
The mission of the MICT program is to provide quality education in ICT related fields and train the students to effectively apply this education to solve real-world problems, thereby contributing towards the benefit of our country and the humanity.

Program Objectives

a.   To master the research methods, procedures and processes, with development of critical and self-critical assessment
b.   To develop the ability to research, select and organize information by analysis, as well as synthesize solution and evaluate it and anticipate their consequences so that they contribute to the society
c.   To teach the context of applications, activities, projects and problems that replicate real-life situations with its development giving optimized solution to it using the knowledge of Information and Communication Engineering

Learning Outcomes
Graduates with Masters in ICT degree from BUP will be able to:
a.   Demonstrate knowledge of relevant subject matter.
b.   Exhibit leadership qualities through experimental learnings.
c.   Analyze various technologies and methods to efficiently and effectively and controls ICT projects.
d.   Understand this value of sustainable ICT practices to optimize the use of available resources.

Generic Skills
Students should be able to demonstrate the ability to:
a.   Apply the principles and theory of computing to the requirements, design and development of systems with appropriate understanding of trade-offs.
b.   Present reasoned arguments for a given information handling problem or opportunity, including the impact of modern technologies.
c.   Critically think, evaluate and test systems to ensure the system meets the criteria for its use and future development.
d.   Define and use appropriate research methods to conduct a specific project.
e.   Learn independently, be self-aware and self-manage their time and workload.
f.   Apply critical thinking to problem solving.
g.   Analyze data in multiple forms and justify the appropriate use of technology.
h.   Work effectively with others and exhibit social responsibility.

Teaching Strategy
Students gain knowledge and understanding through practical work that allows the exposure and exploration of underpinning theory and concepts. Guided reading and online content support students in developing their understanding of the subject area. An emphasis on formative feedback and tasks is built into all the first-year modules and may include participation in online activities, in order to practice and explore the topics covered in classes more fully.
Assessment Strategy
Students’ knowledge and understanding is assessed by a range of activities that include both formative (developed to provide feedback on learning) and summative (graded) tasks. A wide range of assessment methods are used. Tasks may involve traditional approaches such as case studies, assignments, presentations and term papers, time constrained tests and exams. (Details are given in article 16 of part one)

MICT1201 | OS & Networking

Objectives

1. To understand the basic issues in operating system design and implementation. 2. To understand the process, memory management, deadlock and file system, 3. To study the network model, topology and protocols 4. To understand the transport layer functionalities.

Outcomes

At the end of this course, students will be able to: 1. Describe, contrast and compare differing structures for operating systems. 2. Understand and analysis theory and implementation of: processes, resource control (concurrency etc.), physical and virtual memory, scheduling, I/O and files. 3. Analyze the structure of OS and basic architectural components involved in OS design. 4. Analyze the various device and resource management techniques for timesharing and distributed systems. 5. Understand the Mutual exclusion, Deadlock detection and agreement protocols of Distributed operating system 6. Students will be able to implement tools and protocols for nrtworking.

References

1. “Operating System Concepts”, 7th edition, Silberschatz, Galvin, Gagne 2. “Modern Operating Systems”, 4th edition, Tanenbum, Bos

MICT2202 | Information Security

Objectives

1. To understand how information security can counteract attempts to attack an individual’s “infosphere,” the person’s sensitive information. 2. To understand how people are the weakest components in any security system. 3. To acknowledge the students about the fundamentals of cryptography and how cryptography serves as the central language of information security. 4. To understand the basic software tools for assessing the security posture of a computer or a network. 5. To understanding how issues of privacy affect information security.

Outcomes

At the end of this course, students will be able to: 1. Demonstrate a basic understanding of the practice of IS, especially in evaluation of information security risks across diverse settings including the Internet and WWW based commerce systems, high bandwidth digital communications and funds transfer services. 2. Explore the idea that in Information Security answers are not always known, and proposed solutions could give rise to new, equally complex problems. 3. Navigate through the language and other dimensions of the field of information security in order to expand your knowledge, skills and their application. 4. Acknowledge the ethical considerations in all judgements and decisions in academic and professional settings. 5. Utilise software packages (for example Maple) to explore the intricacies of cryptography, demonstrating comprehension the use of these and other tools in Information Security.

References

1. “Michael E. Whitman”, Herbert J. Mattord 2. “Principles of Information Security”, Michael E. Whitman, Herbert J. Mattord 3. “Information Security - The Complete Reference Second Edition”, Mark Rhodes-Ousley 4. “The Basics of Information Security”, Jason Andress

MICT2201 | Advanced Artificial Intelligence and Machine Language

Objectives

1. Understand a range of techniques of intelligent systems across artificial intelligence (AI) and intelligent agents (IA); both from a theoretical and a practical perspective. 2. Apply different AI/IA algorithms to solve practical problems. 3. Design and build simple intelligent systems based on AI concepts. 4. To present an overview of artificial intelligence (AI) principles and approaches. 5. Develop a basic understanding of the building blocks ofAI as presented in terms of intelligent agents: Search, Knowledge representation, inference, logic, and learning.

Outcomes

Students should be able to: 1. Identify problems that are amenable to solution by AI methods, and which AI methods may be suited to solving a given problem. 2. Implement basic AI algorithms (e.g., standard search or constraint propagation algorithms). 3. By attending the course the students should acquire a firm grasp of various search techniques and should be able to select an appropriate search technique and apply it in practice. Since search is such a fundamental technique in computer science, the material taught in the course is relevant in contexts other than artificial intelligence.

References

1. “Artificial Intelligence: A Modern Approach”, S.J. Russell and P. Norvig. 2. “Intelligent Systems A Modern Approach”, CrinaGrosan, Ajith Abraham 3. “Intelligent Systems for Engineers and Scientists”, Adrian A. Hopgood 4. “Introduction to Artificial Intelligence”, Wolfgang Ertel 5. “Introducing Artificial Intelligence”, Henry Brighton and Howard Selina

MICT2104 | Smart Sensor Networking

Objectives

1. To understand of various physical phenomenon of different types of sensors and microsystems. 2. To design of sensors with appropriate electronic interface as a complete system. 3. To discuss about various types of sensors like magnetic, optical, bio, chemical, radiation, electrical and mechanical etc. 4. To emphasis on the integration of electronics with sensors to provide a smart transducer or a system on a chip with multiple integrated devices.

Outcomes

At the end of this course, students will be able to: 1. Select the right sensor for a given application. 2. Design basic circuit building blocks. 3. Simulate, synthesize, and layout a complete sensor or sensor system, MEMS device or microsystem ready for fabrication tools.

References

1. N. V. Kirianaki, S. Y. Yurish, N. O. Shpak V. P. Deynega: Data Acquisition and Signal Processing for Smart Sensors, John Wiley, 2004 2. H. Karl, A. Willig: Protocols and Architectures for Wireless Sensor Networks, John Wiley, 2005 3. M. Ilyas, I. Mahgoub (ed.): Handbook of Sensor Networks: Compact Wireless and Wired Sensing Systems, CRC, 2004

MICT2103 | Advanced Digital SIgnal Processing

Objectives

1. To develop the knowledge on Adaptive filtering. 2. To introduce LMS and RLS algorithm those are fundamental to all DSP techniques. 3. To find out parametric techniques for power spectrum estimation. 4. To study various filter banks.

Outcomes

At the end of this course, students will be able to: 1. Design frequency domain adaptive filter. 2. Learn about power spectrum estimation. 3. know about applications of multirate signal processing.

References

1. “Mathematical Methods and Algorithms for Signal Processing”, Moon and Stirling 2. “Theory and Application”, Kay, S. M., Modern Spectral Estimation, Prentice-Hall 2005 . 3. “Foundations of Signal Processing”, Cambridge, M. Vetterli, J. Kovacevic, and V. K. Goyal, 2014.

MICT2102 | Big Data Analytics

Objectives

1. Understand the Big Data Platform and its Use cases 2. Provide an overview of Apache Hadoop 3. Provide HDFS Concepts and Interfacing with HDFS 4. Understand Map Reduce Jobs 5. Apply analytics on Structured, Unstructured Data. 6. Exposure to Data Analytics with R.

Outcomes

At the end of this course, students will be able to: 1. Demonstrate knowledge of big data analytics. 2. Demonstrate the ability to think critically in making decisions based on data and deep analytics. 3. Students will demonstrate the ability to use technical skills in predicative and prescriptive modeling to support business decision-making. 4. Students will demonstrate the ability to translate data into clear, actionable insights. 5. Students will demonstrate effective communication skills that facilitate the effective presentation of analysis results.

References

1. “Analytics in a Big Data World”,BartBaesens; Wiley 2. “Data Analytics”, Dr. Anil Maheshwari. 3. “Learn Analytics”, Alistair Croll& Benjamin Yoskovitz; Eric Ries Series Editor.

MICT2101 | Database Management

Objectives

1.Understand the role of a database management system in an organization. 2.Understand basic database concepts, including the structure and operation of the relational data model. 3. Construct simple and moderately advanced database queries using Structured Query Language (SQL). 4. Understand and successfully apply logical database design principles, including E-R diagrams and database normalization. 5.Design and implement a small database project using Microsoft Access. 6.Understand the concept of a database transaction and related database facilities, including concurrency control, journaling, backup and recovery and data object locking and protocols. 7.Describe and discuss selected advanced database topics, such as distributed database systems and the data warehouse. 8. Understand the role of the database administrator.

Outcomes

1. Differentiate database systems from file systems by enumerating the features provided by database systems and describe each in both function and benefit. 2. Define the terminology, features, classifications, and characteristics embodied in database systems. 3. Analyze an information storage problem and derive an information model expressed in the form of an entity relation diagram and other optional analysis forms, such as a data dictionary. 4. Demonstrate an understanding of the relational data model. 5. Transform an information model into a relational database schema and to use a data definition language and/or utilities to implement the schema using a DBMS. 6. Formulate, using relational algebra, solutions to a broad range of query problems. 7. Formulate, using SQL, solutions to a broad range of query and data update problems. 8. Demonstrate an understanding of normalization theory and apply such knowledge to the normalization of a database. 9. Use an SQL interface of a multi-user relational DBMS package to create, secure, populate, maintain, and query a database. 10. Use a desktop database package to create, populate, maintain, and query a database. 11. Demonstrate a rudimentary understanding of programmatic interfaces to a database and be able to use the basic functions of one such interface.

References

1. "Database System Concepts", Silberschatz A., Korth H.F. &Sudarshan S., Tata McGraw Hill 2. “Database Management Systems”, Ramakrishnan R. &Gehrke J., McGraw Hill 3. “Database Systems”, Thomas Connolly, Carolyn Begg, Addison Wesley 4. “Fundamentals of Database Systems”, Elmasri&Navathe, Addison Wesley

MICT1206 | Research Methodology

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT1206 | Research Methodology

Objectives

This course provides a forum for students to discuss and generate ideas on issues related to a variety of applied social research. Students conduct an in-depth study of a research topic of their choice, discuss issues with experts in the field of research, work in discussion groups, debate and problem solve on selected issues. In the research seminar, the students are given an opportunity to integrate their knowledge, skills and practical experience gained in the program.

Outcomes

Upon successful completion of this course, the student will have reliably demonstrated the ability to: 1. co-ordinate and participate in a seminar(s) on current research issues 2. successfully implement an in-depth research seminar utilizing field experts and collegial discussions/input. 3. articulate in writing a formal description of research design and research analysis. 4. identify and assess data sources and data collection methods for quantitative studies. 5. assess the reliability and validity of measures. 6. demonstrate understanding of quantitative data analysis techniques. 7. interpret analytical results from quantitative studies.

References

1. Writing Successful Science Proposals by Andrew J. Friedland, Carol L. Folt, Publisher: Yale University Press; 2 edition (June 9, 2009) 2. The Myths of Innovation (Hardcover) by Scott Berkun, Publisher: O'Reilly Media (August 30, 2010) 3. Pedhazur, E. J. and Schmelkin, L. P. Measurement, Design and Analysis: An Integrated Appoach, Psychology Press, 2013

MICT2203 | Information Theory and Coding

Objectives

1. To understand the concept of Information Theory & different types of Coding. 2. To learn about data encoding system. 3. To understand the process of performance analysis.

Outcomes

Students will be able to: 1. To reduce transmission error. 2. To increase the performance of various transmission method. 3. To create different types of coding based on conventional coding.

References

1. Fundamentals in Information Theory and Coding- Monica Borda- Springer. 2. Information Theory and Coding- VarunGoyal- Katson Book 3. Management Information Systems- Uma G. Gupta -Galgotia Publications PrivateLtd.

MICT1202 | Cloud Computing

Objectives

1. To understand Cloud Computing, its evolution and applicability; benefits, as well as current and future challenges; 2. To study the basic ideas and principles in data center design; cloud management techniques and cloud 3. Software deployment considerations; 4. To study different CPU, memory and I/O virtualization techniques that serve in offering software, computationand storage services on the cloud; Software Defined Networks (SDN) and Software Defined Storage(SDS); 5. To learn cloud storage technologies and relevant distributed file systems, NoSQL databases and object storage; 6. To distinguish the variety of programming models and develop working experience in several of them.

Outcomes

At the end of this course, students will be able to: 1. Explain the core concepts of the cloud computing paradigm: how and why this paradigm shift came about, the characteristics, advantages and challenges brought about by the various models and services in cloud computing. 2. Apply fundamental concepts in cloud infrastructures to understand the tradeoffs in power, efficiency and cost, and then study how to leverage and manage single and multiple datacenters to build and deploy cloud applications that are resilient, elastic and cost-efficient. 3. Discuss system, network and storage virtualization and outline their role in enabling the cloud computing system model. 4. Illustrate the fundamental concepts of cloud storage, cloud management and cloud services 5. Analyze various cloud programming models and apply them to solve problems on the cloud.

References

1. “Cloud Computing”, John W. Rittinghouse, James F. Ransome 2. “Cloud Computing”, Ray Rafels

MICT1204 | Advanced Optical Communication

Objectives

1. The aim of this course is to train students in methods of analysis, design, dimensioning and performance evaluation of optical fiber-based communications systems. 2. We consider the parameters of interest for systems planning to use different photonic technologies as well as advanced optical signal processing models. 3. Using this knowledge, we will study the design and evaluation of modern optical fiber-based communication systems.

Outcomes

1. Define basic terminology and concepts and take the lead in fiber optic discussions. 2. Compare and contrast the features, functions, benefits and challenges of fiber optic communications with other wireline and wireless solutions. 3. Match communication requirements with practical fiber optic systems. 4. Specify optical fibers, cables, connectors, splices, and other transmission equipment. 5. Participate in or manage all aspects of the fiber optic system life cycle from planning through design, installation, maintenance, upgrading and troubleshooting. 6. Identify when and how to test fiber optic systems by use of power meters and OTDRs. 7. Monitor fiber optics evolution to higher performance and greater market penetration.

References

1. Optical fiber Communications : Principles and practice by John M.Senior, 3rd Edition, 2010, Pearson education 2. Optical Fiber Communication by Gerd Keiser, 5th Edition, 2013, Tata McGraw Hills 3. Fiber Optic Communications Technology by Djafar K Mynbaev& Lowell L Scheiner, 3rd Edition, 2008, Pearson Education. 4. Optical communication systems by J. Gowar, 2nd Edition, 2001, Prentice-Hall of India. 5. Fiber-Optic Communication Systems by Govind P. Agrawal, 3rd Edition, 2007, Wiley India.

MICT1203 | Cellular Mobile Communication

Objectives

1. To understand the basic cellular system concepts. 2. To have an insight into the various propagation models and the speech coders used in mobile communication. 3. To understand the multiple access techniques and interference education techniques in mobile communication.

Outcomes

1. Discuss cellular radio concepts. 2. Identify various propagation effects. 3. To have knowledge of the mobile system specifications. 4. Classify multiple access techniques in mobile communication. 5. Outline cellular mobile communication standards. 6. Analyze various methodologies to improve the cellular capacity

References

1. Mobile Communication Hand Book”, 2nd Edition, IEEE Press. 2002 2. Theodore S Rappaport, “Wireless Communication Principles and Practice”, 2nd Ed, Pearson Education. 2002 3. Lawrence Harte, “3G Wireless Demystified”, McGraw Hill Publications. 2000 4. KavehPahlavan and Prashant Krishnamurthy, “Principles of Wireless Networks”, PHI.2000

MICT1105 | Basic Mathematics and Statistics

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT1101 | Advanced Multimedia Communication

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT1101 | ICT Basics & Programming

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT2000 | Project

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT1103 | Analog and Digital Communication

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT2204 | Satellite and Navigation

Objectives

1. The first of the primary course objectives is to understand how mission dictates orbit.This will require the student to understand the basics of orbital mechanics, the types of satellite orbits, the location of ground stations, and the look angles from ground stations to the satellite.User footprints will also be covered. 2. The second primary objective is to use and understanding of link budget equations to provide sufficient margin for performance. This includes examining the various types of modulation, error correcting codes, and encryption. 3. The third primary objective is to examine concepts of satellite networking.This includes mobile satellite systems for voice and internet communication, data networks, and scientific data. 4. The fourth primary objective is to take a practical look at the engineering impact of the various satellite components on performance. These include power, size, materials used, and attitude control.

Outcomes

1. Able to obtain different types of satellites 2. Ability to calculate the orbital determination and launching methods 3. Ability to develop commands, monitoring power systems and developments of antennas. 4. Able to design antennas to provide Uplink and Down link Frequency. 5. Able to design Satellite for real time applications. 6. Ability to design different kinds of transmitter and receiver antennas. 7. Ability to demonstrate the impacts of GPS, Navigation, NGSO constellation design for tracking and launching.

References

1. Digital Satellite Communications – Tri T. Ha; McGraw-Hill International. 2. Satellite Communication Mobile & Fixed Services - Michael J. Miler; Kluwer Academic Publisher. 3. Satellite Communications - T. Pratt, C. Bostian, J. Allnut; John Wiley & Sons Inc. 4. Mobile Communication satellites theory and application – Ton Logadon; McGraw-Hill International. 5. Digital Communication System with satellite and fiber optic applications - Herald Kolimbiris; Pearson Education Private Ltd. 6. Fundamentals of satellite Communication – Rao& Raja K.N; Prentice Hall of India. 7. Fundamentals of satellite Communication – Jagannathan; Prentice Hall of India. 8. Satellite Communications - Dr. D.C. Agarwal; Khanna Publishers.

MICT2203 | Information Theory & Coding

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT2201 | Advanced Optical Communication

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT2201 | Project

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT2000 | Thesis

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT2001 | Project

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT2108 | Advanced Data Communication

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT1101 | Computer Architecture & Operating System

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT1102 | Advanced Communication Network

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT1103 | Advanced Artificial Intelligence & Machine Learning

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT2207 | Ethical Hacking & Intrusion Management

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT1201 | Advanced Cloud Computing

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT1202 | Broadband & Wireless Communication

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

GED1203 | Research Methodology

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT1204 | Advanced Digital Signal Processing

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT2103 | Advanced Computer Network

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT3104 | Operating System

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT1205 | Mathematics for Engineers

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT1204 | Data Structure and Algorithm

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT3107 | Computer Programming

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT2109 | Advanced Digital Communications

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT2117 | Wireless Communication

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT2114 | Advanced Embedded Systems

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT2111 | Computer Graphics and Animation

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT1204 | OS and Network Security

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT2119 | Network Planning and Management

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT1201 | ICT Project Management

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT1203 | Cloud Computing

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT2112 | IT Entrepreneurship and Innovation

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT2113 | Advanced Telecommunication Systems

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT1104 | ICT Fundamentals

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT1103 | Digital Forensics

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT1102 | Advanced Data Communication

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT2106 | Mobile/Cellular Communication

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT2214 | Computer Networking

Objectives

On successful completion of this course students will be able to: • explain the way protocols currently in use in the Internet work and the requirements for designing network protocols. • capture and analyze network traffic.and apply the theory of basic network performance analysis • analyze soundness or potential flaws in proposed protocols • describe the current architecture of the Internet and the entities involved with the day to day running of the Internet and the process involved with development of policy and new protocols • implement key networking algorithms in simulation

Outcomes

Student will be able to understands application layer protocols
Understand routing protocols, and can design own routing protocols
Understand transport layer protocols
Use the knowledge in IoT, CPS

References

Book

MICT2208 | Ethical Hacking

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT2205 | Big Data Analytics

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT2207 | Operating System

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT2207 | OperatingSystem

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT2101 | Advanced Database Management System

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT2116 | Advanced Optical Communication

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT2107 | Advanced Pervasive Computing

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT3105 | Database Management

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT2105 | Ethical Hacking

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT2114 | Cyber Law and Ethics

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT2102 | Advanced Web Programming

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT3106 | Networking

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

1st Semester

MICT1103 | Advanced Artificial Intelligence and Machine Learning

Objectives

1. Understand a range of techniques of intelligent systems across artificial intelligence (AI) and intelligent agents (IA); both from a theoretical and a practical perspective. 2. Apply different AI/IA algorithms to solve practical problems. 3. Design and build simple intelligent systems based on AI concepts. 4. To present an overview of artificial intelligence (AI) principles and approaches. 5. Develop a basic understanding of the building blocks ofAI as presented in terms of intelligent agents: Search, Knowledge representation, inference, logic, and learning.

Outcomes

1. Identify problems that are amenable to solution by AI methods, and which AI methods may be suited to solving a given problem. 2. Implement basic AI algorithms (e.g., standard search or constraint propagation algorithms). 3. By attending the course the students should acquire a firm grasp of various search techniques and should be able to select an appropriate search technique and apply it in practice. Since search is such a fundamental technique in computer science, the material taught in the course is relevant in contexts other than artificial intelligence.

References

1. “Artificial Intelligence: A Modern Approach”, S.J. Russell and P. Norvig. 2. “Intelligent Systems A Modern Approach”, CrinaGrosan, Ajith Abraham 3. “Intelligent Systems for Engineers and Scientists”, Adrian A. Hopgood 4. “Introduction to Artificial Intelligence”, Wolfgang Ertel 5. “Introducing Artificial Intelligence”, Henry Brighton and Howard Selina

MICT1104 | Advanced Telecommunication Network

Objectives

The rationale behind this course is to provide the student with an understanding of the evolution of telecommunication networks from traditional Public Switched Telephone Network (PSTN), through the emergence of data networks, local area networks, integrated services digital network (ISDN), broadband ISDN, development of fast packet switching, to the Internet. An overview on the Role of Telecommunications in Developing Countries, Telecommunications Organizations, Telecommunication Standardizations and Services is also provided.

Outcomes

The Role of Telecommunications in Developing Countries; Telecommunication Organizations and Standardization; The Public Switched Telephone Network (PSTN); Signals Carried Over the Network; Transmission Media and Systems; Integrated Services Digital Network (ISDN); x-DSL; Internet Technology.

References

1. T. Anttalainen: Introduction to Telecommunications Network Engineering, Artech House, Boston, 1999. 2. J. Bellamy: Digital Telephony, John Wiley & Sons, 1991, 580 pp. 3. T. Saadawi: Fundamentals of Telecommunication Networks, John Wiley & Sons, Inc., 1994 4. M.P. Clark: Networks and Telecommunications, John Wiley & Sons, 1991 5. R. L. Freeman: Telecommunication System Engineering, John Wiley & Sons, Second Edition, 1989 6. Pramode K. Verma: ISDN Systems: Architecture, Technology and Applications, Prentice Hall, 1990 7. William Stallings: strong>Advances in ISDN and Broadband ISDN, IEEE Comp. Soc. Press, 1993 8. B. G. Lee, Broadband Telecommunications Technology, Artech House, Boston, 1996 9. P.-G. Fontolliet, Telecommunication Systems, Artech House, 1986 ITU-T Recommendations given in CCITT Blue Books related to PSTN, ISDN, Data Networks, etc.

MICT1102 | ICT Project Management

Objectives

1. To provide information on how project management and the effective use of software can help managing ICT projects. 2. To develop a project plan using a step-wise approach. 3. To distinguish ICT projects from other types of projects. 4. To apply various project scheduling techniques.

Outcomes

At the end of the course student will be able to: 1. Perform Project Costing, Scheduling, Resource Allocation and Risk Management. 2. Apply various techniques to manage project staff. 3. Evaluate different types of ICT oriented contracts.

References

1. Project Management: A Managerial Approach, 4 th Edition, Jack Meredith and Samuel Mantel. 2. Project Management: Strategic Design and Implementation, 4th Edition, David Cleveland and Lewis Ireland. 3. Software Project Management, 4th Edition, Mike Cotterel and Bob Hughes. 4. Project Management for Information Systems by James Cadle& Donald Yeates, Prentice Hall, Fourth Edition, ISBN 0-273-68580-5.

2nd Semester

MICT1204 | Research Methodology

Objectives

This course provides a forum for students to discuss and generate ideas on issues related to a variety of applied social research. Students conduct an in-depth study of a research topic of their choice, discuss issues with experts in the field of research, work in discussion groups, debate and problem solve on selected issues. In the research seminar, the students are given an opportunity to integrate their knowledge, skills and practical experience gained in the program.

Outcomes

1. Co-ordinate and participate in a seminar(s) on current research issues 2. Successfully implement an in-depth research seminar utilizing field experts and collegial discussions/input. 3. Articulate in writing a formal description of research design and research analysis. 4. Identify and assess data sources and data collection methods for quantitative studies. 5. Assess the reliability and validity of measures. 6. Demonstrate understanding of quantitative data analysis techniques. 7. Interpret analytical results from quantitative studies.

References

1. Writing Successful Science Proposals by Andrew J. Friedland, Carol L. Folt, Publisher: Yale University Press; 2 edition (June 9, 2009) 2. The Myths of Innovation (Hardcover) by Scott Berkun, Publisher: O'Reilly Media (August 30, 2010) 3. Pedhazur, E. J. and Schmelkin, L. P. Measurement, Design and Analysis: An Integrated Appoach, Psychology Press, 2013

MICT1203 | Advanced Database Management Systems

Objectives

1. Understand the role of a database management system in an organization. 2. Understand advance database concepts, including the structure and operation of the relational data model. 3. Construct simple and moderately advanced database queries using Structured Query Language (SQL). 4. Understand and successfully apply logical database design principles, including E-R diagrams and database normalization. 5. Design and implement a small database project using Microsoft Access. 6. Understand the advanced concept of a database transaction and related database facilities, including concurrency control, journaling, backup and recovery and data object locking and protocols. 7. Describe and discuss selected advanced database topics, such as distributed database systems and the data warehouse. 8. Understand the role of the database administrator.

Outcomes

1. Differentiate database systems from file systems by enumerating the features provided by database systems and describe each in both function and benefit. 2. Define the terminology, features, classifications, and characteristics embodied in database systems. 3. Analyze an information storage problem and derive an information model expressed in the form of an entity relation diagram and other optional analysis forms, such as a data dictionary. 4. Demonstrate an understanding of the relational data model. 5. Transform an information model into a relational database schema and to use a data definition language and/or utilities to implement the schema using anadvance DBMS. 6. Formulate, using relational algebra, solutions to a broad range of query problems. 7. Formulate, using SQL, solutions to a broad range of query and data update problems. 8. Demonstrate an understanding of normalization theory and apply such knowledge to the normalization of a database. 9. Use an SQL interface of a multi-user relational DBMS package to create, secure, populate, maintain, and query a database. 10. Use a desktop database package to create, populate, maintain, and query a database. 11. Demonstrate a rudimentary understanding of programmatic interfaces to a database and be able to use the basic functions of one such interface.

References

1. "Database System Concepts", Silberschatz A., Korth H.F. &Sudarshan S., Tata McGraw Hill 2. “Database Management Systems”, Ramakrishnan R. &Gehrke J., McGraw Hill 3. “Database Systems”, Thomas Connolly, Carolyn Begg, Addison Wesley 4. “Fundamentals of Database Systems”, Elmasri & Navathe, Addison Wesley

MICT1202 | Internet of Things (IoT)

Objectives

1. To understand of various physical phenomenon of different types of sensors and microsystems. 2. To design of sensors with appropriate electronic interface as a complete system. 3. To discuss about various types of sensors like magnetic, optical, bio, chemical, radiation, electrical and mechanical etc. 4. To emphasis on the integration of electronics with sensors to provide a smart transducer or a system on a chip with multiple integrated devices.

Outcomes

1. Select the right sensor for a given application. 2. Design basic circuit building blocks. 3. Simulate, synthesize, and layout a complete sensor or sensor system, MEMS device or microsystem ready for fabrication tools.

References

1. N. V. Kirianaki, S. Y. Yurish, N. O. Shpak V. P. Deynega: Data Acquisition and Signal Processing for Smart Sensors, John Wiley, 2004 2. H. Karl, A. Willig: Protocols and Architectures for Wireless Sensor Networks, John Wiley, 2005 3. M. Ilyas, I. Mahgoub (ed.): Handbook of Sensor Networks: Compact Wireless and Wired Sensing Systems, CRC, 2004

MICT1201 | Cloud Computing

Objectives

1. To understand Cloud and Fog Computing, its evolution and applicability; benefits, as well as current and future challenges; 2. To study the basic ideas and principles in data center design; cloud management techniques and cloud 3. Software deployment considerations; 4. To study different CPU, memory and I/O virtualization techniques that serve in offering software, computationand storage services on the cloud; Software Defined Networks (SDN) and Software Defined Storage(SDS); 5. To learn cloud storage technologies and relevant distributed file systems, NoSQL databases and object storage; 6. To distinguish the variety of programming models and develop working experience in several of them.

Outcomes

1. Explain the core concepts of the cloud computing paradigm: how and why this paradigm shift came about, the characteristics, advantages and challenges brought about by the various models and services in cloud computing. 2. Apply fundamental concepts in cloud infrastructures to understand the tradeoffs in power, efficiency and cost, and then study how to leverage and manage single and multiple datacenters to build and deploy cloud applications that are resilient, elastic and cost-efficient. 3. Discuss system, network and storage virtualization and outline their role in enabling the cloud computing system model. 4. Illustrate the fundamental concepts of cloud storage, cloud management and cloud services 5. Analyze various cloud programming models and apply them to solve problems on the cloud.

References

1. “Cloud Computing”, John W. Rittinghouse, James F. Ransome 2. “Cloud Computing”, Ray Rafels

3rd Semester

MICT2101 | Big Data Analytics

Objectives

1. Understand the Big Data Platform and its Use cases 2. Provide an overview of Apache Hadoop 3. Provide HDFS Concepts and Interfacing with HDFS 4. Understand Map Reduce Jobs 5. Apply analytics on Structured, Unstructured Data. 6. Exposure to Data Analytics with R.

Outcomes

1. Demonstrate knowledge of big data analytics. 2. Demonstrate the ability to think critically in making decisions based on data and deep analytics. 3. Students will demonstrate the ability to use technical skills in predicative and prescriptive modeling to support business decision-making. 4. Students will demonstrate the ability to translate data into clear, actionable insights. 5. Students will demonstrate effective communication skills that facilitate the effective presentation of analysis results.

References

1. “Analytics in a Big Data World”,BartBaesens; Wiley 2. “Data Analytics”, Dr. Anil Maheshwari. 3. “Learn Analytics”, Alistair Croll& Benjamin Yoskovitz; Eric Ries Series Editor.

MICT2102 | Advanced Digital Signal Processing

Objectives

1. To develop the knowledge on Adaptive filtering. 2. To introduce LMS and RLS algorithm those are fundamental to all DSP techniques. 3. To find out parametric techniques for power spectrum estimation. 4. To study various filter banks.

Outcomes

1. Design frequency domain adaptive filter. 2. Learn about power spectrum estimation. 3. know about applications of multirate signal processing.

References

1. “Mathematical Methods and Algorithms for Signal Processing”, Moon and Stirling 2. “Theory and Application”, Kay, S. M., Modern Spectral Estimation, Prentice-Hall 2005 . 3. “Foundations of Signal Processing”, Cambridge, M. Vetterli, J. Kovacevic, and V. K. Goyal, 2014.

MICT2103 | Recent Trends in ICT

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

4th Semester

MICT2211 | Advanced Optical Communication

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICT2000 | Project

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

About BUP

Administration

Regulatory Bodies

Academic Personnels

Masters in Information and Communication Technology (MICT)

Faculty: Faculty of Science & Technology (FST)

Department: Department of Information and Communication Technology

Program: Masters in Information and Communication Technology (MICT)

Course Outline

2.8 Admission Procedure

2.8.1 Eligibility for Admission

2.8.2 Admission Rules

2.8.3 Selection Process

2.9 Admission in the Program

The selected candidates from BUP must collect their Admission Form from the Department and complete admission/registration formalities within the given time frame by paying the required fees at the beginning of the academic year. The following rules will apply in this regard:

2.10 Tuition and other Fees

Note: Admission cancellation and refund of admission fee will be executed as per following: No amount of total admission fee will be refunded.

2.11 Review of Fee Structure

2.12 Deadline for Submission of Fees/Dues