Bangladesh University of Professionals | Masters in Information and Communication Engineering

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 Engineering

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, and opportunities;
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

Scholarships (semester-wise) and stipends (semester-wise) are granted to many students based on the criteria set by the University. In general terms, scholarship is a financial grant-in-aid awarded to students, whereas stipend is an allowance paid to students as monetary assistance. The students are granted scholarships and stipends duly scrutinized by a committee that consists of the following members:

a. Vice Chancellor - Chairman

b. Pro-Vice Chancellor - Member

c. Treasurer - Member

d. All Deans - Member

e. Controller of Examinations - Member

f. Registrar - Member

g. Dean, FBS - Member Secretary

2.3.1 Required CGPA for Scholarship

Name of the Scholarship	Minimum CGPA	Amount BDT/month
Chancellor Scholarship	3.9	2500
Vice Chancellor Stipend	3.80	1500

2.3.2. Required CGPA for Stipend

Name of the Stipend	Minimum CGPA	Amount BDT/month
BUP Scholarship	3.75	2000
BUP Stipend	3.50	1000

N.B

1. BUP Scholarship and Stipend Policy is already in vouge as per 'Rules and Regulations for Awarding Scholarship and Stipend-2015'.

2. In the case of BUP Scholarship/Stipend concerned committee may review the minimum GPA for the respective Department considering the overall standard of the result obtained during the particular Semester. Respective Dean may recommend the special cases based on the student's merit and financial capability.

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. Every year, BUP organizes at least one International Seminar. The purposes of the Guest Lectures/Seminars/Symposiums/Workshops/Exercises are:

a. Academic Success and Career Awareness: To provide an opportunity to the students to learn about the scholarly characteristics of an academic setting. To participate in activities that improve the students' awareness of careers and their individual career goals.

b. Communication: To create a classroom environment that encourages a communication-across-the-curriculum approach to learning.

c. Research and Undergraduate Scholarship: To engage students in activities that promote skills and positive attitudes toward scholarship and seeking knowledge.

d. Critical Thinking: To create activities that encourage students to use reasoned thinking and the analysis of information, including rhetorical strategies.

e. Community Building and Diversity: To encourage collaborative learning and support students' efforts to connect with the university setting's many varied components and diversity.

f. Good Citizenship: To appraise the students about the duties and obligations of a good citizen to demonstrate exemplary behavior both in the local and global context.

g. Developing Human Qualities: To encourage students to develop desirable human qualities like kindness, forgiveness, charity, acceptance, tolerance, openness, and other human qualities required to make our societal life better.

2.8 Admission Procedure

BUP seeks applications from prospective candidates, who fulfill Masters in Information and Communication Engineering (MICE) admission qualifications 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 July/August of each year through media advertisement and the BUP website notice board. The candidates are asked to apply online. The detailed admission procedure has been spelled out in Admission Guideline, which is available on the BUP website (www.bup.edu.bd).

2.8.1 Eligibility for Admission

For admission to the program leading to a Masters in Information and Communication Engineering (MICE), an applicant must have,

A minimum GPA of 4.50 out of 5.00 or a first division or equivalent in any one of SSC and HSC or 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. in ICE, an applicant must have obtained a bachelor's degree in ICE or relevant engineering background from any public university of Bangladesh.

2.8.3 Selection Process

All the students of the Dept. of ICT, BUP are selected for this regular program, M. Sc./M. in Information and Communication Engineering course. But students outside ICT, FST, BUP have to go through a selection process.

2.8.3.1. For Regular Students of Department of ICT, BUP

The students of Department of ICT, FST, BUP will be selected for admission in MICE, BUP without giving any admission test.

2.8.6.2. For Students of Other Universities

Students who have completed their B. Sc. in ICE or relevant subjects from other public universities of Bangladesh need to seat for an admission test but on the availability of the vacancy of seats after the completion of admission of ICT graduates from BUP.

Written Test:

The students outside of Department of ICT, FST, BUP have to go through an admission test. The admission test subject criteria with its marks distribution are given below:

Serial	Subjects	Syllabus	Marks
	English	Follow the graduate syllabus	10
	Mathematics		20
	Software/Hardware/Communication		30
	Total =		60

b. Communication Test (Interview/ Viva-voce)

The candidates are selected for communication tests based on their written test results. Panels of faculty members will take the communication test/interview (Weightage is 10 marks).

c. Marks from Past Public Examinations

The results of past public examinations carry 30 marks weightage, where 10% is from HSC and equivalent, 10% from SSC and equivalent, and 10% from graduate and equivalent. The marks are calculated in a simple linear distribution method from candidates' GPA.

d. Final Selection

The final selection will be made based on merit. The merit list is prepared according to combined marks obtained by candidates in the written admission test (60 marks), score in communication test (10 marks), and past public examinations (30 marks) out of 100 marks.

2.9 Admission in the Program

After final selection, the candidates are asked to go through a medical checkup at BUP Medical Centre to ascertain their medical fitness. The selected candidates must collect the admission form from the Admission Section of Registrar Office and complete admission and registration formalities within the given time frame with respective BUP Admission Section and Faculty by paying required fees. The following rules will apply in this regard:

The candidate failing to complete admission formalities within the prescribed date and time, his/her selection will be considered as canceled.
A student who fails to attend the class within two weeks of the commencement of 1^st-semester class, his/her admission will be considered as canceled.

In case, if the prescribed vacancies are not filled up by the candidates in the first merit list, other merit lists will be published from the waiting candidates for admission, who will have to follow the same procedure for admission.

2.10 Tuition and other Fees

2.10.1 Semester-wise Fees

1^st Semester

Sl.	Category of Fees / Charges		Amount (Tk.)
	Application processing Fee (if Applicable)		1000.00
	Admission Fee		10,000.00
	Registration Fee		1,000.00
	Library Fee		500.00
	Computer Lab and Training Aid Fee		600.00
	Tuition Fee	Thesis (05 courses, 500/= per course)	2,500.00
		Project (05 courses, 500/= per course)
	Medical Fee		600.00
	Sports Fee		600.00
	Examination Fee (Theory course)	Thesis (13 credit, 500/= per credit)	6,500.00
		Project (13 credit, 500/= per credit)
	Grade Sheet Fee		500.00
	Student Welfare Fee		2,000.00
	Education Enhancement Fee		600.00
	Cultural/Magazine Fee		300.00
	Center Fee		500.00
	MT Development Fee		2,000.00
	Transport Fee		500.00
	Recreation Fee		300.00
	ID card Fee		100.00
	BUP Tie/Scarf Fee		500.00
Grand Total =			30,600.00
In Word: Thirty Thousand Six Hundred taka

2^nd Semester

Sl.	Category of Fees / Charges		Amount (Tk.) Thesis (3 x Courses)	Amount (Tk.) Project (5 x Courses)
	Library Fee		500.00	500.00
	Computer Lab and Training Aid Fee		600.00	600.00
	Tuition Fee	Thesis (03 course, 500/= per course)	1,500.00	2,500.00
		Project (05 Course, 500/= per course)
	Medical Fee		600.00	600.00
	Sports Fee		600.00	600.00
	Examination Fee	Thesis (09 credit, 500/= per credit)	4,500.00	7,500.00
		Project (15 credit, 500/= per credit)
	Grade Sheet Fee		500.00	500.00
	Student Welfare Fee		2,000.00	2,000.00
	Education Enhancement Fee		600.00	600.00
	Cultural/Magazine Fee		300.00	300.00
	Center Fee		500.00	500.00
	Transport Fee		500.00	500.00
	Recreation Fee		300.00	300.00
Grand Total =			13,000.00	17,000.00

3^rd Semester

Sl.	Category of Fees / Charges			Amount (Tk.) Thesis (18 credit)	Amount (Tk.) Project (2 x Courses + project 6 credit)
	Library Fee			500.00	500.00
	Computer Lab and Training Aid Fee			600.00	600.00
	Tuition Fee	Thesis		0.00	1,000.00
		Project (02 Course, 500/= per course)
	Medical Fee			600.00	600.00
	Sports Fee			600.00	600.00
	Examination Fee	Thesis		0.00	3,000.00

		Project (6 credit, 500/= per credit)
	Grade Sheet Fee			500.00	500.00
	Student Welfare Fee			2,000.00	2,000.00
	Education Enhancement Fee			600.00	600.00
	Cultural/Magazine Fee			300.00	300.00
	Center Fee			500.00	500.00
	Transport Fee			500.00	500.00
	Recreation Fee			300.00	300.00
	Provisional Certificate fee			500.00	500.00
	Viva-Voce / Defense		Thesis	14000.00	6000.00
			Project
Grand Total =				21,500.00	17,500.00

Summary

Sl.	Year	Semester	Total Courses	M. Sc. Engg./ M. Engg. (Thesis/Project)	Total Credit	Amount (TK.)
1	First	1^st	5	M. Sc. Engg.	13	30,600.00
1		1^st	5	M. Engg.	13	30,600.00
2		2^nd	3	M. Sc. Engg.	9	13,000.00
2		2^nd	5	M. Engg.	15	17,000.00
3	Second	3^rd	Thesis	M. Sc. Engg.	18	21,500.00
3	Second	3^rd	2+Project	M. Engg.	12	17,500.00
Total			8	M. Sc. Engg.	40	65,100.00
Total			12	M. Engg.	40	65,100.00

2.10.2 Additional Fees/Payments (As Required):

SL.	CATEGORIES OF FEES/CHARGES	AMOUNT (TK.)
1.	Re-registration Fee	5000.00
2.	Supplementary Final Exam Fee	4000.00
3.	Dis-collegiate (per course)	5000.00

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 of M. Sc. Engg. must complete 22 credit theory course work and for M. Engg. it is 34. However, a maximum of six courses will be allowed in a semester, when a student is repeating course/courses because of obtaining an 'F' grade or ‘I’ grade or if they want to improve their previous grades. This will be allowed only once for a particular course and the students have to take the course/courses with the batch that comes immediately after them. A student will be allowed to retake only 2 courses in each semester. He/she must complete all the courses of masters within 3 years of his or her registration period. A student must register for a minimum of 2 courses in a semester.

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.
At least 2 (two) classes per week, consisting of 90 minutes respectively, should be planned for each batch. Of the 90 minutes, 30 minutes may be catered for individual presentation/ consultation as per the course outlines.
The students will be required to write a Thesis/Project on a topic related to the program he/she is enrolled in. To conduct the research for Thesis/Project successfully and to write the completion of the Thesis/Project in the stipulated time, the students will be under the direct supervision of a supervisor who is preferably an in-house faculty member. The supervision will include at least twice one to one meeting (monthly) of students with the respective supervisor. Altogether, at least 10- 12 meetings will be required to complete the 'Thesis/Project Work' successfully.
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.
The course teachers are expected to ensure that n+1 quizzes/weekly tests are conducted in a semester for each course. and n will be counted. (n = credit hour).
An individual term paper/project paper/assignment will be assigned to the students that will be followed by a presentation.
Assignments (individual and group), case studies, etc. should be allotted to students which will be followed by presentations, as per the course requirements. The presentations must be short. For that purpose, miscellaneous periods or 15-30 minutes in each day’s class may be utilized.
One analytical group assignment and the individual presentation should be included in a course. As per the requirements of the course, field trips may be organized.
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
95% and above	10.0
90% to 94%	9.0
85% to 89%	8.0
75% to 84%	7.0 (Non-collegiate, with payment @5000/- per course)
Less than 75%	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.

2.17 Review of Class Attendance

The attendance policy mentioned in the above table will be reviewed as and when necessary by the university authority and updated attendance policy will be effective as per revision.

3. Performance Evaluation System

3.1 Distribution of Marks for Evaluation

3.1.1 Distribution of Marks for Evaluation (Theory Course)

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 (Four)	10%
Project paper/Assignments /Term Paper (Individual) including Presentation	10%
Class attendance	10%
Total:	100%

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

3.1.3 Thesis /Project Report

In addition to the theoretical examination of the Thesis/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/Project Report work shall be submitted to the examination committee. The Examination Committee shall appoint the examiners for the Thesis /Project Report as per the requirements of their respective professional programs.

Evaluation of Thesis/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 Thesis/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_iG_i

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	1.5-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	2.00	* Maximum one (01) ‘F’ Grade
2	2^nd – 3^rd	2.50	* Maximum one (01) ‘F’ Grade

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

If a student gets an ‘I’ or ‘F’ grade in a maximum of two courses, before the condition of retaking the courses, he/she will be promoted to the next semester.

If a student gets an ‘I’ or ‘F’ grade in a minimum of three courses in a semester/ year, he/she will not be promoted to the next semester/year. In such a case a student will have two more chances for clearing I or F grades.

He/she must complete all the retake courses within 3 years of his or her registration period.

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 the respective 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 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' or ‘I’ grade.
Students must have a minimum CGPA of 2.50.
Minimum grade in the Thesis/ Project Dissertation 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

The Academic Council may dismiss any student on disciplinary grounds 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. The 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 Masters Academic Guideline-2021 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	8/12	22/34	18/6	40	M. Sc.*/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 & Communication Engineering (MICE)

5.1 Introduction

Masters in Information and Communication Engineering (MICE) program is designed to produce postgraduates with a solid foundation in information engineering skills and knowledge that can be applied across a wide range of applications. It focuses on the systems development aspects of employment in the information engineering profession. Students gain extensive experience in developing information and communication engineering skills to address the needs of modern organizations.

The students will be provided with two types of degrees M. Sc. Engg. and M. Engg. The students who will be selected for research-oriented areas will do a thesis of 18 credits and will be awarded M. Sc. Engg. after completion of the course. The students who will be selected for project-oriented areas will do a project of 6 credits and will be awarded M. Engg. after completion of the course. The registration period for a student will be 3 years. The students will have to complete 40 credits and there will be a total of 3 semesters.

The program includes basic programming concepts and modern programming environments, network engineering principles, communication system networking, object-oriented software architectures, enterprise web, cloud, mobile technologies, and software quality management. It also encompasses industrial orientation, project management, and communication skills, which are developed in addition to the exploration of the technical and human aspects of information engineering and its use. Modern communication technologies with internet protocol, wireless, optical mobile, satellite multimedia, etc. are also explored.

5.2 Vision of the Program

To develop world standard program of Information and Communication Technology through education and research.

5.3 Mission of the Program

To impart quality education on Information and Communication Technology with a view to preparing world-standard engineers based on dynamically changing technology.

5.4 Program Objectives

The department has the following program objectives:

To teach the context of applications, activities, projects, and problems that replicate real-life situations with its development giving optimized solutions to it using the knowledge of information and communication engineering.
To capable the students working as an ICT professional, utilizing the knowledge acquired in the field of Information and Communication Technology.
To encourage adaptability by exposing students to the latest trends in ICT, such as artificial intelligence, data science, and cloud computing, preparing them to learn and adopt new technologies throughout their careers.
To instill a strong sense of ethics and professionalism, teaching students the responsibilities of handling data and systems with integrity and in compliance with legal and regulatory standards.
To promote a culture of continuous learning and research, encouraging students to pursue further education or stay updated with ICT developments to remain competitive in the industry.
To foster an entrepreneurial mindset among students, enabling them to launch, manage, or scale technology-based startups, especially in sectors like telecommunications, software development, IoT (Internet of Things) and data communications, etc.

5.5 Learning Outcomes

A student graduating from MICE program of BUP will be able to:

Apply their course knowledge in creating and designing any software solutions for the betterment of society.
Develop skills to work with artificial intelligence and machine learning.
Apply their course knowledge in technological advancement in the generation upgradation of mobile cellular communication to create fast connectivity.

5.6 Generic Skills

Students should be able to demonstrate the ability to:

Critically think, evaluate and test systems to ensure that the system meets the criteria for its use and future development by contributing to society.
Work in a team by maintaining good coordination with the team members.
Lead any kind of work while working in a group with good and manageable communication skills.
Learn anything willingly with a good manner and must have self-motivation to encourage

himself/herself in learning.

Involve in any type of extra-curricular activities in building their potentialities among themselves.
Take any type of positive challenges in order to develop their problem-solving approach to any type of work.

5.7 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 theoretical modules and may include participation in online activities, in order to practice and explore the topics covered in classes successfully.

5.8 Assessment Strategy

Students’ knowledge and understanding are 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 is used. Tasks may involve traditional approaches such as case studies, assignments, presentations and term papers, time-constrained tests, and exams.

6. Course and Credit Related Information

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

Sl.	Course Code	Name of the Course	Credit
1	MICE-5101	Advanced Machine Learning	3.0
2	MICE-5102	Information and Cyber Security	3.0
3	MICE-5103	Big Data Analytics and Design	3.0
4	MICE-5104	Advanced Networking	3.0
5	MICE-5105	Research Methodology	1.0
6	MICE-5201	Entrepreneurship and Business Ethics	3.0
7	MICE-5202	Advanced Software Engineering	3.0
8	MICE-5203	Industrial Internet of Things	3.0
9	MICE-5204	Broadband & Wireless Communication	3.0
10	MICE-5001	Advanced Operating System	3.0
11	MICE-5002	NLP and Large Language Model	3.0
12	MICE-5003	Image Processing and Pattern Recognition	3.0
13	MICE-5004	Advanced Embedded System	3.0
14	MICE-5005	Advanced Cloud Computing	3.0
15	MICE-5006	Digital Forensics	3.0
16	MICE-5007	Algorithm and Optimization	3.0
17	MICE-5008	Graph Theory and its Application	3.0
18	MICE-5009	Ethical Hacking and Intrusion Management	3.0
19	MICE-5010	Recent Trends in Information & Communication Engineering	3.0
20	MICE-5011	Advanced Digital Signal Processing	3.0
21	MICE-5012	Optical Waveguide Theory	3.0
22	MICE-5013	Advanced Telecommunication Engineering	3.0
23	MICE-5014	Radio Frequency Technology	3.0
24	MICE-5015	Advanced Optical Communication	3.0
25	MICE-5016	Satellite Communication	3.0
26	MICE-5017	Radar Engineering	3.0
27	MICE-5018	Geographic Information System Technology	3.0

*Note: Courses may be added based on the availability of the new subject areas.

6.2 Information Engineering Core Courses– M. Sc. Engg. (9 credits)/M. Engg. (12 Credits)

Information Core Courses and Credit Distribution
Sl.	Course Code	Name of the Course	M. Sc. Engg.	M. Engg.
1	MICE-5101	Advanced Machine Learning	3.0	3.0
2	MICE-5102	Information and Cyber Security	3.0	3.0
3	MICE-5201	Big Data Analytics and Design	3.0	3.0
4	MICE-5203	Advanced Software Engineering	-	3.0
		Total	9.0	12.0

6.3 Communication Engineering Core Courses - M. Sc. Engg. (3 credits)/M. Engg. (9 Credits)

Communication Core Courses and Credit Distribution
Sl.	Course Code	Name of the Course	M. Sc. Engg.	M. Engg.
1	MICE-5104	Advanced Networking	3.0	3.0
2	MICE-5202	Industrial Internet of Things	-	3.0
3	MICE-5203	Broadband & Wireless Communication	-	3.0
		Total	6.0	9.0

6.4 Elective Courses

Elective courses to be selected by the Students from Information/Communication Disciplines - M. Sc. Engg. (6 credits)/M. Sc. Engg. (9 Credits)

Elective Courses
Sl.	Course Code	Name of the Course	M. Sc. Engg.	M. Engg.
1		Elective Course (Information/Communication)	3.0	3.0
2		Elective Course (Information/Communication)	3.0	3.0
3		Elective Course (Information/Communication)	-	3.0
		Total	6.0	9.0

6.5 Thesis/Project Related Courses - Thesis (18 credits)/Project (6 Credits)

Other Courses
Sl.	Course Code	Name of the Course	M. Sc. Engg.	M. Engg.
1	MICE-5105	Research Methodology	1.0	1.0
2	MICE-5201	Entrepreneurship and Business Ethics	3.0	3.0
3	MICE-6000	Thesis	18.0	-
4	MICE-6100	Project	-	6.0
		Total	20.0	8.0

6.6 Elective Courses from Information & Communication Disciplines

Information Related Courses
Sl.	Course Code	Name of the Course	Credit
1	MICE-5001	Advanced Operating System	3.0
2	MICE-5002	NLP and Large Language Model	3.0
3	MICE-5003	Image Processing and Pattern Recognition	3.0
4	MICE-5004	Advanced Embedded System	3.0
5	MICE-5005	Advanced Cloud Computing	3.0
6	MICE-5006	Digital Forensics	3.0
7	MICE-5007	Algorithm and Optimization	3.0
8	MICE-5008	Graph Theory and its Application	3.0
9	MICE-5009	Ethical Hacking and Intrusion Management	3.0
10	MICE-5011	Recent Trends in Information & Communication Engineering	3.0

Communication-Related Courses
Sl.	Course Code	Name of the Course	Credit
1	MICE-5011	Advanced Digital Signal Processing	3.0
2	MICE-5012	Optical Waveguide Theory	3.0
3	MICE-5013	Advanced Telecommunication Engineering	3.0
4	MICE-5014	Radio Frequency Technology	3.0
5	MICE-5015	Advanced Optical Communication	3.0
6	MICE-5016	Satellite Communication	3.0
7	MICE-5017	Radar Engineering	3.0
8	MICE-5018	Geographic Information System Technology	3.0

6.7 Summary of Credit Distribution

SL	YEAR	SEMESTER	M. Sc. Engg. (THESIS) / M. Engg. (PROJECT)	NO. OF THEORY COURSES	THEORY (CR.)	THESIS/ PROJECT	CREDIT
1	First	1^st	M. Sc. Engg.	5	13	-	13
		1^st	M. Engg.	5	13	-	13
		2^nd	M. Sc. Engg.	3	9	-	9
		2^nd	M. Engg.	5	15	-	15
2	Second	1^st	M. Sc. Engg.	-	-	18	18
2	Second	1^st	M. Engg.	2	6	6	12
	Total	M. Sc. Engg.	M. Sc. Engg.	-	-	-	40
	Total	M. Engg.	M. Engg.	-	-	-	40

6.8 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 corresponds to the year/level in which the course is normally taken by the students.
The second digit corresponds to the semester/ term in which the course is normally taken by the students.
The last two digits denote various courses, where an odd number is used for theoretical courses and an even number for laboratory courses.

The course designation system is illustrated as follows:

MICE-5101	Advanced Machine Learning

	Course Title
	Course Serial Number
	(Reserved for departmental use to denote course)
	Signifies 1^st Semester course Signifies 5^th Year (Masters) course Department identification code

6.9 Semester-wise Course and Credit Distribution

6.9.1 Semester-wise Course and Credit Distribution for M. Sc. Engg. (40 credits)

Year	Semester	Course Code	Course Title	Theory (Cr.)	Total Credit Hours	Weekly Contact Hours
1^st	1^st	MICE-5101	Advanced Machine Learning	3.00	3.0	3
		MICE-5102	Information and Cyber Security	3.00	3.0	3
		MICE-5103	Big Data Analytics and Design	3.00	3.0	3
		MICE-5104	Advanced Networking	3.00	3.0	3
		MICE-5105	Research Methodology	1.00	1.0	2
			Total	13.00	13	14
1^st	2^nd	MICE-5201	Entrepreneurship and Business Ethics	3.0	3.0	3
			Elective Course (Information/Communication)	3.00	3.0	3
			Elective Course (Information/Communication)	3.00	3.0	3
			Total	9.00	9.0	9
2^nd	1^st	MICE-6000	Thesis	18.00	18.0	18
			Total	18.00	18	18
Grand Total					40.0	41

6.9.2 Semester-wise Course and Credit Distribution for M. Engg. (40 credits)

Year	Semester	Course Code	Course Title	Theory (Cr.)	Total Credit Hours	Weekly Contact Hours
1^st	1^st	MICE-5101	Advanced Machine Learning	3.00	3.0	3
		MICE-5102	Information and Cyber Security	3.00	3.0	3
		MICE-5103	Big Data Analytics and Design	3.00	3.0	3
		MICE-5104	Advanced Networking	3.00	3.0	3
		MICE-5105	Research Methodology	1.00	1.0	2
			Total	13.00	13	13
1^st	2^nd	MICE-5201	Entrepreneurship and Business Ethics	3.0	3.0	3
		MICE-5202	Advanced Software Engineering	3.00	3.0	3
		MICE-5203	Industrial Internet of Things	3.00	3.0	3
		MICE-5204	Broadband & Wireless Communication	3.00	3.0	3
			Elective Course (Information/Communication)	3.00	3.0	3
			Total	15.00	15.0	15
2^nd	1^st		Elective Course (Information/Communication)	3.00	3.0	3
			Elective Course (Information/Communication)	3.00	3.0	3
		MICE-6100	Project	6.00	6.0	6
			Total	12.00	12.0	12
Grand Total					40.0	41

Detail syllabus is attached in Annex A

7 Thesis/Project Related Guidelines

7.1 Thesis - Credit 18

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/MIST/BUET/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, either from within or outside the department, may be appointed upon the determination by the Supervisor or the student that such an appointment is necessary. The thesis proposal with the signature of Supervisor and Co-supervisor shall be submitted for approval by the Academic Committee after completion of at least 09 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.
Students will be selected for a thesis based on their performance in the undergraduate result and the result of the 1^st semester (must have at least CGPA 3.25 in undergraduate program or in the 1st semester of the current program). If the student has experience in research, his application for the thesis can be considered.
The research work must be carried out in BUP or at a place 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.
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.
Every student shall submit to the Chairman, Department of ICT/Dean, through his/her Supervisor, the required number of typewritten copies of his/her thesis in the approved format on or before a date to be fixed by the Supervisor and Co-supervisor concerned in consultation with the Chairman, Department of ICT/ Dean.
The student shall certify that the research work was done by him/her and the 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.
For thesis, publication in a conference or journal is required.
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.
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.

7.1.1 Thesis Lifecycle for Effective Management

Submission of Proposal – Notice will be given in the 2^nd semester to the students after 1^st weeks of class and must be submitted within 2 weeks.
Supervisor confirmation – Within the next month.
Proposal Presentation – After 3 months of the 2^nd Semester, the proposal presentation will be done where the research work/project proposal will be accepted/rejected.
Pre-defense – Pre-defense will be done after acceptance of a publication in any journal or conference, within the registration period of the program.
Final defense – The final defense will be conducted after the pre-defense, based on the recommendation and approval of the supervisor and the Head of the Department, where the total evaluation of students’ works will be done. Students must submit their publication when applying for the final defense. The Final defense must take place within the registration period of the program.

7.1.2 Submission of Thesis

Every student submitting a thesis 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 Head of the Department of ICT and must satisfy the examiners that he/she has gained satisfactory knowledge related to the thesis/project work.

7.1.3 Examination Board for Thesis

An Examination Board for the student for the thesis/project examination shall consist of four to five members including the Supervisor. The Supervisor shall act as the Chairman of the board. The Academic Committee shall recommend the names of the examiners for approval of Dean FST. The examination board for Thesis shall be constituted as follows:

Supervisor	Chairman
Co-supervisor (if any)	Member
Chairman, Department of ICT	Member
One member from within the Department	Member
One external member from outside the department from the relevant Institute/ Department	(External)

If any member of the Examination Board is unable to accept the appointment or has to relinquish his/her appointment before the examination. The 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 thesis/project report and/or presentation, the student can be given one more chance to resubmit the thesis/project report and/or appear in another examination as recommended by the Board.

7.2 Project - Credit 6

The students who will not be selected for pursuing thesis, will automatically be selected for project. If any student is willing to do project-even if being selected for thesis, his application can be considered.
Project work shall be carried out under the supervision of a full-time member of the staff belonging to the relevant department of BUP/ MIST/ BUET/ 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 by the Academic Committee after completion of a minimum of 30 Credits.
If any change is necessary of the approved project (title, content, cost, Supervisor, Co-supervisor, etc.) it shall be approved by the Academic Committee.
The project work must be carried out in BUP or at a place approved by the Dean FST or recommended 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.
Eligible project students will be selected by the department.
No publication is needed for project students.
Students shall submit to the Chairman, Department of ICT, through his/her Supervisor, the required number of typewritten copies of his/her project report in the approved formation 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 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.
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.
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.

7.2.1 Project Lifecycle for Effective Management

Submission of Proposal – Notice will be given in the 2^nd semester to the students after 1^st weeks of class and must be submitted within 2 weeks.
Supervisor confirmation – Within the next month.
Proposal Presentation – After 3 months of the 2^nd Semester, the proposal presentation will be done where the research work/project proposal will be accepted/rejected.
Pre-defense – Pre-defense will be done at the end of the 3^rd Semester. The Pre-defense will be done to identify the progress and to help the students by giving any suggestions regarding their works.
Final defense – The final defense will be conducted after the pre-defense, based on the recommendation and approval of the supervisor and the Head of the Department, where the total evaluation of students’ works will be done. The Final defense must take place within the registration period of the program.

7.2.2 Submission of Project

Every student submitting a thesis/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 Head of the Department of ICT and must satisfy the examiners that he/she has gained satisfactory knowledge related to the thesis/project work.

1. 1. Examination Board for Project
2. An Examination Board for the student for the project examination shall consist of four to five members including the Supervisor. The Supervisor shall act as the Chairman of the board. The Academic Committee shall recommend the names of the examiners for approval of Dean FST. The examination board for Project shall be constituted be as follows:

Supervisor	Chairman
Co-supervisor (if any)	Member
Chairman, Department of ICT	Member
One member from within the Department	Member
One external member from outside the department from the relevant Institute/ Department	(External)

If any member of the Examination Board is unable to accept the appointment or has to relinquish his/her appointment before the examination. The 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 thesis/project report and/or presentation, the student can be given one more chance to resubmit the thesis/project report and/or appear in another examination as recommended by the Board.
1. 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 80% of the final marks and the evaluation of the other board members will carry 20% of the final marks.

7.8 Re-defense:

If any student’s thesis/project is not up to the mark of acceptance in the final defense, he/she have to give the re-defense for the successful completion of the Masters degree.
The date of the re-defense will be set again by the consent of the thesis/project Supervisor and the Chairman of the Department of ICT.

ANNEX-A

DETAIL COURSE CURRICULUM

CORE COURSES

MICE-5101 Advanced Machine Learning

Credit Hour: 3

Course Objectives:

The course covers the principles, design, and implementation of learning programs that improve their performance on some set of tasks with experience.

Course Contents:

Introductory Concepts: Aspects of developing a learning system: training data, concept representation, function approximation.
Regression Models: Logistic regression, Linear regression, estimator bias and variance, active learning, non-linear predications, kernels, Kernel regression.
Classification Models: Support vector machine (SVM) and kernels, kernel optimization, Linear classification, perceptron update rule, Perceptron convergence, generalization, Maximum margin classification, Classification errors, regularization.
Clustering: Agglomerative clustering, K-means clustering, Hierarchical clustering, Spectral Clustering.
Model selection: Model selection criteria, Description length, feature selection, combining classifiers, Bagging, Boosting, margin, and complexity, Margin and generalization, mixture models, Mixtures, and the expectation-maximization (EM) algorithm, EM, regularization.
Bayesian networks: Learning Bayesian networks, Probabilistic inference, Guest lecture on collaborative filtering, Current problems in machine learning.
Evaluation of Learning Algorithm: Measuring the accuracy of learned hypotheses. Comparing learning algorithms: cross-validation, learning curves, and statistical hypothesis testing.

Course Outcomes:

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

Develop an appreciation for what is involved in learning from data.
Understand a wide variety of learning algorithms.
Understand how to apply a variety of learning algorithms to data.
Understand how to evaluate learning algorithms and model selection.

References:

“Machine Learning”, Tom M. Mitchell
“Machine Learning”, John Paul Mueller, Luca Massaron

MICE-5102 Information and Cyber Security

Credit Hour: 3

Course Objectives:

To gain a fundamental knowledge of what Cyber Security is and how it applies to your daily work.
To gain an understanding of terms commonly used in Cyber Security such as vulnerability.
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.

Course Contents:

Introduction: Principles of cyber security, Interrelated components of the computing environment, Cyber security models (the CIA triad, the star model, the Parkerian Hexad), Cyber vulnerabilities, and consequences,
Cyber threats: Types of attackers, Motives-what drives an attacker, Means, Cyber-attack, Methods, Types of cyber-attack & attack vectors, botnet, DoS, DDoS, social engineering, cloud security issues, EDoS, Risks of conducting a cyberattack. Cybercrime, Cyber harassment, Cyberwarfare, Cyber surveillance, Issues making cyber security difficult, State of security today.
Cyber threat detection and mitigation: Intrusion detection, signature and anomaly detection, IDS, IPS, incident response, security operation center.
Principles of risk: Types of risk, Risk strategies, Risk Management Framework (RMF), Disaster recovery plan and procedures, Challenges of a disaster recovery plan, traditional disaster recovery.
Policies: national ICT Act & Policy, National Information security policy guideline, government and private sector roles in securing cyberspace, International laws in securing cyberspace.

Course Outcomes:

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

Possess a fundamental knowledge of Cyber Security.
Understand what a vulnerability is and how to address the most common vulnerabilities.
Know basic and fundamental risk management principles as it relates to Cyber Security.
Have the knowledge needed to practice safer computing and safeguard your information.
Critically evaluate and reflect on ethical issues that relate to the IT discipline.

References:

“Information Security: The Complete Reference”, Rhodes-Ousley, Mark, 1^st Edition.
“Information Security Management: Concepts and Practice”, New York, McGraw-Hill, 2013.
“Cyber security: A practitioner’s guide”, David Sutton.
“Cyber security and Cyber war: What Everyone Need to Know”, P.W. Singer, Allan Friedman, 1^st Edition, ISBN-13: 978-0199918119.
“Cyber Security Basics: Protect your organization by applying the fundamentals”, Don Franke, 1^st Edition.

MICE-5103 Big Data Analytics and Design

Credit Hour:3

Course Objectives:

Understand the Big Data Platform and its Use cases
Provide an overview of Apache Hadoop
Provide HDFS Concepts and Interfacing with HDFS
Apply analytics on Structured, Unstructured Data.
Exposure to Data Analytics with R.

Course Contents:

Introduction to Big Data Analytics: Getting started with R, Data Exploration, Data Preparation.
Statistical Concepts: Statistical Thinking, Introduction to Machine Learning; Dimensionality Reduction; Clustering; Market Basket Analysis; Kernel Density Estimation; Regression; Logistic Regression; Decision Trees; K-Nearest Neighbor Classification; Bayesian Classifiers; Neural Networks; Support Vector Machines; Ensemble Learning.
Data Analysis: Data Collection, Sampling & Preprocessing, Predictive Analytics, Descriptive Analytics, Survival Analysis, Social Network Analytics, Analytics: Putting It All to Work, Example applications.

Course Outcomes:

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

Demonstrate knowledge of big data analytics.
Demonstrate the ability to think critically in making decisions based on data and deep analytics.
Students will demonstrate the ability to use technical skills in predictive and prescriptive modeling to support business decision-making.
Students will demonstrate the ability to translate data into clear, actionable insights.

References:

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

MICE-5104 Advanced Networking

Credit Hour: 3

Course Objectives:

This course is designed to provide an in-depth understanding of modern networking technologies, principles, and practices. The main objective is to equip students with advanced skills and knowledge required to design, implement, and troubleshoot complex network systems across various environments including enterprise, data centers, and IoT ecosystems. By the end of the course, students will acquire the key networking concepts, protocols, and tools. This will enable them to meet the evolving challenges in the field of networking.

Course Contents:

Recap of Core Networking Concepts: Review of OSI and TCP/IP Models, Advanced IP Addressing and Subnetting, Review of Fundamental Routing Protocols.
Lab: Complex Subnetting and Basic Routing Protocol Configuration
Advanced Routing Protocols: In-depth Study of OSPF and ISIS, BGP Deep Dive: Internal and External BGP, BGP Multihoming Techniques.
Lab: Configuring Advanced OSPF/ISIS and BGP Scenarios
Network Virtualization: Concepts of Network Virtualization, Virtual LANs (VLANs) and VxLANs, Virtual Routing and Forwarding (VRF).
Lab: Basic Implementation of VLANs and VRF
MPLS (Multiprotocol Label Switching): Introduction to MPLS Architecture, MPLS VPNs and Traffic Engineering, MPLS vs. Traditional IP Routing.
Lab: Configuring Basic MPLS and L2VPN, L3VPN.
Software-Defined Networking (SDN): SDN Architecture and Concepts, OpenFlow and SDN Controllers, SDN Applications and Real-life Use Cases
Segment Routing: Introduction to Segment Routing, Overview of Segment Routing and its evolution from traditional MPLS, Benefits of Segment Routing: Simplification, Scalability, Flexibility, Segment Routing Architecture and Components, Key Concepts: Segments, Segment Identifiers (SIDs), Types of SIDs: Node SID, Adjacency SID, Binding SID, SR Global Block (SRGB) and SR Local Block (SRLB), SR vs. Traditional Routing Protocols, Introduction to SRv6
Network Automation and Orchestration: Introduction to Network Automation Tools (Ansible), Automating Network Configuration and Management.

Lab: Automating Network Tasks Using Ansible or Terraform

Advanced IP Security: Next-Generation Firewalls (NGFWs) and IDS/IPS, Advanced Threat Detection and Mitigation, Introduction to Routing Security (RoA and RPKI)

Lab: Configuring NGFWs using OPNsense

Internet of Things (IoT) Networking: IoT Network Architecture, Protocols and Standards in IoT Networking (LoRa, 6LoWPAN, MQTT), Security Challenges in IoT Networks

Lab: Building a Secure IoT Network with Rasbery-PI.

Data Center Networking: Data Center Network Architectures (Spine-Leaf), Storage Networking (SAN, NAS) , High Availability and Disaster Recovery in Data Centers.

Lab: Designing and Implementing a Data Center Network

Network Performance Optimization: Network Performance Monitoring Tools and Techniques, Traffic Shaping, QoS, and Load Balancing, Network Performance Tuning and understanding the Metrics.

Lab: Implementing QoS and Load Balancing Strategies

Advanced Network Troubleshooting: Systematic Network Troubleshooting Approaches, Advanced Diagnostic Tools (Traceroute, Wireshark, NetFlow, SFlow), Case Studies in Complex Network Troubleshooting

Lab: Troubleshooting Complex Network and Routing Issues

Advance Wireless Networking: Overview of Wireless Networking, Wireless Networking Fundamentals, Review of wireless communication principles (radio frequency, signal propagation), Key differences between wired and wireless networking, Wireless Networking Standards, Overview of IEEE 802.11 standards (Wi-Fi 4, 5, 6, and 6E), Comparison of other wireless technologies (Bluetooth, Zigbee, LTE, 5G), Advanced Wireless Concepts, Multiple Input Multiple Output (MIMO) and Beamforming, OFDM (Orthogonal Frequency Division Multiplexing), Channel bonding and aggregation
Future Trends in Networking: Quantum Networking, AI and Machine Learning in Networking, The Future of Networking: Challenges and Opportunities
Project and Final Review: Comprehensive Review and Final Exam Preparation, Project Presentation: Designing and Implementing a Full-Scale Advanced Network

Course Outcomes:

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

Understand and be able to explain the principles of a layered protocol architecture.
Understand, explain and calculate digital transmission over different types of communication media.
Understand, explain and solve mathematical problems for datalink and network protocols.
Describe the principles of access control to shared media and perform performance calculations.

References:

1. "Computer Networking: A Top-Down Approach", by James F. Kurose and Keith W. Ross

2. "Routing TCP/IP, Volume I & II”, by Jeff Doyle

3. "MPLS Fundamentals", by Luc De Ghein

4. "SDN: Software Defined Networks", by Thomas D. Nadeau and Ken Gray

5. "Network Security with OpenSSL", by John Viega, Matt Messier, and Pravir Chandra

6. "Network Automation Cookbook", by Karim Okasha

7. "Wireless Communications: Principles and Practice", by Theodore S. Rappaport

MICE-5105 Research Methodology

Credit Hour: 1

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 Contents:

Introduction to Research: Definition Engineering, Components of research methodology, aim, Nature and scope of research, Importance of Research, Research methods vs. Methodology, Types of research, Applied vs. Fundamental, Quantitative vs. Qualitative, Conceptual vs. Empirical, Recent trends, criteria of good research.
Research Formulations and Design: Defining and formulating the research problem, selecting the problem, Importance of literature review in defining a problem, literature review-primary and secondary sources, reviews, monographs, patents, research databases, web as a source, searching the web, critical literature review, identifying gap areas from literature and research database, development of working hypothesis.
Data Collection and Analysis: Sources of data sets, Computer and its role in research, Effective use of the Internet, Execution of the research, Methods of data collection, Reliability check, Sampling Methods, Data Processing and Analysis strategies - Data Analysis with Google Colab, Kaggle, Jupiter notebook and Statistical Packages (Sigma STAT, SPSS for student t-test, ANOVA, etc.), Hypothesis testing, Generalization and Interpretation.
Simulation software: Introduction, simulation software features, use of simulation software (MATLAB, COMSOL Multiphysics, R Programming, etc.), data import and export, geometry, Sketching, meshing, convergences, and Graphical presentation.
Scientific conduct: Ethics with respect to science and research, Intellectual honesty and research integrity, Scientific misconducts: Falsification, Fabrication, and Plagiarism (FFP), Redundant publications: duplicate and overlapping publications, salami slicing, Selective reporting and misrepresentation of data.
Publication ethics: Definition, introduction and importance, best practices/standards setting initiatives and guidelines: COPE, WAME, etc., Conflicts of interest,
Publication misconduct: definition, concept, problems that lead to unethical behavior and vice versa, types, Violation of publication ethics, authorship and contributor ship, Identification of publication misconduct, complaints and appeals, Predatory publishers and journals, Plagiarism.
Reporting and thesis writing: Structure and components of scientific reports, Types of the report, Technical reports and thesis, Significance, Different steps in the preparation, Layout, structure and Language of typical reports, Illustrations and tables- Bibliography, referencing and footnotes, Oral presentation, planning, preparation, practice, Making a presentation, Importance of effective communication.

Laboratory Part:

1. Standards and Predatory Journals: Open access publications and initiatives, online resources to check publisher copyright & self-archiving policies, Software tools to identify standards and Predatory publishers, Time management, and developing Gantt Charts. Journal finder/journal suggestion tools viz. JANE, Elsevier Journal Finder, Springer Journal Suggested, etc.

2. 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.

3. Latex software: Use Latex software in writing manuscripts (Thesis, Project, Article etc.) through Overleaf

4. Databases and research metrics: Sources of data sets, download of data from reliable sources, Reliability check, Data processing in Google Colab, Kaggle, Jupiter notebook (Data Reading, Cleaning, Integration, Transformation, Reduction, Discretization), Databases: Indexing databases, Citation databases: Web of Science, Scopus, etc., Research Metrics: Impact Factor of journal as per Journal Citation Report, SNIP, SIR, IPP, Cite Score, Metrics: h-index, g index, i10 index, altmetrics.

5. Simulation software: Use of simulation software like MATLAB, COMSOL Multiphysics, R Programming etc. (Instructors may show a minimum of one simulation software)

6. Programming Software: Machin learning, Jave, Python, VS code, etc. (Instructors may show a minimum of one software)

7. Publication Misconduct: Subject-specific ethical issues, FFP, authorship, Conflicts of interest, use of plagiarism software like Turnitin, Urkund and other open-source software tools.

8. Writing of Research Report and Proposal: Writing a journal/ conference paper /poster presentation/research report using latex, writing of synopsis.

Course Outcomes:

Upon completing 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.
critically 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.
critically 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.

Reference Books:

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

MICE-5201 Entrepreneurship and Business Ethics

Credit Hour: 3

Entrepreneurship is the ability and readiness to develop, organize and run a business enterprise, along with any of its uncertainties to make a profit or sustenance. The university graduates are observed to prepare mainly for getting good jobs and performing there well. But it is vital to create business entities to afford and host those opportunities in a sustainable manner. To maintain a balance between these two sides, it is very important that we help the potential tech-business founders from our resource pool. This course is dedicated to them. However, there is another form of entrepreneurial spirit needed to hold leadership positions in an organization. This course should help the students to develop those traits as well.

Course Objectives:

Cultivate an entrepreneurial mindset.
Master the entrepreneurial process from idea to execution.
Identify and evaluate business opportunities.
Develop effective business plans and strategies.
Manage financial aspects of a business.
Build marketing and sales expertise.
Develop risk management and problem-solving capabilities.
Enhance leadership and team-building skills.
Ensure compliance with legal and ethical standards.
Improve pitching and presentation skills.
Foster innovation in product and service development.
Promote social responsibility and sustainable practices.

Course Contents:

1. 1. Introduction to Entrepreneurship

Understanding the concept and importance of entrepreneurship, different types of business entities, understanding the business life cycle.

1. 1. Business Modeling and Planning

Difference and correlation between the business model and business planning.

Understanding the business model canvas and balance scorecard.

1. 1. Market Study and Customer Segmentation

Identifying the target customer segments, learning their core activities, pain points and gain aspirations; the use of surveys and FGD.

1. 1. Product Innovation, Pricing and Marketing

Designing the value proposition, product design, materials sourcing and production process design. Product cost calculation, margin & price determination. Developing price plans.

Branding & production promotion plans.

1. 1. Sales and Customer Relationship

Direct sales, channel sales, online sales.

Product sales & subscription sales.

Joint venture & outsourcing models. Learning how to participate in the tendering process in private and public organizations.

Customer billing, collection & support services.

1. 1. Production and Service Delivery

MTO & MTS model, use of production planning and control, importance of project management,

Business process automation, workforce management.

1. 1. Cost and Revenue Estimation

Monthly and yearly revenue estimation considering both one-off revenue and recurring revenue;

Monthly and yearly cost estimation considering both one-off costs and recurring costs;

Determination of the business case and how to make it positive.

1. 1. Financing the Business

Cash requirements planning with amount and schedule;

Own initial funding, startup funding, venture capital, banking facility, etc.;

Knowing the startup funding facilities in Bangladesh.

1. 1. Starting a Business

Company registration, trade license, tax & VAT registration, opening bank accounts.

Initial office and team formation.

1. 1. Basic Compliance in Business

Income tax & VAT compliance;

RJSC, BIDA and BB compliance

1. 1. Corporate Vision, Mission & Value System

Defining the vision, mission and adopting a value system

1. 1. Application of Ethics in Business

Ethics in products, marketing, sales, customer service, procurement, financial accounting & reporting, people management;

Use of code of conduct (CoC), corporate penal code, whistleblowing, etc.

1. 1. Watching the Conflict of Interests (CoI)

CoI scenarios, disclosure procedure and remediation

Course Outcomes:

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

1. Understand how to initiate a business with a higher probability of success
2. Incorporate a basic ethical approach in doing business.

References:

Business Model Generation by Alexander Osterwalder and Yves Pigneur
Local laws and regulations of RJSC, NBR, BB, City Corporation, etc.

MICE-5202 Advanced Software Engineering

Credit Hour: 3

Course Objectives:

To develop a broad understanding of the discipline of advanced software engineering.
To learn about requirements management techniques.
To acquire the skill of software project management.
To learn the techniques of quality assurance.
To examine the concepts and techniques associated with several advanced and industrially relevant topics, relating to both the product and processes of software engineering.

Course Contents:

Introduction: Overview, History, Types of software, Ethics of software engineers.
The Wider Software Engineering Context: Embedded software and systems engineering: overview, examples and industrial realities, Project Management - Project Planning and Scheduling, Standards, Case studies.
Software Engineering Process: Unified Software Development Process, Software Process Improvement, Software Economics, Software Quality, Software Metrics - Measurement, Estimation and Prediction, Requirements Management, Configuration Management, Risk Management, Testing, and Inspection.
Software re-engineering: Software evolution, legacy systems, re-engineering techniques overview - reverse engineering, restructuring & forward propagation, reverse engineering and its techniques, refactoring code to analysis artifacts and architecture.
Software Architecture: Architecture Description Languages: Pattern-Oriented Software Architecture, Component-based Development, Distributed Software Architectures using Middleware, Enterprise Application Integration, Architectures for Mobile and Pervasive Systems, Model Driven Architecture.
Advanced Modeling: UML Extension Mechanisms, Object Constraint Language, Model Checking.

Course Outcome:

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

Describe the knowledge and skills necessary to practice software engineering, and the professional issues that a software engineer might face.
Create major activities and key deliverables in software development.
Use project management concepts to manage projects, people, and products.
Use software engineering concepts to construct quality software systems.

References:

“Software Engineering: A Practitioner's Approach”, 7^th edition, Roger S. Pressman.
“Pattern-Oriented Software Architecture”, Volume 1, F. Buschmann, R. Meunier, H. Rohnert, P. Sommerlad, M. Stal.
“Software Engineering”, 10^th edition, Ian Sommerville.
“Software Engineering: Principles and Practice”, 3^rd edition, Hans van Vliet.

MICE-5203 Industrial Internet of Things

IIoT is an ecosystem of devices, sensors, applications, and associated networking equipment that work together to collect, monitor, and analyze data from industrial operations. Analysis of such data helps increase visibility and enhances troubleshooting and maintenance capabilities.

Course Objectives:

To understand the SCADA and IoT systems used in the industry
To design sensors with the appropriate electronic interface as a complete system.
To learn how IoT systems work as a whole
To learn designing IoT systems to solve industrial problems with smart solutions.

Course Contents:

1. Introduction to Supervisory Control and Data Acquisition (SCADA): Understanding control circuits, computer-based control systems and their benefits. Discussing common industrial applications of SCADA systems and their benefits.
2. Architecture of a SCADA System & Devices: The field devices (sensors or interface circuits), the remote terminal unit (RTU) or PLC, the communications network, and the human-machine interface (HMI) or frontend application along with data storage.
3. Programming Skills for SCADA: C/C++, Python, Java, etc.
4. Designing a Basic SCADA System: A case study-based classroom lesson.
1. Standard Protocols Used in the Industry: Distributed network protocol (DNP3), Modbus, IEC 60870-5, etc.
1. Class Test on SCADA: A simple class test to verify the level of SCADA knowledge gained by the students.
1. IoT System Architecture & IoT Devices: The device layer (sensors), the network layer, the management layer (data & API servers), and the application layer (frontends) – similarity with the SCADA system. The difference between SCADA and IoT.
1. Sensors in an IoT System: Basic sensor architecture; various classes of sensors such as passive & active, analog & digital, scalar & vector sensors; various types of sensors such as electrical sensor, light sensor, touch sensor, mechanical sensor, pneumatic sensor, optical sensor, speed sensor, temperature sensor, ultrasonic sensor, etc.
1. Consideration of the Network in an IoT System: Use of WiFi, LAN, mobile network, etc.
1. MQTT Messaging System: The MQTT protocol definition, MQTT broker, programming scope, etc.
1. The Server’s Role in an IoT System: Messaging server, database server, API server, etc.
1. Designing a Basic IoT System: A case study-based classroom lesson.
1. Introduction of SNMP Protocol: SNMP way of monitoring, device security, OID and MIB database
1. Low-cost Design of SNMP-based Monitoring System: A case study-based classroom lesson for power equipment using an IP network.

- Security of IoT Systems: Understanding the security vulnerabilities of an IO system and protecting them from misuse.

Course Outcomes:

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

Select the right sensor for a given application.
Design basic IoT systems.

References:

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

MICE-5204 Broadband & Wireless Communication

Credit Hour: 3

Course Objectives:

To distinguish the major wireless communication standards.
To characterize the tradeoffs among frequency reuse, signal-to-interference ratio, capacity, and spectral efficiency.
To analyze the error probabilities for common modulation schemes
To characterize TDMA, FDMA and CDMA

Course Contents:

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.

Labs 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.

Course Outcomes:

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

Learn about various multiple access techniques.
Calculate bit error rate & channel capacity.
Know about broadband wireless standards.

References:

“Wireless Communications and Networks”, William Stallings

“IEEE 802 Wireless Systems”, B. H. Walke, S. Mangold, and L. Berlemann, Wiley

ELECTIVE COURSES

MICE-5001 Advanced Operating System

Credit Hour: 3

Course Objectives:

To learn the fundamentals of Operating Systems.
To learn the mechanisms of OS to handle processes and threads and their communication.
To learn the mechanisms involved in memory management in contemporary OS.
To gain knowledge on distributed operating system concepts that include architecture, mutual exclusion algorithms, deadlock detection algorithms, and agreement protocols.

Course Contents:

Introduction: What is an operating system, History of an operating system, Operating system concepts.
Operating System Structures: Operating system services, System call, Types of System call, Operating System structures.
Process Management: Process concept, Process scheduling, Inter-process communication, Operations on processes.
Threads: Overview, Multicore Programming, Multithreading models, Thread libraries, Thread usage.
Process Synchronization: Critical section problem, Peterson’s solution, Synchronization hardware, Mutex lock, Semaphore, Classical problems of synchronization, Monitors.
CPU Scheduling: Basic concepts, Scheduling criteria, Scheduling algorithm, multiple processors scheduling.
Deadlocks: Deadlock characterization, Deadlock handling, prevention, avoidance, detection, recovery.
Memory Management: Swapping, Contiguous memory allocation, Segmentation, Paging, Structure of the page table.
Virtualization: Types and techniques for efficient virtualization, memory, and i/o
virtualizations, virtual appliances.
Cloud: clouds as a service, virtual machine migration, Checkpointing.
Security: Intro Security, System and Network Threats, Authentication, Access Control, Cryptography.
Others: Overview, Architecture, Features of Windows, Linus, Android.

Course Outcomes:

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

Describe, contrast, and compare differing structures for operating systems.
Understand and analyze theory and implementation of processes, resource control (concurrency, etc.), physical and virtual memory, scheduling, I/O, and files.
Analyze the structure of OS and basic architectural components involved in OS design.
Understand the Mutual exclusion, Deadlock detection, and agreement protocols of distributed operating systems.

References:

“Operating System Concepts”, 7^th edition, Silberschatz, Galvin, Gagne
“Modern Operating Systems”, 4^th edition, Tanenbum, Bos
“Operating Systems: Three Easy Pieces”1^st edition, Remzi Arpaci-Dusseau, Andrea Arpaci-Dusseau.

MICE-5002 Natural Language Processing and Large Language Models

Credit Hour: 3

Course Objectives

This course provides a comprehensive overview of Natural Language Processing (NLP) and Large Language Models (LLMs). The course covers the foundational concepts, algorithms, and applications of NLP, culminating in a deep understanding of LLMs and their impact on various domains.

Course Content:

Introduction to Machine Learning: Basic Understanding of Machine Learning and Deep learning, commonly used ML and DL models, advantages, limitations and applications.
Introduction to Natural Language Processing: Definition and scope of NLP, NLP tasks (e.g., text classification, named entity recognition, machine translation), Text preprocessing and feature engineering, Evaluation metrics for NLP systems
Statistical Language Models: N-gram models, Probabilistic models (e.g., Hidden Markov Models, Conditional Random Fields), Language modeling for text generation and prediction
Syntactic and Semantic Analysis: Part-of-speech tagging, Syntactic parsing (e.g., dependency parsing, constituency parsing), Semantic analysis (e.g., word sense disambiguation, semantic role labeling)
Machine Learning for NLP: Supervised learning for NLP tasks (e.g., support vector machines, decision trees, neural networks), Unsupervised learning for NLP tasks (e.g., clustering, topic modeling), Deep learning for NLP (e.g., recurrent neural networks, convolutional neural networks, transformers)
Large Language Models: Architecture of LLMs (e.g., Transformer architecture), Training and fine-tuning LLMs, Applications of LLMs (e.g., text generation, question answering, summarization), Limitations and challenges of LLMs
NLP Tools and Libraries: NLTK, spaCy, Gensim, TensorFlow, PyTorch.
Generative Adversarial Networks (GANs): Architecture and training process of GANs, Variants of GANs (e.g., DCGAN, CycleGAN, StyleGAN), Applications of GANs in image generation, style transfer, and data augmentation
Variational Autoencoders: Architecture and training process of VAEs, Applications of VAEs in data generation, anomaly detection, and latent space exploration
Autoregressive Models: Architecture and training process of autoregressive models (e.g., GPT, BERT), Applications of autoregressive models in text generation, language modeling, and machine translation
Diffusion Models: Architecture and training process of diffusion models, Applications of diffusion models in image generation, text generation, and audio synthesis
Applications of NLP and Large Language Models: Text Generation and Summarization, Machine Translation, Sentiment Analysis, Chatbots and Virtual Assistant, Information Extraction, Text Classification, Medical Record Analysis, Drug Discovery, Document Review, Predictive Analytics, Learning, Language Tutoring, Search Engines
Ethical Considerations and Societal Impact: Bias in LLMs, Privacy and security concerns, Misinformation and disinformation, Responsible AI development and deployment

Course Outcomes

By the end of this course, students will be able to:

Understand the fundamental concepts and techniques of NLP.
Apply NLP algorithms to solve real-world problems.
Develop a strong foundation in LLMs, including their architecture, training, and applications.
Critically evaluate the strengths and limitations of LLMs.
Explore the ethical implications of LLMs and their societal impact.

References:

Jurafsky, D., & Martin, J. H. (2021). Speech and Language Processing (3rd ed.). Prentice Hall.
Manning, C. D., & Schütze, H. (1999). Foundations of Statistical Natural Language Processing. MIT Press.
Bengio, Y., LeCun, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436-444.
Natural Language Processing with Transformers, Revised Edition - Lewis Tunstall, Leandro von Werra, Thomas Wolf
Mastering NLP from Foundations to LLMs - by Lior Gazit, Meysam Ghaffari
Vaswani, A. (2017). Attention is all you need. Advances in Neural Information Processing Systems.

MICE-5003 Image Processing and Pattern Recognition

Credit Hour: 3

Course Objectives:

Use foundational techniques of image processing and analysis such as filtering, segmentation, and local features to solve image processing problems of real-world applications.
Build a statistical classifier and know how to use other classifiers.
Use image processing and pattern recognition techniques to detect objects and activities in images and videos.

Course Contents:

Digital Image Fundamentals - Elements of Visual Perception, Light and the Electromagnetic Spectrum, Image Sensing and Acquisition, Image Sampling and Quantization.
Image Enhancement in the Spatial Domain – Background, Some Basic Gray Level Transformations, Histogram Processing, Enhancement Using Arithmetic/Logic Operations, Basics of Spatial Filtering.
Image Enhancement in the Frequency Domain – Background, Introduction to the Fourier Transform and the Frequency Domain.
Smoothing Frequency- Domain Filters, Sharpening Frequency Domain Filters, Homomorphic Filtering, Implementation.
Image Restoration - A Model of the Image Degradation/Restoration Process, Noise Models, Minimum Mean Square Error (Wiener) Filtering, Constrained Least Squares Filtering, Geometric Mean Filter, Geometric Transformations.
Color Image Processing - Color Fundamentals. Color Models, Pseudocolor Image Processing, Basics of Full-Color Image Processing, Color Transformations, Smoothing and Sharpening, Color Segmentation, Noise in Color Images, Color Image Compression.
Wavelets and Multiresolution Processing – Background, Multiresolution Expansions, Wavelet Transforms in One Dimension, The Fast Wavelet Transform, Wavelet Transforms in Two Dimensions, Wavelet Packets.
Image Compression – Fundamentals, Image Compression Models, Elements of Information Theory, Error-Free Compression, Lossy Compression, Image Compression Standards.
Image Segmentation - Detection of Discontinuities, Edge Linking and Boundary Detection, Thresholding, Region-Based Segmentation, Segmentation by Morphological Watersheds, The Use of Motion in Segmentation.
Object Recognition - Patterns and Pattern Classes, Recognition, Theoretic Methods, Structural Methods.

Course Outcomes:

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

Comprehend the fundamentals of image formation.
Appreciate typical pattern recognition techniques for object recognition.
Implement basic image processing and computer vision techniques.
Develop simple object recognition systems.

References:

“Digital Image Processing”, Rafael C Gonzalez and Richard E. Woods.
“Image Processing and Pattern Recognition, Volume 5, 1^st Edition”, Cornelius Leondes.
“Image Processing and Pattern Recognition: Fundamentals and Techniques, 1^st Edition”, Frank Y. Shih

MICE-5004 Advanced Embedded System

Credit Hour: 3

Course Objectives:

To explore the fundamentals of embedded system hardware and firmware design.
To discuss the issues such as embedded processor selection, hardware/firmware partitioning, glue logic, circuit design, circuit layout, circuit debugging, development tools, firmware architecture, firmware design, and firmware debugging.
To discuss the architecture and instruction set of the microcontroller and build and debug wire-wrapped microcontroller board by each student.
The course will culminate with a significant final project which will extend the base microcontroller board completed earlier in the course.

Course Contents:

Introduction to Embedded Systems: Processor and Memory Organization, Devices and Buses for Device Networks, Device Drivers and Interrupts Servicing Mechanism.
Embedded Programming: Programming Concepts and Embedded Programming in C and C++, Program Modeling Concepts in Single and Multiprocessor Systems Software-Development Process, Software Engineering Practices in the Embedded Software Development Process.
State Machines: Composition of state machines, hierarchical state machines, synchronous reactive, sensor actuators.
Embedded Operating System Concepts: Inter-Process Communication and Synchronization of Processes, Tasks, and Threads, Real-Time Operating Systems.
Real-Time Operating Systems Programming Tools: Micro C/OS-II and VxWorks, Case Studies of Programming with RTOS.

Course Outcomes:

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

Acquire knowledge about microcontrollers embedded processors and their applications.
Foster the ability to understand the internal architecture and interfacing of different peripheral devices with Microcontrollers.
Foster the ability to write the programs for a microcontroller.
Foster the ability to understand the role of embedded systems in the industry.

References:

“Embedded System Architecture, Programming and Design”, Raj Kamal.
“Debugging Embedded Microprocessor Systems”, Stuart R. Ball; Butterworth-Heinemann.
“Embedded Microprocessor Systems: Real World Design”, Stuart R. Ball; Butterworth Heinemann.
“Embedded Systems Design”, Steve Heath; Butterworth-Heinemann.
“The Art of Designing Embedded Systems”, Jack G. Ganssle; Butterworth-Heinemann.

MICE-5005 Advanced Cloud Computing

Credit Hour: 3

Course Objective:

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

Course Content:

Cloud Basics: What is Cloud Computing, Basic Concepts, and Terminologies, Cloud Computing History. Cloud Characteristics, Cloud Delivery Models, Cloud Deployment Models, Goals and Benefits, Risks and Challenges.
Cloud Enabling Technology: Internet and Networks, Data Centers, Virtualization, Web Technology. Cloud Infrastructure I: Virtual Server, Resource Virtualization, Resource Pooling and Sharing, Cloud Storage, File System, Database Technology.
Cloud Mechanism: Load Balancing, Scalability& Elasticity, Replication, Monitoring, Software Defined Networks, Network Function Virtualization, MapReduce, Identity & Access Management, Service Level Agreement: Hypervisor Clustering, Service Relocation, Dynamic Failure Detection, and Recovery Architecture
Cloud Services: Amazon Web Services (AWS), Microsoft Azure, Google Cloud, Application
Services, Content Delivery Services, Analytics Services, Deployment & Management Services
Cloud Security: Basics: Security Threats and Issues, Encryption, Hashing, Digital Signature,
PKI, IAM, SSO, Privacy, Security Design Principle. (Industrial visit in a four-tier data center might be arranged.)

Course Outcomes:

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

Explain the core concepts of the cloud computing paradigm.
Apply fundamental concepts in cloud infrastructures to understand the tradeoffs in power, efficiency, and cost, and then study how to leverage.
Discuss system, network, and storage virtualization and outline their role in enabling the cloud computing system model.
Analyze various cloud programming models and apply them to solve problems on the cloud.

References:

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

MICE-5006 Digital Forensics

Credit Hour: 3

Course Objectives:

To provide an understanding of Computer forensics fundamentals.
To analyze various computer forensics technologies.
To provide computer forensics systems.
To identify methods for data recovery.
To apply the methods for the preservation of digital evidence.

Course Contents:

Digital Forensics: An overview, Forensics basic and criminalities.
Basics of Operating system and networking: A review, Forensic modeling and principles, Forensic duplication and analytics, File carving and testing, network surveillance, and accountability, network attach traceback and attribution.
Security Issues: Cyber forensics tools and testing, processing crime and incident scenes, mobile device forensics, multicast fingerprinting, multimedia forensics, Intrusion, and online frauds detection, Steganography;
Policy Guidelines: Cyberlaw, Security and Privacy policies; Court testimony and report writing skills; Digital Evidence control.

Course Outcomes:

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

Explain the origins of forensic science.
Explain the difference between scientific conclusions and legal decision-making.
Explain the role of digital forensics and the relationship of digital forensics to traditional forensic science.
Outline a range of situations where digital forensics may be applicable.
Identify and explain at least three current issues in the practice of digital forensic investigations.

References:

“The Basics of Digital Forensics: The Primer for Getting Started in Digital Forensics”, 1^st Edition, John Sammons
“Digital Forensics with Open Source Tools”, 1^st Edition, Cory Altheide Harlan Carvey
“Digital Forensics for Legal Professionals”, 1^st Edition, Larry Daniel, Lars Daniel

MICE-5007 Algorithm and Optimization

Credit Hour: 3

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 Contents:

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, 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.

Course Outcomes:

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

Apply optimization methods to engineering problems including developing a model.
Apply optimization methods,
Explore the solution and interpret the results.
Develop the ability to choose and justify optimization techniques that are appropriate for solving real engineering problems.

References:

“Combinatorial Optimization: Algorithms and Complexity”, Christos H. Papadimitriou.
“Graphs, Algorithms, and Optimization”, Donald L. Kreher and William Lawrence Kocay.
“Optimization Algorithms and Applications”, Rajesh Kumar Aurora

MICE-5008 Graph Theory and its Application

Credit Hour: 3

Course Objectives:

To cover a variety of different problems in Graph Theory.
To learn several theorems and proofs where theorems will be stated and proved formally using various techniques.
To learn various graphs algorithms along with their analysis.

Course Contents:

Introduction to Graphs: Definition of a graph and directed graph, simple graph. Degree of a vertex, regular graph, bipartite graphs, subgraphs, complete graph, the complement of a graph, operations of graphs, isomorphism and homomorphism between two graphs, directed graphs, and relation.
Paths and Circuits: Walks, paths and circuits, the connectedness of a graph, Disconnected graphs, and their components, Konigsberg 7-bridge problem, Around the world problem, Euler graphs, Hamiltonian paths and circuits, Existence theorem for Eulerian and Hamiltonian graphs.
Trees and Fundamental circuits: Trees and their properties, distance and center in a tree and a graph, rooted and binary trees, spanning trees and forest, fundamental circuits, cut sets, connectivity and separability,1-isomorphism, 2-isomorphism, breadth-first, and depth-first search.
Matrix representation of graphs: Incidence matrix and its sub-matrices, Reduced incidence matrix, circuit matrix, fundamental circuit matrix, cut set matrix, fundamental cut set matrix, path matrix, the adjacency matrix of a graph, and a digraph.
Planar and Dual graph: Planar graphs, Euler’s formula, Kuratowski’s graphs, detections of planarity, geometric dual, combinatorial dual.
Coloring of planar graphs: Chromatic number, independent set of vertices, maximal independent set, chromatic partitioning, dominating set, minimal dominating set, chromatic polynomial, coloring, and four-color problem, coverings, matchings in a graph.
Graph Algorithms: Network flows, Ford-Fulkerson algorithm, Dijkstra algorithm for the shortest path between two vertices, Kruskal and Prim’s algorithms for minimum spanning tree.

Course Outcomes:

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

have a strong background of graph theory which has diverse applications in the areas of computer science, biology, chemistry, physics, sociology, and engineering.
Apply the theories in real world applications.
Select the appropriate algorithm for solving graph problems.

References:

“Introduction to Graph Theory”, Douglas B West
“Graph Theory”, Balakrishnan (Schaum)
“A First Course in Graph Theory (Dover Books on Mathematics)”, Gary Chartrand

MICE-5009 Ethical Hacking and Intrusion Management

Credit Hour: 3

Course Objectives:

The course combines an ethical hacking methodology with the hands-on application of security tools to better help students secure their systems.
Students are introduced to common countermeasures that effectively reduce and/or mitigate attacks.
Students will know about intrusion management system.

Course Contents:

Ethical Hacking: Introduction to Hacking; Linux Basics; Information Gathering Techniques; Target Enumeration and Port Scanning techniques; Vulnerability Assessment; Network Sniffing; Remote Exploitation; Client-Side Exploitation; Post exploitation; Windows Exploit Development Basics; Wireless Hacking; Web Hacking.
Intrusion Management: Attack Framework; Introduction to IDS and IPS; Principles of IDS; IDS Architecture; Understanding TCP IP for IDS; Microsoft Internet Acceleration and Security Server 2004 (ISA Server 2004); Testing and ISA Server Installation; TCP Dump; Snort.

Course Outcomes:

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

Describe the concepts of ethical hacking
Explain the stages of a cyber attack
Scan and enumerate a network and a computer system
Execute basic attacks against network and computer systems

References:

“Ethical Hacking and Penetration Testing Guide”, Rafay Baloch.
Intrusion Alert: An Ethical Hacking Guide to Intrusion Detection”, Ankit Fadia & Manu Zacharia.
“The Basics of Hacking and Penetration Testing - Ethical Hacking and Penetration Testing Made Easy”, Patrick Engebretson

MICE-5010 Recent Trends in Information & Communication Engineering

Credit Hour: 3

Course Objectives:

To teach any recent course relevant to the ICE field which is not in the offered list of the syllabus.

Course Contents:

Contents will be added according to the teaching materials.

This course might address the latest 4G and 5G-related topics and beyond.

MICE-5011 Advanced Digital Signal Processing

Credit Hour: 3

Course Objectives:

To find out spectral estimation of random processes.
To find out parametric techniques for power spectrum estimation.
To develop knowledge on Adaptive filtering along with LMS and RLS algorithms.
To study various filter banks.

Course Contents:

Spectral estimation of random processes: Classical methods, model based high resolution methods, super resolution techniques, spectral estimation in noisy condition, applications: estimation of sinusoids in noise, speech enhancement, quantitative tissue characterization, ECG/PPG signal analysis, Review of parametric techniques for power spectrum estimation, high-resolution methods.
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.
Multi-rate signal processing: Filter banks: cosine modulated filter banks, para unitary QMF banks, multidimensional filter banks, emerging applications of multi-rate signal processing, Wavelets.

Course Outcomes:

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

1. Design frequency domain adaptive filter.
2. Learn about spectral estimation of random processes.
3. To know about applications of multi-rate signal processing.

References:

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

MICE-5012 Optical Waveguide Theory

Credit Hours: 3

Course Objectives:

Explain the principles of optical waveguide characteristics.
Analyze and design optical communication systems.
Locate, read, and discuss current technical literature dealing with optical fiber waveguides.
Network management and access networks for optical waveguide.
Dealing with various photonic switches.

Course Contents:

Types of optical waveguides: optical integrated circuits and guiding structures.
Basics of optical waveguide analysis: basic equations for light waves, the polarization of light, reflection and refraction, wave equations. Guided radiation modes in dielectric slab waveguides. Coupled mode theory.
Analytical solution for optical waveguides: WKB method, Marcatili's method, effective index method, equivalent network method. Computer-aided design of integrated optical waveguide devices. Application of photonics to microwave devices. Non-linear optical waveguides.

Course Outcomes:

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

Classify the Optical sources and detectors and discuss their principle.
Familiar with Design considerations of optical waveguide systems.
To get an understanding of the physical properties of optical networks.
To get an understanding of optical components and optical node design.

References:

“Modern optical Engineering the Design of Optical Sys.”, J. Smith; SPIE Press McGraw-Hill.
“Optical Networks –A practical3.perspective”, Rajiv Ramaswamy, Kumar N. Sivaranjan and Galen H. Sasaki,3rdedition, Elsevier, 2010.
“Optical Networks –Third generation transport systems”, Uyless Black, 1st Edition, Pearson, 2002.
“Optical Fiber Communications – Principles and Practice”, John M. Senior, Pearson Education, 2009

MICE-5013 Advanced Telecommunication Engineering

Credit Hour: 3

Course Objectives:

This course is designed to help the students to understand advanced concepts in telecommunication systems and networks, analyze modern telecommunication technologies, protocols, and standards, study emerging trends and innovations in the telecommunication sector and to develop skills to design, optimize, and troubleshoot telecommunication networks.

Course Contents:

1. Introduction to Advanced Telecommunication Systems: Overview of telecommunications: Evolution and advancements, Basic network infrastructure, protocols, and technologies, Current trends and future directions in telecommunication engineering.
2. Wireless Communication Systems: Cellular networks (GSM, LTE, 5G), Frequency spectrum and bandwidth management, Wireless network protocols and standards (IEEE 802.11, WiMAX, Bluetooth).
3. Modulation and Coding Techniques: Advanced digital modulation techniques (QPSK, QAM), Error detection and correction: Block codes, convolutional codes, and Turbo codes, Trade-offs between bandwidth, power, and performance.
4. Multiple Access Techniques: Frequency Division Multiple Access (FDMA), Time Division Multiple Access (TDMA), Code Division Multiple Access (CDMA) and Orthogonal Frequency Division Multiple Access (OFDMA), Comparison and application of multiple access techniques in modern systems.
5. Antenna Theory and Design: Antenna fundamentals: Gain, polarization, and radiation patterns, Advanced antenna design for telecommunications, MIMO (Multiple Input Multiple Output) and beamforming technologies.
6. Satellite Communication Systems: Components of satellite systems: Earth stations, transponders, and satellites, Link budget analysis and satellite orbits, Applications of satellite communications in telephony, broadcasting, and internet services, Study on BS-1. (implementation, orbital location, coverage etc. )
7. Optical Communication Systems: Fundamentals of fiber optics and light propagation, Components of optical networks: Transmitters, receivers, and amplifiers, Coarse Wavelength Division Multiplexing (CWDM) Network Design, Dense Wavelength Division Multiplexing (DWDM) Network design, Study on NTTN networks of Bangladesh.
8. Network Architectures and Protocols: OSI and TCP/IP models: Revisited with advanced concepts, MPLS (Multiprotocol Label Switching) and VPNs (Virtual Private Networks), Core vs. Access Networks and Network Virtualization techniques.
9. Telecommunication Traffic Engineering: Traffic models: Erlang formulas and queuing theory, Congestion management and Quality of Service (QoS) , Performance analysis and capacity planning in telecom networks.
10. Telecommunication Regulations and Standards: Overview of telecommunication regulatory bodies (ITU, FCC) , Spectrum allocation and licensing, International standards for telecom networks and services (3GPP, IETF).
11. Voice over IP (VoIP) and IP Telephony: VoIP principles, protocols (SIP, RTP), and codecs, QoS considerations for voice traffic, Challenges in implementing large-scale IP telephony networks.
12. 5G and Beyond: Fundamentals of 5G architecture: mmWave, small cells, and massive MIMO, 5G core network and virtualization concepts, Future trends: 6G and edge computing in telecom.
13. Internet of Things (IoT) and Telecommunication: Role of telecom networks in IoT ecosystems, IoT protocols: MQTT, CoAP, and cellular IoT (NB-IoT, LTE-M) , Network management and security challenges in IoT.
14. Network Security in Telecommunication: Telecommunication network vulnerabilities, Cryptography and encryption techniques for secure communications, Emerging security challenges in 5G networks.
15. Case Studies and Practical Applications: Case study: Deployment of a nationwide cellular network, Case study: Design and optimization of a fiber-optic backbone, Analysis of recent telecommunication infrastructure projects and trends in Bangladesh.

Course Outcomes:

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

Analyze the characteristics of the telephone systems
Define and distinguish digital and analog transmissions
Evaluate the digital services over analog carrier
Analyze the processes used in telecommunications
Make use of the parameters in designing telephone switches

References:

1. Wireless Communications: Principles and Practice_ by Theodore S. Rappaport.
2. Optical Fiber Communications_ by Gerd Keiser.
3. Data and Computer Communications_ by William Stallings.
4. Computer Networking: A Top-Down Approach_ by James F. Kurose and Keith W. Ross

MICE-5014 Radio Frequency Technology

Credit Hour: 3

Course Objectives:

Calculate noise (amplitude and phase), linearity, and dynamic range performance metrics for RF devices and circuits.
Discuss transceiver architectures relevant to current wireless communications standards and their relative advantages and disadvantages.
Discuss active and passive device technologies relevant to RFICs and their relative performance advantages and disadvantages.
Design IC implementations of RF functional blocks (such as low-noise amplifiers, mixers, and oscillators) based on foundry models and design rules to meet specifications for a wireless communications system.

Course Contents:

Antennas: Launching of waves, transmission, the definition of antennas, reciprocity, wave propagation,
Principal of equivalent sources: electric and magnetic surface current, uniqueness principle, Huygens principle, Hertzian vector, image theory.
Aperture antennas: rectangular apertures, horn antenna, corrugated horn, circular aperture, reflector, and lens antennas.
Linear antennas: Field calculation, current distribution, linear dipoles and monopoles, design and feeding of dipole antennas, electrically short antennas, elementary dipole, receiving antennas.
Group antennas: Directivity, group factor, phased arrays, parasitic antennas.
Electronic noise: Characteristics of noise voltages and currents, calculations with noise: Fourier analysis, correlation, superposition of noise quantities, transmission through linear networks, the noise of 2-port networks: noise factor and temperature, noise matching, concatenation of noisy 2-port-networks; RF amplification:2-terminal amplifiers, 2-port amplifiers: design with scattering parameters, selection of the point of operation, stability, unilateral design, wide-band amplifiers.
Frequency Spectrum: 4G and 5G frequency bands, frequency management, applications.

Course Outcomes:

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

Analyze an RF system using a link budget, accounting for characteristics of the antenna, transmitter, receiver, and propagation.
Design impedance matching circuits suitable for RF.
Analyze a linear small-signal amplifier using s-parameter concepts to determine gain and stability.
Describe RF amplification and its applications, advantages, and disadvantages.

References:

“Antenna Theory Analysis and Design”, Balanis A., John Wiley &Sons, New York,1982.
“Smart Antennas for Wireless Communications: IS95 and third-generation CDMA Applications”, Joseph C. Liberti, Theodore S. Rappaport, Prentice Hall, Communications Engineering and Emerging Technologies Series.
“An Introduction to Radio Frequency Engineering Reissue Edition”, Christopher Coleman.
“Radio Frequency Integrated Circuits and Technologies”, Ellinger, Frank

MICE-5015 Advanced Optical Communication

Credit Hour: 3

Course objective:

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

Course content:

Fiber-optic communication systems: Ray theory transmission in optical fiber, Electromagnetic mode theory for optical propagation, Modes in a planar guide, phase shift and Evanescent field, Goos-Haenchen Shift, Signal distortion and attenuation, Kerr nonlinearity, self-phase and cross-phase modulation, dispersion flattened, and dispersion compensated fibers, profile dispersion, polarization mode dispersion (PMD).
Optical Sources & Detectors: LEDs, semiconductor lasers, constructions, and their characteristics, optical confinement and carrier confinement, transmitter design, Photodetectors, and their characteristics, PIN and APD photodetectors, receiver’s structures, sensitivity, Noise analysis in photodetectors.
Optical Amplifiers: Semiconductor laser amplifiers, Raman and Brillouin fiber amplifier, EDFAs, optical couplers, Mach-Zehnder interferometer, optical add/drop multiplexers, isolators, circulators, optical filters, diffraction grating, and switches.
Design issues: Transmitter circuit, LED drive circuits, laser drive circuits, optical receiver circuit: pre-amplifier and AGC, Equalizations, Digital system design considerations: regenerative repeater, optical transmitter, an optical receiver, temporal losses, Optical power budgeting, analog system planning.
Optical components: Couplers, isolators and circulators, multiplexers, and filters.
Optical Networking: Generations of optical networks, SONET and SDH- integration of TDM signals, framing, transport overhead, network element and topologies, Broadcast and select network- topologies, single hop, multi-hop, media access control protocols, routing and wavelength assignment, High capacity networks- SDM, TDM, WDM and DWDM approaches, optical transport, access and premise networks.

Course outcomes:

Define basic terminology and concepts and take the lead in fiber optic discussions.
Compare and contrast the features, functions, benefits, and challenges of fiber optic communications with other wireline and wireless solutions.
Match communication requirements with practical fiber optic systems.
Specify optical fibers, cables, connectors, splices, and other transmission equipment.
Monitor fiber optics evolution to higher performance and greater market penetration.

References:

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

MICE-5016 Satellite Communication

Credit Hour: 3

Course Objectives:

Understand how mission dictates orbit.
Understand link budget equations to provide a sufficient margin for performance.
Examine concepts of satellite networking.
Take a practical look at the engineering impact of the various satellite components on performance.

Course Contents:

Introduction, satellite classification, solution of the space segment, evolution of the ground segment, very large aperture terminal, large and medium-size antennas, small antennas, international telecommunication satellite, non-parabolic satellite antennas, voice-data-video applications, characteristics of satellite networks, Satellite repeaters, satellite earth station, satellite link analysis, link design,

Access technique for satellite communication: SCPC, MCPC, SPADE, etc. Spread spectrum technique in Satellite networks, Multi-beam Satellite, Inter-Satellite link (ISL), Interference in satellite link, Satellite on-board switching techniques, optical ISL. VSAT technologies, elements of VSAT networks, regulatory issues, benefits of VSATs, applications of VSATs, VSAT network configurations, protocols and interfaces, Mobile satellite system: IRID/VM, INMARSAT, ODESSEY, etc. Digital Video Broadcasting (DVB), Digital Audio Broadcasting.

Course Outcomes:

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

Able to obtain different types of satellites
Ability to calculate the orbital determination and launching methods
Ability to develop commands, monitor power systems, and development of antennas.
Able to design Satellite for real-time applications.

References:

“Digital Satellite Communications”, Tri T. Ha; McGraw-Hill International.
“Satellite Communication Mobile & Fixed Services”, Michael J. Miler; Kluwer Academic Publisher.
Satellite Communications - T. Pratt, C. Bostian, J. Allnut; John Wiley & Sons Inc.
“Mobile Communication satellites theory and application”, Ton Logadon; McGraw-Hill International.

MICE-5017 Radar Engineering

Credit Hour: 3

Course objectives:

1.This course covers the fundamental concepts needed to understand the design and operation of radar systems for a variety of applications.
Topics covered include the radar range equation, signal-to-noise ratio, system losses, radar cross section, range and velocity ambiguity, radar clutter and jamming, detection and receiver design, transmitters and antenna systems.
Applications surveyed include pulsed, CW, and FM radars, Doppler radars, MTI radars, tracking radars, Phased Array radars, LPI radars, and stealth radars etc.

Course content:

Introduction to radar, radar terminology, radar bands, functional block diagram and operation: radar subsystems and components, radar range equation, pulse repetition frequency and range ambiguity, radar cross section, distributed targets, propagation, information contents in radar signals, noise and SNR, system losses, clutter and jamming, detection and tracking, sea and land clutter models, radar antennas and parameters, radiation pattern and aperture distribution, radar transmitters and receivers, displays and duplexers.

CW and FM radar principles, effect of phase and amplitude errors, airborne doppler navigation; Doppler and MTI radar, delay-line cancellers, Synthetic Aperture Radar: principles, SAR processing, autofocus, spotlight mode, airborne and spaceborne systems and applications, interferometry, ISAR; Tracking radar: conical-scan radar, monopulse tracking radar, track-while-scan, Kalman filters; Avionics and radionavigation: Air Traffic Control, primary and secondary radar, Phased array radar: phased array principles, array signal processing, multifunction radar, scheduling; LPI radar; Stealth radar, stealth and counter-stealth: stealth techniques for aircraft and other target types.

Labs:

Detection, identification, and classification of objects/targets using different radar systems.
Measurement of radiation pattern, aperture, and other parameters (gain, directivity) of different types of antennas.
Detection of fixed targets and moving targets using parabolic/patch antenna.

Course outcomes:

Understand the radar system and its operation.
Design simple radar systems and the associated signal processing, at block diagram level.
Apply appropriate mathematical and computer models relevant to radar systems to calculate system performance, and assess the limitations of particular cases, and how to overcome the limitations.
Understand the design of radar signals, and FM radar, MTI radar etc.
Understand the principles of Synthetic Aperture Radar, its use in geophysical remote sensing and surveillance applications, and the digital processing used to form SAR images.
Analyze the performance of simple tracking radar systems.
Understand the principles of radionavigation systems, stealth and counter-stealth techniques.

References:

Introduction to RADAR systems- M. I. Sholnik; McGraw-Hill International
Principle of Radar- Tomay; Prentice Hall of India
Radar design, principles, signal processing and the environment- Fred E Nathanson, Prentice Hall of India Private Ltd

MICE-5018: Geographic Information System (GIS) Technology

Credit Hour: 3

GIS technology is a powerful tool that has revolutionized the way we manage and analyze geographic data. Its importance spans across various industries, including urban planning, environmental management, public health, and business operations. By enabling more informed decision-making, resource optimization, and risk mitigation, GIS technology plays a crucial role in enhancing operational efficiency and driving sustainable growth. As GIS technology continues to evolve, its potential applications and benefits will only expand, further shaping the future of industries and society.

Course Objectives:

To understand how earth surface mapping works
To learn geo-spatial services using GIS technology
To learn location-based services (LBS)
To learn map-based data visualization techniques
To learn the GPS and map-based navigation process in modern time
Practice GIS programming using open-source technologies, etc.

Course Contents:

1. Introduction to geographic coordinate system (WGS 1984) & OGC

Recap the basic geometric shapes, coordinate geometry, spherical geometry, geographic coordinate system, the World Geodetic System 1984 (WGS84) and the use of longitudes and latitudes, understanding the use of Haversine formula.

2. Understanding Vector, Raster GIS & GDAL Utility

Installation of PostGIS and GDAL & solving challenges.

Difference of PostGIS and GDAL, use of GDAL for transformation of geometry data between data file of various formats and PostGIS database.

3. Overview of SQL and PostgreSQL

Learning the SELECT, INSERT, UPDATE, DELETE statements, UNION & MINUS operation, sub-queries & joins.

4. Overview of SQL and PostgreSQL

Practicing complex queries using case studies.

5. Introduction to PostGIS

Learning the syntax of Point, Linestring, Polygon and their multi-dimensional variants;

Understanding the role of table index in data and binary geometries

6. Uses of Point and MultiPoint Objects

Using PostGIS functions: ST_Distance

7. Uses of Linestring & MultiLinestring Objects

Using PostGIS functions: ST_Length, ST_ShortestLine, ST_LineSubstring, ST_MakeLine

8. Uses of Polygon and MultiPolygon Objects

Using the polygon functions: ST_AsText, ST_GeomFromText, ST_AsGeoJSON,

ST_Area, ST_Intersection, ST_Intersects, ST_Centroid, ST_Covers, ST_Perimeter,

ST_Union, ST_Polygonize

9. Understanding the Road Network & pgRouting

Road network and the concept of routing like Google Maps & Uber app. Understanding the Dijkstra's Algorithm.

10. Determining of the Shortest Route

Learning pgRouting functions: pgr_createTopology, pgr_nodeNetwork, pgr_analyzeGraph, pgr_analyzeOneWay;

Learning how to use pgr_dijkstra to determine the shortest path.

11. Visualization of the Shortest Route on Map

JavaScript, Leaflet library, use cases of Leaflet, QGIS – all open-source products.

12. Introduction to Raster

Understanding PostGIS raster technology, raster2pgsql utility, viewing rasters in the web browser.

13. Uses of Raster GIS

Understanding raster functions: ST_Union, ST_Polygon, ST_Transform, ST_SummaryStatsAgg, ST_SummaryStats, ST_Histogram;

creating rasters from geometries, converting rasters to geometries, creating derivative rasters, coloring your rasters with ST_ColorMap.

Course Outcomes:

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

1. Understand how GIS works and how they can use it to solve spatial problems

2. Design GIS-based systems.

References: PostGIS user manual

General Info

Intake: Once in a Year
Admission Duration: 17 August - 21 August 2025
Class Start: 24 August 2025
Method of Application: Offline
Course Duration: 1.5 (one and half) years, 3 (three) 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. 65,100.00 & M. Engineering - TK. 65,100.00 which may be re-fixed by the authority.

Eligibility for Admission

For admission to the program leading to a Masters in Information and Communication Engineering (MICE), an applicant must have,

A minimum GPA of 4.50 out of 5.00 or a first division or equivalent in any one of SSC and HSC or 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.

Selection Process

For Regular Students of Department of ICT, BUP

The students of Department of ICT, FST, BUP will be selected for admission in MICE, BUP without giving any admission test.

For Students of Other Universities

MICE6000 | Project

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICE5105 | Research Methodology

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICE5104 | Advanced Networking

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICE5103 | Big Data Analytics and Design

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICE5102 | Information and Cyber Security

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICE5101 | Advanced Machine Learning

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICE5010 | Ethical Hacking and Intrusion Management

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICE5018 | Satellite Communication

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. These include 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

At the end of this course, students will be able to: 1. Able to obtain different types of satellites 2. Ability to calculate the orbital determination and launching method. 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

MICE5008 | Algorithm and Optimization

Objectives

Through the study of this course, students will gain a comprehensive understanding on the concepts of different algorithms. Students will be able to-  Analyze the asymptotic performance of algorithms.  Write rigorous correctness proofs for algorithms.  Demonstrate a familiarity with major algorithms and data structures.  Apply important algorithmic design paradigms and methods of analysis.  Synthesize efficient algorithms in common engineering design situations.

Outcomes

At the end of this course, students will be able to:  Analyze worst-case running times of algorithms using asymptotic analysis.  Apply optimization methods to engineering problems including developing a model.  Define the optimization problems.  Describe the greedy algorithm, its technique, analysis and utilization.  Describe the dynamic-programming paradigm and explain when an algorithmic design situation calls for it. Recite algorithms that employ this paradigm. Synthesize dynamic-programming algorithms, and analyze them.  Apply optimization methods,  Explore the solution and interpret the results.  Develop the ability to choose and justify optimization techniques that are appropriate for  solving realistic engineering problems

References

 “Combinatorial Optimization: Algorithms and Complexity”, Christos H. Papadimitriou.  “Graphs, Algorithms, and Optimization”, Donald L. Kreher and William Lawrence Kocay.  “Optimization Algorithms and Applications”, Rajesh Kumar Aurora  Introductions to Algorithms- Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein,Prentice-Hall.  Algorithms + Data Structures= Programs, Wirth N, Prentice Hall  Adam Drozdek, Data Structures and Algorithms in C++, Thomson Brooks/cole - Vikas Pub. House pvt.Ltd.

MICE5001 | Advanced Operating System

Objectives

Through the study of this course, students will gain a comprehensive understanding on the concepts and functions of a modern operating system. Students will be able to-  To learn the fundamentals of Operating Systems.  To learn the mechanisms of OS to handle processes and threads and their communication  To learn the mechanisms involved in memory management in contemporary OS  To gain knowledge on distributed operating system concepts that includes architecture, mutual exclusion algorithms, deadlock detection algorithms and agreement protocols  Use OS as a resource manager that supports multiprogramming  Explain the low level implementation of CPU dispatch.  Explain the low level implementation of memory management.  Explain the performance trade-offs inherent in OS implementation

Outcomes

On successful completion of this course, students should be able to:  Describe, contrast and compare differing structures for operating systems.  Understand and analysis theory and implementation of: processes, resource control (concurrency etc.), physical and virtual memory, scheduling, I/O and files.  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.  Understand the Mutual exclusion, Deadlock detection and agreement protocols of distributed operating system.

References

1. “Operating System Concepts”, 9th edition, Avi Silberschatz, Peter Baer Galvin, Greg Gagne. (OSC) 2. “Modern Operating Systems”, 4th edition, Bos Tanenbum.(MOS)

MICE5102 | Information Security

Objectives

a) To provide a practical survey of both the principles and practice of cryptography as well as network and information security. b) To provide the state-of-the-art developments and initiatives in cyber security. c) Explore major security issues and trends in the study of cybercrime and computer related security.

Outcomes

After completing this course, students will be familiar with the fundamental concepts of information security, its different contexts, security measures and current state-of-the-art in this field.

References

1) Cryptography and network security principles and practice, William Stallings, Prentice Hall 2) Principles of Information Security, Michael E. Whitman and Herbert J. Mattord, Cengage Learning 3. Cryptography and network security, Behrouz A. Forouzan and Debdeep Mukhopadhyay, McGrawHill 4. Network Security: Private communication in a public world, Kaufman, C, Perlman, R and Speciner, M., Prentice Hall 5. Applied Cryptography, Schneier, B., John Wiley

MICE5104 | Internet of Things

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

MICE5016 | Industrial Automation and Control

Objectives

1. To provide the student with basic skills useful in identifying the concepts of automated machines and equipment and describe the terms and phrases associated with industrial automation. 2. Student can demonstrate competence in maintaining and troubleshooting technology includes identifying, understanding, and performing routine preventative maintenance and service on technology. 3. Detecting more serious problems; generating workable solutions to correct deviations; and recognizing when to get additional help.

Outcomes

At the end of this course, students will be able to: 1. Understand the overall automation system used in industries. 2. Acquire knowledge of different types of controlling system. 3. 3.Learn about Hydraulic Control System. 4. Design various control systems.

References

1. “Industrial Instrumentation, Control and Automation”, S. Mukhopadhyay, S. Sen and A. K. Deb, Jaico Publishing House, 2013. 2. “Chemical Process Control, An Introduction to Theory and Practice”, George Stephanopoulos, Prentice Hall India, 2012. 3. “Electric Motor Drives, Modelling, Analysis and Control”, R. Krishnan, Prentice Hall India, 2002. 4. “Hydraulic Control Systems”, Herbert E. Merritt, Wiley, 1991.

1st Semester

MICE5101 | Intelligent Systems

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.

Outcomes

1. Acquire a firm grasp of various search techniques and should be able to select an appropriate search technique and apply it in practice. 2. Learn to solve problems with planning and STRIPS programming. 3. Apply Fuzzy logic in real-life scenarios.

References

1. “Artificial Intelligence: A Modern Approach”, S.J. Russell and P. Norvig. 2. “Intelligent Systems: A Modern Approach”, Crina Grosan, Ajith Abraham 3. “Intelligent Systems for Engineers and Scientists”, Adrian A. Hopgood

MICE5102 | Cyber Security

Objectives

1. To gain a fundamental knowledge of what Cyber Security is and how it applies to your daily work. 2. To gain an understanding of terms commonly used in Cyber Security such as vulnerability. Page 32 of 52 3. To know how vulnerabilities, occur and how to limit your exposure to them. 4. To gain a fundamental understanding of what an attack/threats are, and how to identify and prevent them from occurring.

Outcomes

1. Possess a fundamental knowledge of Cyber Security. 2. Understand what a vulnerability is and how to address the most common vulnerabilities. 3. Know basic and fundamental risk management principles as it relates to Cyber Security. 4. Have the knowledge needed to practice safer computing and safeguard your information. 5. Critically evaluate and reflect on ethical issues that relate to the IT discipline.

References

1. “Information Security: The Complete Reference”, Rhodes-Ousley, Mark, 1st Edition. 2. “Information Security Management: Concepts and Practice”, New York, McGraw-Hill, 2013. 3. “Cyber security: A practitioner’s guide”, David Sutton. 4. “Cyber security and Cyber war: What Everyone Need to Know”, P.W. Singer, Allan Friedman, 1st Edition, ISBN-13: 978-0199918119. 5. “Cyber Security Basics: Protect your organization by applying the fundamentals”, Don Franke, 1st Edition.

MICE5104 | Advanced Internet of Things

Objectives

1. To understand the various physical phenomenon of different types of sensors and microsystems. 2. To design sensors with the appropriate electronic interface as a complete system. 3. To discuss various types of sensors like magnetic, optical, bio, chemical, radiation, electrical and mechanical, etc. 4. To emphasis 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. “Data Acquisition and Signal Processing for Smart Sensors”, N. V. Kirianaki, S. Y. Yurish, N., O. Shpak V. P. Deynega, John Wiley, 2004 2. “Protocols and Architectures for Wireless Sensor Networks”, H. Karl, A. Willig, John Wiley, 2005. 3. “Handbook of Sensor Networks: Compact Wireless and Wired Sensing Systems”, M.Ilyas, I. Mahgoub (ed.), CRC, 2004.

MICE5105 | Research Methodology

Objectives

1. To provide a basic understanding of research with a special focus on Business Research. 2. To equip the students how to identify a good “Research Problem”. 3. To provide hands-on experience on the key aspects of research. 4. To guide the students on writing their research reports.

Outcomes

1. Understand how research contributes to business success. 2. Know how to define business research. 3. Know when business research should and should not be conducted. 4. Understand how research activities can be used to address business decisions. 5. List the major phases of the research process and the steps within each.

References

1. Zikmund, W. G., Babin, B. J., Carr, J. C., & Griffin, M. (2013). Business research methods. Cengage Learning. 2. C. R. Kothari (1996). Research Methodology- Methods and Techniques. Wishaw Prokashan, New Delhi, Wiley Eastern Limited. 3. Ranjit Kumar (2005). Research Methodology- A step by step guide for beginners, 3rd Ed. Singapore, Pearson Education. 4. M. Nurul Islam (2014). An introduction to Research Methods, 3rd Edition, Mollick & Brothers, Dhaka.

MICE5103 | Advanced Digital Signal Processing

Objectives

1. To develop knowledge on Adaptive filtering along with LMS and RLS algorithms. 2. To find out parametric techniques for power spectrum estimation. 3. To study various filter banks.

Outcomes

1. Design frequency domain adaptive filter. 2. Learn about power spectrum estimation. 3. know about applications of multi-rate 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.

2nd Semester

MICE5002 | Advanced Machine Learning

Objectives

The course covers the principles, design, and implementation of learning programs that improve their performance on some set of tasks with experience.

Outcomes

1. Develop an appreciation for what is involved in learning from data. 2. Understand a wide variety of learning algorithms. 3. Understand how to apply a variety of learning algorithms to data. 4. Understand how to evaluate learning algorithms and model selection.

References

1. “Machine Learning”, Tom M. Mitchell 2. “Machine Learning”, John Paul Mueller, Luca Massaron

MICE5019 | Advanced Networking

Objectives

1. To provide an overview of advanced communication network functions and a good foundation for further studies in the subject. 2. To provide instruction in advanced data communication and computer networks through lectures, tutorials.

Outcomes

1. Understand and be able to explain the principles of a layered protocol architecture. 2. Understand, explain and calculate digital transmission over different types of communication media. 3. Understand, explain and solve mathematical problems for datalink and network protocols. 4. Describe the principles of access control to shared media and perform performance calculations.

References

1. “Data Communication & Networking”, Behrouza Forouzan- McGraw Hill Education. 2. “Computer Network”, Tannenbaum, Pearson Education. 3. “Computer Networks: Protocols, Standards, and Interfaces”, Uyless Black, PHI. 4. “Computer Networks a System Approach”, Larry L. Peterson and Bruce S. Davie, MK Education. 5. “Internetworking with TCP/IP: Principles, Protocols, Architecture”, D. E. Comer – PHI.

MICE5202 | Advanced Telecommunication Engineering

Objectives

1. Understanding the advanced concepts and structure of telecommunications networks for narrowband and broadband services. 2. Showing the advanced principles of modern telecommunication. 3. Understanding the advanced settings in the operation of telecommunications systems and devices.

Outcomes

1. Analyze the characteristics of the telephone systems 2. Define and distinguish digital and analog transmissions 3. Evaluate the digital services over analog carrier 4. Analyze the processes used in telecommunications 5. Make use of the parameters in designing telephone switches

References

1. “Digital Switching Systems”, Syed R. Ali, McGraw Hill international. 2. “Digital Telephony”, John Bellamy- John Wiley & Sons, Inc. 3. “Telecommunication Switching Systems and Networks”, Thiagarajan Viswanathan- Prentice Hall of India. 4. “Telephones and Telegraphy”, S.F. Smith, Oxford University Press.

MICE5201 | Big Data Analytics and Design

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. Apply analytics on Structured, Unstructured Data. 5. 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 predictive and prescriptive modeling to support business decision-making. 4. Students will demonstrate the ability to translate data into clear, actionable insights.

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.

MICE5203 | Recent Trends in Information & Communication Engineering

Objectives

1. To teach any recent course relevant to the ICE field which is not in the offered list of the syllabus.

Outcomes

To Know new programming environment
To grow research capabilities

References

Book

3rd Semester

MICE6000 | Thesis

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICE5015 | Radio Frequency Technology

Objectives

1. Calculate noise (amplitude and phase), linearity, and dynamic range performance metrics for RF devices and circuits. 2. Discuss transceiver architectures relevant to current wireless communications standards and their relative advantages and disadvantages. 3. Discuss active and passive device technologies relevant to RFICs and their relative performance advantages and disadvantages. 4. Design IC implementations of RF functional blocks (such as low-noise amplifiers, mixers, and oscillators) based on foundry models and design rules to meet specifications for a wireless communications system.

Outcomes

1. Analyze an RF system using a link budget, accounting for characteristics of the antenna, transmitter, receiver, and propagation. 2. Design impedance matching circuits suitable for RF. 3. Analyze a linear small-signal amplifier using s-parameter concepts to determine gain and stability. 4. Describe RF amplification and its applications, advantages, and disadvantages.

References

1. “Antenna Theory Analysis and Design”, Balanis A., John Wiley &Sons, New York,1982. 2. “Smart Antennas for Wireless Communications: IS95 and third-generation CDMA Applications”, Joseph C. Liberti, Theodore S. Rappaport, Prentice Hall, Communications Engineering and Emerging Technologies Series. 3. “An Introduction to Radio Frequency Engineering Reissue Edition”, Christopher Coleman. 4. “Radio Frequency Integrated Circuits and Technologies”, Ellinger, Frank

MICE6100 | Project

Objectives

No objective found!

Outcomes

No outcome found!

References

No reference found!

MICE5007 | Advanced Software Engineering

Objectives

1. To develop a broad understanding of the discipline of advanced software engineering. 2. To learn about requirements management techniques. 3. To acquire the skill of software project management. 4. To learn the techniques of quality assurance. 5. To examine the concepts and techniques associated with several advanced and industrially relevant topics, relating to both the product and processes of software engineering.

Outcomes

1. Describe the knowledge and skills necessary to practice software engineering, and the professional issues that a software engineer might face. 2. Create major activities and key deliverables in software development. 3. Use project management concepts to manage projects, people, and products. 4. Use software engineering concepts to construct quality software systems.

References

1. “Software Engineering: A Practitioner's Approach”, 7th edition, Roger S. Pressman. 2. “Pattern-Oriented Software Architecture”, Volume 1, F. Buschmann, R. Meunier, H. Rohnert, P. Sommerlad, M. Stal. 3. “Software Engineering”, 10th edition, Ian Sommerville. 4. “Software Engineering: Principles and Practice”, 3rd edition, Hans van Vliet.

About BUP

Administration

Regulatory Bodies

Academic Personnels

Masters in Information and Communication Engineering

Faculty: Faculty of Science & Technology (FST)

Department: Department of Information and Communication Technology

Program: Masters in Information and Communication Engineering

Course Outline

6.8 Course Designation System