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Masters in Information and Communication Technology (MICT)

  • Outline
  • Admission Criteria
  • General Guideline
  • Course List

Faculty: Faculty of Science & Technology (FST)

Department: Department of Information and Communication Technology

Program: Masters in Information and Communication Technology (MICT)

Objective

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

Mission

The mission of the MICT is to prepare students for employment in various ICT related areas and for this pursuit of advanced degrees in ICT or information related professional institutions by educating them in fundamental concepts, knowledge, laboratory, field technologies and skills of this communication sciences and engineering.

Vision

BUP seeks to become national leader at the graduate levels among public universities in the fields of Communication and Information Engineering to be a world-class center of excellence in training, research and innovation in cutting edge technologies reflected in historic and contemporary worldview.

General Info 

  • Intake: Once in a Year
  • Application Duration: 24 September - 26 October 2023
  • Written Test and Viva Voce: 24 November 2023 (0930 hrs -1730 hrs)
  • Class Start: 19 January 2024
  • Method of Application: Online
  • Course Duration: 2 (two) years, 4 (four) semesters
  • Total Credit Hours: M. Sc. Engineering (Theory: 18 Cr. + Thesis: 18 Cr.) &  M. Engineering (Theory: 30 Cr. + Project: 6 Cr.)
  • Total Course Fee : M. Sc. Engineering - TK. 1,63,270.00 & M. Engineering - TK. 1,48,270.00 which may be re-fixed by the authority. 

Eligibility for Admission

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

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

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

Admission Test Syllabus 

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

Exam Type 

  •  MCQ (1 Hour)

Weightage 

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

Contact Information 

  •  Program Co-Coordinator, MICT , Dept. of ICT, FST, BUP, Phone- 01769021830, 01769021816 (09am-04pm), Email: mict@bup.edu.bd 

Others Information 

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

 

 

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Objectives

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

Outcomes

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

References

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

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

Outcomes

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

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  • Book

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

Outcomes

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

References

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

Objectives

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

Outcomes

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

References

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

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Objectives

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

Outcomes

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

References

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

Objectives

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

Outcomes

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

References

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

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Objectives

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

Outcomes

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

References

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

Objectives

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

Outcomes

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

References

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

Objectives

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

Outcomes

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

References

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

Objectives

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

Outcomes

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

References

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

Objectives

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

Outcomes

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

References

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

Objectives

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

Outcomes

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

References

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

Objectives

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

Outcomes

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

References

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

Objectives

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

Outcomes

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

References

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

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1st Semester

Objectives

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

Outcomes

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

References

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

Objectives

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

Outcomes

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

References

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

Objectives

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

Outcomes

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

References

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

2nd Semester

Objectives

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

Outcomes

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

References

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

Objectives

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

Outcomes

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

References

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

Objectives

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

Outcomes

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

References

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

Objectives

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

Outcomes

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

References

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

3rd Semester

Objectives

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

Outcomes

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

References

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

Objectives

  • No objective found!

Outcomes

  • No outcome found!

References

  • No reference found!

Objectives

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

Outcomes

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

References

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

4th Semester

Objectives

  • No objective found!

Outcomes

  • No outcome found!

References

  • No reference found!

Objectives

  • No objective found!

Outcomes

  • No outcome found!

References

  • No reference found!