DCS
Department of Computer Science

Course Structure

  1. PREAMBLE

The proposed M.Sc. (Computer Science) programme (two years), M.Tech. (Computer Science) programme (two years), and integrated M.Sc. + M.Tech. (Computer Science) programme (three years) have been designed to keep pace with the rapid developments in field of Computer Science and to cater the requirements of the SARRAC countries as well as the aspirations of students. The integrated programme is flexible with multiple entry and exit options for the students, as shown in Figure 1, to cater diverse academic structures across the SAARC countries. The proposed integrated M.Sc. + M.Tech. (Computer Science) programme is one of the unique curricula offered by some of the universities in the SAARC region. The salient features of the aforesaid programmes are outlined below: 

  1. The students with three years of bachelor’s degree are eligible to apply either for two years M.Sc. (Computer Science) programme or three years integrated M.Sc. + M.Tech. (Computer Science) programme.

     

  2. The students with four years bachelor’s degree are eligible to apply for two years M.Tech. (Computer Science) programme.

  1. The students entering into the integrated programme will have an option to exit the programme with M.Sc. (Computer Science) degree after two years; or, they can opt to continue with one more year and exit with integrated M.Sc.+ M.Tech. (Computer Science) degree.

  1. At most 5 students of M.Sc. (Computer Science) programme satisfying minimum CGPA criteria decided by the department will be offered an option to switch to integrated M.Sc.+M.Tech. (Computer Science) programme in the beginning of second year.

  1. The students may complete the programme without any specialization, or they can opt any of the two specializations viz. Artificial Intelligence & Machine Learning and Advanced Networks & Systems. For specialization, besides studying the specialized courses, the students will have to do their projects/dissertations in the area of specialization.

  1. Admission to M.Tech. programme is either through merit list based on GATE (conducted by IITs) scores or merit list based on marks in SAU entrance examination.

  1. Admission to M.Sc. programme and integrated M.Sc. + M.Tech. programme is through SAU entrance examination. There is a common application form for M.Sc. and integrated M.Sc. + M.Tech. programmes. The students can provide their preferences for both the programmes in the application form. There is the same question paper in the entrance examination for both the programmes. Separate merit lists will be prepared for both programmes based on the students preferences and the marks obtained in SAU entrance examination. In case a seat becomes vacant after withdrawal of admission by a student, the next student will be automatically switched from one programme to another based on the preference given by student in the application form and marks in the entrance examination, and/or next student from the waiting list will be offered admission.

                                                 

  1. The grade requirement for promotion to next semester as well as for the award of the degree, repetition of a course, extra semester to clear backlog etc. are as per university regulations/byelaws.

SUMMARY OF THE PROGRAMMES

Name of the programme

Duration

Number of seats

M. Sc. (Computer Science)

2 years (4 semesters)

20

M. Tech. (Computer Science)

2 years (4 semesters)

30

Integrated M.Sc. + M.Tech. (Computer Science)

3 years (6 semesters)

20

The entry and exit schemes of the proposed programmes are summarized in Figure 1.

  1. MINIMUM ELIGIBILITY CRITERIA

In order to be eligible for admission to these programmes, an applicant must satisfy following criterion:

M.Sc. (Computer Science) Programme

  • A 3 or 4-year Bachelor’s degree in Computer Science or a relevant area* with mathematics as a subject either at the Bachelor’s level or at the 10+2 (12th class) level from an institution recognised by the government of any of the SAARC countries with a minimum of 55% marks in the aggregate or an equivalent grade. Candidates who have a 2-year Bachelor’s degree and have cleared the first year of the Master’s programme are also eligible.

M.Tech. (Computer Science) Programme

  • A 4-year B.Tech./B.E./BSc. (Engg.)/BS degree in Computer Science and Engineering or a relevant area* from an institution recognised by the government of any of the SAARC countries with a minimum of 55% marks in the aggregate or an equivalent grade. 

OR

  • A Master’s degree in Computer Science/ Computer Applications/ Mathematics/ Operational Research/ Statistics/ Electronics/ Information Technology/ Physics an institution recognised by the government of any of the SAARC countries with a minimum of 55% marks in the aggregate or an equivalent grade level. 

Integrated M.Sc. + M.Tech. (Computer Science) Programme

  • A 3 or 4-year Bachelor’s degree in Computer Science or a relevant area* with mathematics as a subject either at the Bachelor’s level or at the 10+2 (12th class) level from an institution recognised by the government of any of the SAARC countries with a minimum of 55% marks in the aggregate or an equivalent grade. Candidates who have a 2-year Bachelor’s degree and have cleared the first year of the Master’s programme are also eligible.

*Indicative List of Relevant Areas:

  • Computer Science and Engineering

  • Computer Engineering

  • Computer Applications

  • Information Technology

  • Any other Science/Engineering areas having at least one-fifth Computer Science courses

  1. SPECIALIZATION

With an objective to address the emerging global technological challenges, the programmes offer options to students to acquire skills and excellence in the following specific areas: 

  1. Artificial Intelligence & Machine Learning

  2. Advanced Networks & Systems

     

  • The students can either choose to get the respective degree without specialization or with specialization. 

  • The students admitted in the M.Tech. (Computer Science) programme are required to submit their choice of degree with specialization or degree without specialization before the beginning of the first semester. In case a student opts for degree with specialization, then he/she also needs to select one of the above-mentioned areas of specialization before the beginning of the first semester.

  • The students admitted in the M.Sc. (Computer Science) and integrated M.Sc. + M.Tech. (Computer Science) programme are required to submit their choice of degree with specialization or degree without specialization before the beginning of the third semester. In case a student opts for a degree with specialization, then he/she also needs to select one of the above-mentioned areas of specialization before the beginning of third semester.

  1. CATEGORIZATION OF COURSES

The following categories of courses will be taught in the Master’s programmes:

Hard Core (HC) Courses: These are core courses that will be compulsorily studied by the students as a core requirement to complete the requirements of the respective degree. 

Soft Core (SC) Courses: These are electives courses related to the discipline or specialization in the programme and hence are mandatory for qualifying the eligibility for the specialization.

Specialized Elective (SE) Courses: These are optional courses offered in the areas of specialization. 

General Elective (GE) Courses: These are optional courses that can be chosen by students who do not opt for any specialization. A SC or SE course can also be GE.

Open Elective (OE) Courses: These are the relevant optional courses that can be chosen from the other departments in the university. 

  1. PROGRAMME STRUCTURES

The programme structures along with credit distribution of courses are summarized in Tables 1 to 5. 

TABLE 1: M.SC. (COMPUTER SCIENCE) PROGRAMME STRUCTURE

Year

Semester

Course Type

Course Title

Code

L-T-P

Credits

First

1st

HC

Programming and Data Structures

HC 401

3-0-2

4

HC

Computer Organization and Design

HC 402

3-0-2

4

HC

Database Systems

HC 403

3-0-2

4

HC

Mathematical Foundations of Computer Science

HC 404

3-1-0

4

HC

Operating Systems Design

HC 405

3-0-2

4

2nd

HC

Theory of Computation

HC 406

3-1-0

4

HC

Computer Networks

HC 407

3-1-0

4

HC

Design and Analysis of Algorithms

HC 408

3-0-2

4

HC

Logic for Computer Science

HC 409

3-1-0

4

HC

Information Security

HC 410

3-0-2

4

HC

Introduction to South Asia

2-0-0

2

   OE*

Academic Reading and Writing

2-0-0

2

Second

3rd 

HC

Data Mining

HC 501

3-0-2

4

Specialization in Artificial Intelligence & Machine Learning

SC

Fundamentals of Artificial Intelligence

SC 501

3-1-0

4

SC

Fundamentals of Machine Learning

SC 502

3-0-2

4

   SE**

Specialized Elective 1

4

   SE**

Specialized Elective 2

4

Specialization in Advanced Networks and Systems

SC

Wireless and Mobile Networks

SC 503

3-1-0

4

SC

Advanced Internet Protocols

SC 504

3-1-0

4

    SE**

Specialized Elective 1

4

    SE**

Specialized Elective 2

4

Non- specialization

      GE***

General Elective 1

4

      GE***

General Elective 2

4

     GE***

General Elective 3

4

     GE***

General Elective 4

4

4th 

 

Project****

20

Total

82

Note:  * The credit will not be included in the CGPA.

**The SE courses are to be chosen from the specialization buckets as shown in Table 2. These courses will be floated by the department as per the availability of faculties.

***The SC courses will be GE courses for students not opting for specialization. 

****The project can be done in industry or under the supervision of faculty of the department.

The students choosing specialization must take SE courses from the buckets given in Table 2. All SC and SE courses will be GE courses for students opting for degree without specialization. The course codes and credits of SE and GE courses are shown in Table 2.  

TABLE 2: LIST OF SE AND GE COURSES

Course Type

Course Title

Course Code

L-T-P

Credits

 

Specialization in Artificial Intelligence & Machine Learning

SE

Natural Language Processing

SE 501

3-1-0

4

SE

Evolutionary Algorithms

SE 502

3-0-2

4

SE

Information Retrieval

SE 503

3-1-0

4

SE

Reinforcement Learning

SE 504

3-0-2

4

SE

Big Data Analytics

SE 505

3-0-2

4

SE

Social Media Analytics

SE 506

3-1-0

4

SE

Network Science

SE 507

3-1-0

4

SE

AI and ML Techniques for Cyber Security

SE 508

3-1-0

4

SE

Computational Intelligence

SE 509

3-0-2

4

 

Specialization in Advanced Networks & Systems

SE

Optical Networks

SE 521

3-1-0

4

SE

Linear Programming for Computer Networks

SE 522

3-1-0

4

SE

Internet of Things

SE 523

3-1-0

4

SE

Cloud Computing

SE 524

3-1-0

4

SE

Software Defined Networking

SE 525

3-1-0

4

SE

Cryptography and Network Security

SE 526

3-1-0

4

SE

Blockchain Technology

SE 527

3-1-0

4

SE

Performance Modeling of Computer Networks

SE 528

3-1-0

4

 

 Courses for Non-specialization

GE

Distributed Machine Learning

GE 531

3-1-0

4

GE

Embedded Systems Design

GE 532

3-1-0

4

SE

Fuzzy Modelling

GE 533

3-1-0

4

GE

Real-Time Systems

GE 534

3-1-0

4

GE

Mobile Computing

GE 535

3-1-0

4

GE

Queueing Theory with Applications

GE 536

3-1-0

4

GE

Soft Computing

GE 537

3-1-0

4

Remark: The SE courses will be GE courses for students not opting for specialization. Besides above-listed courses, new SE or GE courses may be offered after approval by the BoS. 

TABLE 3: M.TECH. (COMPUTER SCIENCE) PROGRAMME STRUCTURE

Year

Semester

Course Type

Course Title

Code

L-T-P

Credits

First

1st 

HC

Data Mining

HC 501

3-0-2

4

HC

Optimization Techniques

HC 502

3-1-0

4

HC

Advanced Data Structure and Algorithms

HC 503

3-0-2

4

Specialization in Artificial Intelligence & Machine Learning

SC

Fundamentals of Artificial Intelligence

SC 501

3-1-0

4

SC

Fundamentals of Machine Learning

SC 502

3-0-2

4

Specialization in Advanced Networks & Systems

SC

Wireless and Mobile Networks

SC 503

3-1-0

4

SC

Advanced Internet Protocols

SC 504

3-1-0

4

Non- specialization

 GE*

General Elective 1

4

 GE*

General Elective 2

4

2nd 

HC

Advanced Computer Architecture 

HC 504

3-1-0

4

HC

Introduction to South Asia

2-0-0

2

     OE**

Academic Reading and Writing

2-0-0

2

Specialization in Artificial Intelligence & Machine Learning

SC

Computational Intelligence

SC 505

3-0-2

4

SC

Deep Learning

SC 506

3-0-2

4

      SE***

Soft Elective 1

4

      SE***

Soft Elective 2

4

Specialization in Advanced Networks & Systems

SC

Performance Modeling of Computer Networks

SC 507

3-1-0

4

SC

Distributed Systems

SC 508

3-1-0

4

      SE***

Specialized Elective 1

4

      SE***

Specialized Elective 2

4

Non-specialization

 GE*

General Elective 3

4

 GE*

General Elective 4

4

 GE*

General Elective 5

4

 GE*

General Elective 6

4

Second

3rd 

Dissertation (Part-I)

16

4th

Dissertation (Part-II)

24

Total

82

Note: * The SC courses will be GE courses for students not opting for specialization.  

** The credit will not be included in the CGPA.

***The SE courses are to be chosen from the specialization buckets as shown in Table 5. These courses will be floated by the department as per the availability of faculties. 

TABLE 4: INTEGRATED M.SC. + M.TECH. (COMPUTER SCIENCE) PROGRAMME STRUCTURE

Year

Semester

Course Type

Course Title

Code

L-T-P

Credits

First

1st 

HC

Programming and Data Structures

HC 401

3-0-2

4

HC

Computer Organization and Design

HC 402

3-0-2

4

HC

Database Management Systems

HC 403

3-0-2

4

HC

Theory of Computation 

HC 404

3-1-0

4

HC

Operating Systems Design

HC 405

3-0-2

4

2nd

HC

Mathematical Foundations of Computer Science

HC 406

3-1-0

4

HC

Computer Networks

HC 407

3-1-0

4

HC

Design and Analysis of Algorithms

HC 408

3-0-2

4

HC

Logic for Computer Science

HC 409

3-1-0

4

HC

Information Security

HC 410

3-0-2

4

Second

3rd 

HC

Data Mining

HC 501

3-0-2

4

HC

Optimization Techniques

HC 502

3-1-0

4

HC

Advanced Data Structure and Algorithms

HC 503

3-0-2

4

Specialization in Artificial Intelligence & Machine Learning

SC

Fundamentals of Artificial Intelligence

SC 501

3-1-0

4

SC

Fundamentals of Machine Learning

SC 502

3-0-2

4

Specialization in Advanced Networks & Systems

SC

Wireless and Mobile Networking

SC 503

3-1-0

4

SC

Advanced Internet Protocols

SC 504

3-1-0

4

Non- specialization

 GE*

General Elective 1

4

 GE*

General Elective 2

4

4th 

HC

Advanced Computer Architecture 

HC 504

3-1-0

4

HC

Introduction to South Asia

2-0-0

2

   OE**

Academic Reading and Writing

2-0-0

2

Specialization in Artificial Intelligence & Machine Learning

SC

Computational Intelligence

SC 505

3-0-2

4

SC

Deep Learning

SC 506

3-0-2

4

      SE***

Specialized Elective 1

4

      SE***

Specialized Elective 2

4

Specialization in Advanced Networks & Systems

SC

Performance Modeling of Computer Networks

SC 507

3-1-0

4

SC

Distributed Systems

SC 508

3-1-0

4

      SE***

Specialized Elective 1

4

      SE***

Specialized Elective 2

4

Non-specialization

  GE*

General Elective 3

4

 GE*

General Elective 4

4

 GE*

General Elective 5

4

 GE*

General Elective 6

4

Third

5th

Dissertation (Part I)

16

6th

Dissertation (Part II)

24

Total

122

Note: 

* The SC courses will be GE courses for students not opting for specialization. 

** The credit will not be included in the CGPA.

***The SE courses are to be chosen from the specialization buckets as shown in Table 5. These courses will be floated by the department as per the availability of faculties.

The students choosing specialization must take SE courses from the buckets given in Table 5. All SC and SE courses will be GE courses for students opting for degree without specialization. The course codes and credits of SE and GE courses are shown in Table 5. 

TABLE 5: SE AND GE COURSES 

Course Type

Course Title

Course Code

L-T-P

Credits

 

Specialization in Artificial Intelligence & Machine Learning

SE

Natural Language Processing

SE 501

3-1-0

4

SE

Evolutionary Algorithms

SE 502

3-0-2

4

SE

Information Retrieval

SE 503

3-1-0

4

SE

Reinforcement Learning

SE 504

3-0-2

4

SE

Big Data Analytics

SE 505

3-0-2

4

SE

Social Media Analytics

SE 506

3-1-0

4

SE

Network Science

SE 507

3-1-0

4

SE

AI and ML Techniques for Cyber Security

SE 508

3-1-0

4

SE

Advanced Machine Learning

SE 510

3-0-2

4

 

Specialization in Advanced Network & Systems

SE

Optical Networks

SE 521

3-1-0

4

SE

Linear Programming for Computer Networks

SE 522

3-1-0

4

SE

Internet of Things

SE 523

3-1-0

4

SE

Cloud Computing

SE 524

3-1-0

4

SE

Software Defined Networking

SE 525

3-1-0

4

SE

Cryptography and Network Security

SE 526

3-1-0

4

SE

Blockchain Technology

SE 527

3-1-0

4

 

Courses for Non-specialization

GE

Distributed Machine Learning

GE 531

3-1-0

4

GE

Embedded Systems Design

GE 532

3-1-0

4

GE

Fuzzy Modelling

GS 533

3-1-0

4

GE

Real-Time Systems

GE 534

3-1-0

4

GE

Mobile Computing

GE 535

3-1-0

4

GE

Queueing Theory with Applications

GE 536

3-1-0

4

GE

Soft Computing

GE 537

3-0-2

4

Remark: The SE courses will be GE courses for students not opting for specialization. Besides above-listed courses, new SE or GE courses may be offered after approval of the BoS.