MS Computer Science programme
2015-17
Programme Objectives
MS Computer Science (CS) is a research-based degree programme for
candidates with at least sixteen years education in the field of
computing. The MS-CS is aimed at those students who want to extend
their knowledge to a more advanced and highly specialized material that
reflects current research trends in cutting edge of various CS disciplines.
The programme prepares the students for not only the industry but also
would give them the required knowledge to prepare them for doctoral
level degrees. Although the MS-CS is an independent programme,
however, research work developed in MS programme can be stretched
and made more comprehensive to serve as the research base for a PhD
in CS provided the candidate fulfills all the requirements of the Institute
and the HEC. The MS Computer Science will enable the students to:
 Have a solid understanding of computational theory and foundational
mathematics
 Have substantial exposure to advanced topics in software engineering,
networks, computer architecture, and operating systems.
 Prepare students to conduct research in computer science with
advanced training in selected areas
 Increase the opportunities for advanced positions in computing
profession
Eligibility criteria:
The candidates with at least sixteen years of education in the relevant
disciplines are eligible for admission. Following are the basic
requirements for admission to the MS-Computer Science programme:
 4 year BCS / BIT / BE or BS (Telecomm, Electrical, Electronics) with a
minimum of 130 credit hours from an HEC recognized university
having scored at least 3.0/4.0 CGPA
 2 years master’s degree in Computing/ IT (awarded after 16 years of
education) with an aggregate of 60% marks from an HEC recognized
university.
 A minimum of 50% marks in GAT-General conducted by the National
Testing Service (NTS).
Scheme of courses:
 The MS Computer Science programme comprises of a minimum of 30
credit hours which are to be completed in a minimum of three
semesters. The distribution of the core and elective course is given
below:
Category or Area
Core
Electives
Thesis
Total Credit Hours
Credit Hours
09
15
6
30
Semester-wise break-up of courses
Semester wise breakup of courses
Semester 1
S#
Code
Course title
1
2
3
4
CS
CS
CS
CS
Advanced Theory of Computation
Advance Algorithm Analysis
Research Methods for Computer Science
Elective 1
Credit
hours
3
3
3
3
Semester 2
S#
Code
Course title
1
2
CS
CS
Elective 2
Elective 3
Credit
hours
3
3
3
4
CS
CS
Elective 4
Elective 5
3
3
Semester 3
S#
1
Course title
Research thesis
Credit hours
6
List of electives for MS/PhD Computer Science
The list of courses given below are for reference only. The institute reserves the right
to add / remove courses from the given list as per resources available and/ or
demand for a particular course or set of specialization. Further, it is important to note
that a specialization will only be offered if at least 40% of the students from that class
/ batch register for it.
Computer Networks
S#
Code
Course title
Credit hours
1
2
3
4
5
6
7
8
CS
CS
CS
CS
CS
CS
CS
CS
Advance Computer Networks
Cryptography and Network security
Advance topics in Network Security
Distributed computing
Probabilistic graphic models
Network Management
Cloud and Grid Computing
Advance Operating Systems
3
3
3
3
3
3
3
Software Engineering
S#
Code
1
2
3
4
5
6
7
CS
CS
CS
CS
CS
CS
CS
Course title
Advanced Software Project Management
Requirement Engineering
Software System Architecture
Software System Quality
Formal Methods in Software Engineering
Advance topics in software engineering
Data Mining
Credit hours
3
3
3
3
3
3
3
Artificial Intelligence
S#
Code
1
2
3
4
5
6
7
8
CS
CS
CS
CS
CS
CS
CS
CS
Course title
Natural Language Processing
Machine Learning
Computer Vision
Neural Networks
Probabilistic graphic models
Expert systems
Fuzzy systems
Advance topics in AI
Credit hours
3
3
3
3
3
3
3
3
Multimedia systems
S#
Code
1
2
3
4
5
6
7
CS
CS
CS
CS
CS
CS
CS
Course title
Advance digital signal processing
Advance Digital Image processing
Advance Multimedia systems
Data mining
Advance topics in multimedia systems
Computer Vision
Machine learning
Credit hours
3
3
3
3
3
3
3