Program Objectives
MS Computer Science (CS) is a research-based degree program 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 program 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 program, however, research work developed in MS program 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 multimedia systems, 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 for Admission
4 year BCS/BIT/BE or BS (Telecom, Electrical, Electronics) with at least 2.70 CGPA or 2 years Master’s degree in Computing/IT (awarded after 2 years BSc) with a 2.70 CGPA (with a minimum of 130 credit hours in Bachelors and 60 credit hours in the Master program) or 60% aggregate marks in annual system from any HEC recognized university/institute.
Qualifying the ETS-GRE general test/NTS-GAT General /Institute’s own test or any other test required by the HEC with 50% marks and interview is mandatory for admission.
The Hafiz Quran shall be given a special credit of 20 marks.
Scheme of Courses
The MS Computer Science program 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 courses is given below:
Credit
- Category or Area Credit Hours
- Core 09
- Electives 15
- Thesis 06
- Total Credit Hours 30
Semester Wise Breakup of Courses
Semester 1
S.No | Course Code | Course Title |
Credit Hours |
1 | CS-711 | Advance Theory of Computation | 3 |
2 | CS-712 | Advance Algorithm Analysis | 3 |
3 | CS-741 | Research methods for Computer Science | 3 |
4 | CS | Elective 1 | 3 |
Semester 2
S.No | Course Code | Course Title | Credit Hours |
1 | CS | Elective 2 | 3 |
2 | CS | Elective 3 | 3 |
3 | CS | Elective 4 | 3 |
4 | CS | Elective 5 | 3 |
Semester 3
S.No | Cours Code | Course Title | Credit Hours |
1 | CS-749 | Research Thesis | 6 |
List of Electives for MS/PhD Computer Science
List of elective courses is given below. The Institute may add elective courses depending upon the demand and availability of resources. 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.
Networks Multimedia Systems and Graphics |
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Course Code | Course Title | Credit Hours |
|
Advanced Digital Signal Processing Advanced Digital Image Processing Advanced Multimedia Systems Advanced Computer Vision Visual Perception Advanced Computer Graphics Advance Human Computer Interaction Multimedia Database Biometric Systems Advanced Machine Learning |
3 3 3 3 3 3 3 3 3 3 3 3 |
Computer Networks |
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Course Code | Course Title | Credit Hours |
|
Advanced Computer Networks Cryptography and Network security Advance topics in Network Security Distributed computing Probabilistic graphic models Network Management Cloud and Grid Computing Advanced Operating Systems Advanced Machine Learning |
3 3 3 3 3 3 3 3 3 |
Software Engineering |
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Course Code | Course Title | Credit Hours |
CS-721 CS-722 CS-723 CS-724 CS-725 CS-726 CS-727cs 732 |
Advanced Software Project Management Requirement Engineering Software System Architecture Software System Quality Formal Methods in Software Engineering Advance topics in software engineering Advanced Topics in Data MiningAdvanced Machine Learning |
3 3 3 3 3 3 3 |
Artificial Intelligence |
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Code | Course Title | Credit Hours |
CS-731 CS-732 CS-733 CS-734 CS-735 CS-736 CS-738 |
Natural Language Processing Advanced Machine Learning Advanced Computer Vision Data Sciences Probabilistic Graphic Models Expert Systems Advanced topics in Artificial Intelligence |
3 3 3 3 3 3 3 3 |
Note: The institute may add or remove the electives according to the resources available.