MS Computer Science
Important for all candidates
Applicant for admission MUST MEET THE ELIGIBILITY REQUIREMENTS set-forth by Bahria University.
Candidates are advised to CONFIRM THEIR ELIGIBILITY prior apply.
In case of annual system, eligibility will be determined on the basis of result in percentages.
In case of semester system, eligibility will be determined on the basis of CGPA obtained out of 4.00.
In case the result is shown both in CGPA and percentage, CGPA will be considered.
Eligibility Criteria
HEC recognized 4 years Bachelor degree in Computer Sciences/Software Engineering/Computer Engineering/ Information Technology or equivalent with CGPA 2.0/4.0 (Semester System) or 50% marks (Annual System) or MIT/MCS/M.Sc (Computer Science) or equivalent with CGPA 2.0/4.0 (Semester System) or 50% marks (Annual System). NTS GAT (General)/GRE/University entry test passed with 50% Marks.
Prerequisite/ Deficiency Courses: Candidates without Engineering/ Computer background may have to take some or all of the following Deficiency courses from computing domain as given below (please consult CS Department 051-9260002-Extn: 1341 prior applying for admission):
| S No | Course Code | Course Description | Credit Hours |
| 1. | CSC 113 | Computer Programming | 03 |
| 2. | CSC 321 | Analysis of Algorithms | 03 |
| 3. | CEN 324 | Computer Organization and Assembly Language | 03 |
| 4. | CSC 320 | Operating System | 03 |
| 5. | CSC 315 | Theory of Automata | 03 |
Program Mission
The mission of the MSCS program is to produce Computer Science graduates who are able to
apply their theoretical knowledge and analytical skills to create effective and novel solutions to
practical and research oriented computing problems.
Education Objectives
The key objectives of the MSCS program include the following.
1. To provide an in depth understanding of the theory and concepts of the core Computer
Science areas.
2. To prepare students for graduate level training in specialized areas of Computer Science.
3. To enable learning of the latest Computing tools and technologies.
4. To enable students t o apply their knowledge and analytical skills to create effective
and novel solutions to various computing problems.
5. To develop effective oral and written communication skills for working independently
and in groups.
Program Learning Outcomes
Students graduating from the MS (CS) program are expected to:
1. Ability to apply Mathematical foundations, computational theory and algorithmic
principles to solve practical as well as research-oriented computing problems.
2. Ability to turn complex programming specifications into well designed and well tested
computer programs.
3. Acquaintance with the latest computing tools and technologies.
4. To develop effective oral and written communication skills.
5. Ability to pursue continuous professional development.
6. Ability to work on practical and research-based problems collaboratively as well as
independently.
Road Map
| Course Code | Course Title | Credits |
| Semester 1 | ||
| CSC 703 | Advanced Theory of Computation | 3 |
| CSC 721 | Advanced Design and Analysis of Algorithms | 3 |
| ESC 701 | Research Methodology (University Requirement) | 3 |
| Total | 9 | |
| Semester 2 | ||
| CSC 720 | Advanced Operating Systems | 3 |
| CEN 720 | Advanced Computer Architecture | 3 |
| Elective I | 3 | |
| Total | 9 | |
| Semester 3 | ||
| Elective II | 3 | |
| Elective III | 3 | |
| THS 799 |
Thesis I / Elective IV | 3 |
| Total | 9 | |
| Semester 4 | ||
| THS 799 |
Thesis II / Elective V | 3 |
| Total | 3 | |
| Total Program Credits | 30 | |
ELECTIVE COURSES – MSCS Program
| Course Codes | Course Names | Credits |
| CSC 706 | Advanced Ubiquitous Computing | 3 |
| CSC 705 | Intelligent User Interface Design and Evaluation | 3 |
| CSC 717 | Virtual Reality Technologies | 3 |
| CSC 716 | Game Theory | 3 |
| CSC 701 | Computer Supported Cooperative Work | 3 |
| SEN 720 | Advanced Human Computer Interaction | 3 |
| SEN 756 | Advanced Usability Engineering | 3 |
| CSC 728 | Decision Support Systems | 3 |
| CSC 715 | Intelligent Agents | 3 |
| CSC 719 | Machine Learning | 3 |
| DSC 707 | Deep Learning | 3 |
| CSC 741 | Advanced Natural Language Processing | 3 |
| CEN 745 | Advanced Digital Image Processing | 3 |
| CSC 749 | Advanced Neural Networks and Fuzzy Logic | 3 |
| CSC 751 | Pattern Recognition | 3 |
| CSC 764 | Computer Vision | 3 |
| CSC 750 | Intelligent Tutoring Systems | 3 |
| ESC 719 | Distributed Networking | 3 |
| ESCC722 | Network Administration and Management | 3 |
| ESC 756 | Mobile Communications and Networking | 3 |
| EET 702 | Advanced Network Security | 3 |
| EET 713 | Advanced Network Design | 3 |
| EET 716 | Advanced Topics in Wireless Networking and Communications | 3 |
| EET 718 | Network Performance Evaluation | 3 |
| EET 761 | Network Protocols and Standards | 3 |
| CSC 781 | Cloud Computing | 3 |
| CSC 733 | Advanced Information Theory | 3 |
| CSC 746 | Advanced Data Mining | 3 |
| CSC 747 | Text Mining | 3 |
| CSC 752 | Advanced DBMS | 3 |
| CSC 753 | Distributed Databases | 3 |
| CSC 754 | Object Oriented Databases | 3 |
| CSC 755 | Web based DBMS | 3 |
| CSC 756 | Multimedia Databases | 3 |
| CSC 760 | Advanced Data Warehousing | 3 |
| CSC 714 | Advanced Information Retrieval Techniques |
3 |
| SEN 764 | Ontology Engineering | 3 |
| SEN 761 | Semantic Web (3) | 3 |
| CEN 759 | Generative AI | 3 |
