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Course Work
On joining the Institute every student is required to plan his/her course-work in consultation with a Faculty Advisor.
Credit Requirements
All students of the MS programme are normally required to complete the prescribed 34 credits within the first two semesters from the date of joining, by completing the coursework prescribed by the faculty advisor.
In addition, the research scholars should complete PP/NP course on Communication Skills.
MS students will be allowed to take additional courses beyond the prescribed 34 credits, with the approval of APEC.
MS students will be allowed to take only one UG course for credit requirements. Additional details on course work can be found in MS-R.4.1 in MS Rule Book
Performance Requirements
A student MUST get at least CC grade in EVERY course (other than optional) registered as a credit course, including seminar.
Academic Probation to the students having lower grade than the minimum requirement for continuation of their studies may be given. For students who have scored grade lower than CC in at most one course in their first semester may be offered an academic probation, with appropriate conditions decided by APEC.
List of PG Courses from CSE Departments | |||
S.No | Course Code | Name of Course | L-T-P-C |
| 1 | CS 601 | Software Development for Scientific Computing | 3-0-0-6 |
| 2 | CS 603 | Approximation algorithms | 3-0-0-6 |
| 3 | CS 604 | Parametrized Algorithms and Complexity | 3-0-0-6 |
| 4 | CS 605 | Reinforcement Learning | 3-0-0-6 |
| 5 | CS 606 | Advanced Topics in Embedded Computing | 3-0-0-6 |
| 6 | CS 607 | Advanced Computer Networks | 3-0-0-6 |
| 7 | CS 608 | FPGA for communication networks prototyping | 3-0-0-6 |
| 8 | CS 609 | Software Defined Networking (SDN) and Network Function Virtualization (NFV) | 3-0-0-6 |
| 9 | CS 610 | Advanced Distributed Systems | 3-0-0-6 |
| 10 | CS 611 | Advanced Software Systems Lab | 0-1-6-8 |
| 11 | CS 612 | Statistical Pattern Recognition Laboratory | 0-0-3-3 |
| 12 | CS 614 | Reinforcement Learning Laboratory | 0-0-3-3 |
| 13 | CS 616 | Statistical Pattern Recognition | 3-0-0-6 |
| 14 | CS 617 | Special Topics in Hardware Systems | 3-0-0-6 |
| 15 | CS 620 | Formal Models for Concurrent and Asynchronous Systems | 3-0-0-6 |
| 16 | CS 621 | Logic and Applications | 3-0-0-6 |
| 17 | CS 622 | Special Topics in Automata and Logics | 3-0-0-6 |
| 18 | CS 623 | Advanced Topics in Communication Networks | 3-0-0-6 |
| 19 | CS 624 | Compilers - Principles and Implementation | 3-0-0-6 |
| 20 | CS 625 | Topics in Stochastic Control and Reinforcement Learning | 3-0-2-8 |
| 21 | CS 626 | Topics in Data Structures and Algorithms | 2-0-2-6 |
| 22 | CS 627 | Data Structures | 3-0-0-6 |
| 23 | CS 628 | Algorithms | 3-0-0-3 |
| 24 | CS 629 | Introduction to Reinforcement Learning | 2-0-2-6 |
| 25 | CS 630 | Statistical Machine Learning | 2-0-2-6 |
| 26 | CS 631 | Seminar | 0-0-4-4 |
| 27 | CS 632 | Runtime Verification | 3-0-0-6 |
| 28 | CS 702 | Systems Bootcamp for ML | 1-0-2-4 |
| 29 | CS 703 | Topics in Design and Analysis of Algorithms | 3-0-0-6 |
| 30 | CS 704 | Advanced Algorithms | 3-0-0-6 |
| 31 | CS 705 | Topics in Graph Theory | 3-0-0-6 |
| 32 | CS 706 | Topics in Parameterized Algorithms and Complexity | 3-0-0-6 |
| 33 | CS 801 | Power Aware Computing | 3-0-2-8 |
| 34 | CS 802 | Dataflow Processor Architecture | 3-0-0-6 |
| 35 | CS 810 | Advanced Computer Architecture | 3-0-3-9 |