General Information
The MS Computer Science (MSCS) curriculum is structured to be completed with a total of 30 credits over 3 semesters (typically).
Program Rules
- GPA – Students must achieve a cumulative grade point average of at least 3.0 to graduate, and no course grades below C will be allowed to count toward graduation. All grades labeled below as core and elective courses within your specialization must be B or better.
- No graduate credit will be given for CS courses with a number lower than 4140.
- A maximum of 6 hours may be taken at the 4000-level and/or with a subject code other than CS or CSE.
- Pass-Fail and Audit – All courses applied to the M.S. CS degree must be taken for letter grade.
- The maximum total credit hours of Special Problems (CS or CSE 89xx) that may be applied toward the M.S. CS degree is 3. These courses must be within the CoC.
- There is no maximum number of Special Topics (CS or CSE 88xx) courses that may be used towards the degree.
- Each student must complete the requirements for one specialization.
Degree Requirements -Course Option
- 30 hours of course work (no M.S. project or thesis hours)
- Total course credit hours required: 30
- Minimum CS/CSE course credit hours: 24
- Minimum CS/CSE course credit hours at the graduate (6000-8000) level: 24
- Minimum total credit hours at the 6000-8000 level: 24
Specializations
Tentatively, students in the GT-Shenzhen MSCS program may choose from four areas of specialization.
- Computational Perception & Robotics
- Computing Systems
- Interactive Intelligence
- Machine Learning
Tentative Courses Offerings (subject to change)
Specialization in Computational Perception and Robotics
(15 hours)
| 1 from | CS 6515 Introduction to Graduate Algorithms |
| 1 from | CS 6601 Artificial Intelligence |
| CS 7641 Machine Learning | |
| 3 from Perception and Robotics, with at least 1 from each |
Perception CS 6475 Computational Photography CS 6476 Computer Vision CS 7639 Cyber Physical Design and Analysis |
|
Robotics CS 7638 Artificial Intelligence Techniques for Robotics CS 7648 Interactive Robot Learning |
Specialization in Computing Systems
(18 hours)
| 1 from | CS 6515 Introduction to Graduate Algorithms |
| 2 from | CS 6210 Advanced Operating Systems |
| CS 6250 Computer Networks | |
| CS 6290 High-Performance Computer Architecture | |
| CS 6300 Software Development Process | |
| CS 6400 Database Systems Concepts and Design | |
| 3 from | CS 6035 Introduction to Information Security |
| CS 6200 Graduate Introduction to Operating Systems | |
| CS 6262 Network Security | |
| CS 6263 Intro to Cyber Physical Systems Security | |
| CS 6291 Embedded Software Optimizations | |
| CS 6310 Software Architecture and Design | |
| CS 6340 Software Analysis and Testing | |
| CS 6675 Advanced Internet Computing Systems and Applications |
Specialization in Interactive Intelligence
(15 hours)
| 1 from | CS 6300 Software Development Process |
| CS 6515 Introduction to Graduate Algorithms | |
| 2 from | CS 6601 Artificial Intelligence |
| CS 7637 Knowledge-Based AI | |
| CS 7641 Machine Learning | |
| 2 from | CS 6440 Introduction to Health Informatics |
| CS 6460 Educational Technology: Conceptual Foundations | |
| CS 6750 Human-Computer Interaction |
Specialization in Machine Learning
(15 hours)
| 1 from | CS 6515 Introduction to Graduate Algorithms |
| 1 from | CS 7641 Machine Learning |
| 3 from | CS 6476 Computer Vision |
| CS 7643 Deep Learning | |
| CS 7646 Machine Learning for Trading | |
| CSE 6242 Data and Visual Analytics | |
| CSE 6250 Big Data for Health | |
| ISYE 6420 Bayesian Methods |