In addition to meeting the requirements of the university and of the College of Engineering, students must meet the requirements specified below.
Admission
Applicants for admission should possess a bachelor's degree in computer science or a related field such as mathematics, physics, or electrical engineering. All applicants are encouraged to submit their scores from the Graduate Record Examination (GRE) General Test. Additional information is available on the Department's Web site at http://cse.msu.edu.
Requirements for the Master of Science Degree in Computer Science
The student must complete a total of 30 credits for the degree under either Plan A (with thesis) or Plan B (without thesis) and meet the requirements specified below:
Requirements for Both Plan A and Plan B:
The student must complete a minimum of 18 credits in courses listed below with at least one course from each breadth area:
| System Design and Analysis |
|
| CSE |
812 |
Distributed Systems |
3 |
| CSE |
820 |
Advanced Computer Architecture |
3 |
| CSE |
822 |
Parallel Computing |
3 |
| CSE |
824 |
Advanced Computer Networks and Communications |
3 |
| CSE |
825 |
Computer and Network Security |
3 |
| CSE |
834 |
Advanced Topics in Automated Vehicles |
3 |
| CSE |
893 |
Selected Topics in System Design and Analysis |
3 |
| CSE |
870 |
Advanced Software Engineering |
3 |
| Theory and Algorithms |
|
| CSE |
814 |
Computer Aided Verification |
3 |
| CSE |
830 |
Design and Theory of Algorithms |
3 |
| CSE |
835 |
Algorithmic Graph Theory |
3 |
| CSE |
836 |
Probabilistic Models and Algorithms in Computational Biology |
3 |
| CSE |
860 |
Foundations of Computing |
3 |
| CSE |
894 |
Selected Topics in Theory and Algorithms |
3 |
| Data Analysis and Applications |
|
| CSE |
802 |
Pattern Recognition and Analysis |
3 |
| CSE |
803 |
Computer Vision |
3 |
| CSE |
840 |
Computational Foundations in Artificial Intelligence |
3 |
| CSE |
841 |
Artificial Intelligence |
3 |
| CSE |
842 |
Natural Language Processing |
3 |
| CSE |
845 |
Multidisciplinary Research Methods for the Study of Evolution |
3 |
| CSE |
847 |
Machine Learning |
3 |
| CSE |
848 |
Evolutionary Computation |
3 |
| CSE |
849 |
Deep Learning |
3 |
| CSE |
850 |
Advanced Topics in Adversarial Machine Learning |
3 |
| CSE |
851 |
Genetic Programming |
3 |
| CSE |
881 |
Data Mining |
3 |
| CSE |
895 |
Selected Topics in Data Analysis and Applications |
3 |
Additional Requirements for Plan A:
The student must complete:
- A minimum of 21 credits in 800-900 level courses chosen in consultation with the student's advisor, excluding Computer Science and Engineering 801, 890, 898, and 899.
- At least 6, but not more than 8, credits of CSE 899 Master's Thesis Research.
Additional Requirements for Plan B:
- Complete a minimum of 24 credits in 800-900 level courses chosen in consultation with the student's advisor, excluding Computer Science 801, 890, 898, and 899.