MCS Degree Requirements
The MCS program is a coursework-only degree consisting of 32 credit hours with no GRE required for admission. Students learn from world-class faculty and will master in-demand skills.
MCS Degree Planning Documents
Students should regularly reference the university's course explorer and meet with their advisor for the best guidance. Availability of courses varies by location, modality and semester.
Breadth requirement: 12-16 credit hours
Must complete four different courses, each from a different area, from the following core areas with a grade of B- or higher.
Courses in bold italics are available online. Always confirm course availability with your advisor when planning your schedule.
| Area | Available Courses |
| Architecture, Compilers, Parallel Computing | CS 426, 431, 433, 483, 484, 526, 533, 534, 536 |
| Artificial Intelligence |
CS 440, 441, 442, 443, 444, 445, 446, 447, 448, 540, 542, 543, 544, 545, 546, 588, 598 Deep Learning for Healthcare |
| Bioinformatics and Computational Biology |
CS 466, 581, 582 |
| Computers and Education |
CS 500 |
| Database and Information Systems |
CS 410, 411, 412, 470, 510, 511, 512, 514 |
| Interactive Computing |
CS 409, 415, 416, 417, 418, 419, 445, 465, 467, 469, 519, 565, 567, 568 |
| Programming Languages, Formal Methods, Software Engineering |
CS 421, 422, 427, 428, 474, 475, 476, 477, 521, 522, 524, 527, 576, 584 |
| Scientific Computing |
CS 450, 482, 554, 555, 556, 558 |
| Security and Privacy |
CS 461, 463, 507, 539, 562, 563 |
| Systems and Networking (includes real-time systems and security) |
CS 414, 423, 424, 425, 434, 435, 436, 437, 438, 439, 461, 463, 498 Cloud Computing Applications, 523, 525, 537, 538, 541, 563 |
| Theory and Algorithms |
CS 473, 475, 507, 571, 573, 574, 579, 580, 583, 586 |
Advanced coursework: 12 credit hours
- Must be computer science courses numbered CS 500-590 or 598.
- One 4 credit hour CS 597 course or an approved non-computer science 500-level course may be permitted only for students in the Urbana-Champaign and Chicago programs.
- All courses counting toward this requirement must be passed with a grade of C or higher.
Elective courses: 4-8 credit hours
- Graduate (400- and 500-level) coursework from Computer Science, other Grainger College of Engineering Departments, MATH, STAT, or PHYS are pre-approved as elective courses. All other courses must receive prior approval from the Siebel School of Computing and Data Science Graduate Advising Office in order to satisfy degree requirements.
- Subject to all Additional Requirements listed below.
Additional Requirements
- Only 500-level and 400-level (when offered for graduate credit) coursework may be counted toward degree requirements.
- A minimum of 24 computer science credit hours must be taken from the University of Illinois Urbana-Champaign.
- A minimum of 12 credit hours taken at the 500-level overall.
- A maximum of 4 hours of CS 491 and CS 591 may be applied toward the degree, though note that these courses are not available for students in the online program.
- Any course taken for letter grade must have a grade of C or higher. A grade of B- or higher is required for the Breadth coursework.
- The minimum program GPA is 3.0.
- Up to 12 credit hours of previous graduate coursework that is approved by the Siebel School of Computing and Data Science (including non-degree graduate courses completed within the Siebel School) may be transferred and applied to the degree requirements.
- All students must maintain sufficient academic progress. General guidelines are below, but students are responsible for confirming their requirements with their advisor.
- MCS Urbana-Champaign is a full-time program. Students have up to four semesters to complete degree requirements.
- MCS Chicago and MCS online can be taken part-time. Students have the ability to take up to five years to complete their studies, though that is dependent on full-time/part-time status.
Data Science Track
MCS data science track is a more prescribed curriculum plan to ensure the degree and track requirements are met efficiently. Note: the Additional Requirements listed above apply to this course plan.
Students not in this track do not need to follow this course plan.
Must complete one course per area.
| Area | Courses Available |
| Machine learning | CS 441 Applied Machine Learning CS 445 Computational Photography CS 446 Machine Learning CS 447 Natural Language Processing CS 598 Deep Learning for Healthcare |
| Data mining | CS 410 Text Information Systems CS 411 Database Systems CS 412 Introduction to Data Mining |
| Data visualization | CS 416 Data Visualization CS 519 Scientific Visualization |
| Cloud computing | CS 425 Distributed Systems (Cloud Computing Concepts) CS 435 Cloud Networking CS 437 Internet of Things CS 498 Cloud Computing Applications |
Must complete three courses (12 credit hours).
- CS 513 Theory and Practice of Data Cleaning
- CS 519 Scientific Visualization
- CS 598 Foundations of Data Curation
- CS 598 Practical Statistical Learning*
- CS 598 Advanced Bayesian Modeling
- CS 598 Deep Learning for Healthcare
- CS 598 Cloud Computing Capstone*
- CS 598 Data Mining Capstone*
*Prerequisites apply.
At least one elective course is needed to meet degree credit hour requirements. The list below includes courses that may be of special interest to students in the data science track, though you're welcome to choose courses outside of this list as electives instead, keeping the "additional requirements" listed above in mind.
- CS 418 Interactive Computer Graphics
- CS 421 Programming Languages and Compilers
- CS 427 Software Engineering I
- CS 450 Numerical Analysis
- CS 461 Computer Security I
- CS 463 Computer Security II
- CS 475 Formal Models of Computation
- CS 484 Parallel Programming
- STAT 420 Methods of Applied Statistics