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UC Riverside

Data Science

MS in Computational Data Science Coursework

Program Requirements

The MS in Computational Data Science program requires the completion of 49 units of coursework, including a capstone project.

Units are divided among core courses (5 courses, for a total of 20 units), elective courses (6 courses, for a total of 24 units), a professional development course (1 unit) and the capstone course (4 units).

Core courses (20 units):
  1. CS 252A/EE 251A: Data Analytics and Exploration
  2. CS 252B/EE 251B: Fundamentals of Data Science OR CS 224: Fundamentals of Machine Learning
  3. CS 226: Big Data Management OR CS 236: Database Management
  4. CS 235: Data Mining Techniques
  5. CS 108/STAT 108 Data Science Ethics
Elective courses (24 units):

The six electives can be selected from the following two lists of elective courses (list A and list B below); at least four of the courses must be from list A. These lists will be updated as new courses are added. Courses used to satisfy the Core requirements may not be used as Electives.

Elective List A:

  1. CS 205: Artificial Intelligence
  2. CS 222: Natural Language Processing
  3. CS 225: Spatial Computing
  4. CS 226 : Big Data Management OR CS 236: Database Management
  5. CS 227: Probabilistic Models for Artificial Intelligence
  6. CS/EE 228: Introduction to Deep Learning
  7. CS 229: Machine Learning
  8. CS 242: Information Retrieval and Web Search
  9. CS/EE 248: Optimization for Machine Learning
  10. EE 227/CS 258: Introduction to Reinforcement Learning
  11. EE 231: Convex Optimization in Engineering Applications
  12. EE 236: State and Parameter Estimation Theory
  13. EE 240: Pattern Recognition
  14. EE 244: Computational Learning

Elective List B:

  1. CS 210. Scientific Computing
  2. CS 211. High Performance Computing
  3. CS/EE 217: GPU Architecture and Parallel Programming
  4. CS 234: Computational Methods for Biomolecular Data
  5. EE 241: Advanced Digital Image Processing
  6. EE 243: Computer Vision
  7. EE 250: Information Theory
Capstone Experience (4 units):

Students must complete a capstone course CS/EE 279: Capstone Project in Data Science, under the guidance of the capstone instructor member.

Professional Development Requirement (1 unit):

Students will satisfy the professional development requirement by enrolling in one of the following courses: one quarter of CS 287 (Colloquium in Computer Science), or GDIV 403 (Research and Scholarship Ethics), or at least one unit of CS 298I (Individual Internship).

To help students with planning their coursework, below are the graduate course offerings by the two departments:

Computer Science and Engineering: https://www1.cs.ucr.edu/graduate/course-listings

Electrical and Computer Engineering: https://www.ece.ucr.edu/courses