M.S. in Data Science

The M.S. program in Data Science features 36 credits (12 courses) including 10 core courses and 2 electives. The ten core courses are:

• AMS 507 Probability
• AMS 572 Data Analysis
• AMS 580 Statistical Learning (or AMS 530 Parallel Computing if the student has already taken a course like AMS 580)
• AMS 597 Statistical Computing
• CSE 581, Computer Science Fundamentals: Theory
• CSE 582, Computer Science Fundamentals: Data Structures and Algorithms
• CSE 583, Computer Science Fundamentals: Programming Abstractions
• ISE 503 Data Management
• AMS 560 Big Data System
• AMS 598 Big Data Analysis

The two electives can be selected from any letter-graded courses offered by the AMS and CS departments. As a capstone experience and part of the electives, we require the students to take one of the following as a master thesis, with a faculty mentor:

• 3-credit of AMS 585 (Internship in Data Science)
• 6-credits of AMS 585

Students are expected to complete their M.S. program in 3 to 4 semesters.

3 Semester Course Plan

Note: Students can choose to take at least 3-credit of AMS 585 Internship in Data Science during either the third semester, or the summer between the second and the third semesters, with or without industrial sponsors. For students who have taken some of these courses in a previous degree program, they can substitute them with other relevant letter-graded graduate courses from AMS or CS Departments upon the approval of the graduate program director and the course instructor.