Degree Requirement

Students are required to complete a minimum  of thirty-two (32) units of course work. For course descriptions, please use the “Courses of Instruction” search tool on the Catalogue.

At least 32 units are required, including:

 

Core Curriculum (5 courses, 19 units)

COURSE COURSE TITLE UNITS
MATH 447 Mathematics of Machine Learning 4
MATH 546 Mathematical Statistics for Data Science 4
MATH 549 Foundations of Mathematical Data Science 4
MATH 550 Statistical Consulting and Data Analysis 3
PHYS 515 Python for Data Science and Scientific Computing 4

Electives (12 units, selected from the following list)

COURSE COURSE TITLE UNITS
MATH 446 Data Science with Python 4
MATH 505a Applied Probability 3
MATH 542 Analysis of Variance and Design 3
MATH 545 Introduction to Time Series 3
MATH 547 Mathematical Foundations of Statistical Learning Theory 3
MATH 548 Machine Learning in Quantitative Finance 3
ISE 530 Optimization Methods for Analytics 4
DSO 528 Blended Data Business Analytics for Efficient Decisions 3
DSO 545 Statistical Computing and Data Visualization 3
DSO 530 Applied Modern Statistical Learning Methods 3
EE 553 Computational Solution of Optimization problems 3
ISE 520 Optimization: Theory and Algorithms 3
CSCI 570 Analysis of Algorithms 4
QBIO 578a Computational Molecular Biology 3

Additional Requirements

To complete the program, students enroll in at least 1 unit of MATH 590 Directed Research and submit a summative report at the end of the term. Note: enrollment in MATH 590 will often be concurrent with enrollment in MATH 550. Students should consult with their advisor for details.