The Master of Science in Data Science program requires the successful completion of 12 courses to obtain a degree. These requirements cover six core courses, a leadership, project management, or data governance course, two required courses corresponding to a declared specialization, two electives, and a capstone project or thesis. A specialization may be declared as part of the application process or may be declared at any time during a student’s tenure in the program. Students also have the option of choosing a general data science curriculum with no declared specialization. There are five specializations: Analytics and Modeling, Analytics Management, Artificial Intelligence, Data Engineering, and Technology Entrepreneurship

Curriculum

Core Courses (8 units)

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Which course should students take?

• Students without a background in data science should select MSDS 402-DL Data Science and Research Practice. 
• Students with a background in data science should select MSDS 403-DL Data Science and Digital Transformation.  Students who have at least two years’ experience in the field and have or had a title, such as data scientist, data analyst, statistician, data engineer, business analyst, etc. should select this course.

Electives (4 units)

About the Final Project

As their final course in the program, students take either a master's thesis project in an independent study format or a classroom final project class in which students integrate the knowledge they have gained in the core curriculum in a team project approved by the instructor. In both cases, students are guided by faculty in exploring the body of knowledge of data science. The master’s thesis or capstone class project count as one unit of credit.