Data Science Major

Program of Study
Degree Type
Bachelor of Science

Program Distribution Requirements for the Data Science Major 

The distribution requirements for the BS degree in Data Science consists of a series of interdisciplinary courses in Data Science, fundamental courses in Computer Science, Mathematical Sciences, and Business, and a set of more advanced courses selected primarily from the three supporting disciplines: Computer Science, Mathematical Sciences, and/or Business. 

Data Science Core Courses (Minimum 3/3 Units)

Students must complete the series of three DS core courses (DS 1010, DS 2010, and DS 3010)

Business Foundation Courses (Minimum 2/3 Units)

Business foundation courses must include 1/3 unit in entrepreneurship and innovation (OBC 1010, ETR 1100, MIS 3010, ETR 3633), and 1/3 unit in business analysis (BUS 2080 OR OIE 2081). One course from each group.

Computer Science Foundation (Minimum 3/3 Units)

Computer science foundation courses must include 2/3 units of introductory computer science (CS 1004, 1101, 1102, CS 2102, CS 2103, CS 2119, or CS elective courses with no more than 1/3 unit at the 1000 level) and 1/3 unit of algorithms (CS 2223).

CS elective courses at level of 3000 and above may be substituted for introductory computer science credits.

Mathematics Foundation (Minimum 5/3 Units)

Mathematics foundation courses must include 2/3 units calculus (MA 1020, MA 1021, MA 1022, MA 1120, or disciplinary elective courses in MA). Students cannot take both MA 1020 and MA 1021 for credit. Students cannot take both MA 1022 and MA 1120 for credits.
2/3 units applied statistics (MA 2611 and MA 2612), and 1/3 unit linear algebra (MA 2071 or MA 2072).

Mathematics disciplinary elective courses may be substituted for introductory calculus credits.

Data Privacy and Ethics (Minimum 1/3 Units)

Choose 1/3 unit from following: CS3043, GOV 2313, GOV 2314, GOV 2315, GOV 2320, PY 2713, PY/RE 2731 or RBE 3100.

Natural or Engineering Sciences (2/3 Units)

Natural or Engineering Sciences 2/3 units of work chosen in Natural or Engineering Science (courses with prefixes AE, AREN, BB, BME, CHE, CE, CH, ECE, ES, GE, ME, PH or RBE count). 

Disciplinary Elective Requirements

Chosen from disciplinary elective courses in CS, MA, or BUS 

At least one course must be selected from each of the following categories: 

  • Data access and management (CS 3431, MIS 3720, CS 4432, CS4433/DS4433) 
  • Data mining/machine learning (CS 4445, CS 4342) 
  • Business modeling and prediction (MIS 4084, OIE 4430)

DS 4099: Special Topics in Data Science is counted as a disciplinary elective course.

Disciplinary electives must include at least 4/3 units at the 4000 level or above.

Please note: 

Students who are double counting their data privacy and ethics requirements as a social science are required to take an additional free elective to reach the required 135 credits.

Data Science MQP (3/3 Units)

Data Science project (3/3 units) must have a MQP faculty advisor that has a formal collaborative appointment in the Data Science program 

 

 

Program Chart and/or Course Flow Chart