2023-2024 Catalog 
    Jun 13, 2024  
2023-2024 Catalog

Data Science Sequence

Sequence Requirements

The sequence in data science requires 6 courses, distributed as follows:

1. Python (1 course)

An introductory course in programming in Python. Courses at The Claremont Colleges that satisfy this requirement include:

4. Electives (2 courses)

Two approved electives, at least one of which must be from Group B.

Group A

These are intermediate courses that require a quantitative or statistical skills prerequisite.

Group B

These courses are more advanced and generally require an intermediate quantitative course as a prerequisite.


  • Students may not pursue the data science major and the data science sequence.
  • Students may not earn credit for more than one data science principles class (CSCI 036 CM ECON 122 CM , and ECON 160 CM ).

Learning Goals and Student Learning Outcomes of the Data Science Program

Learning Goals

The Data Science sequence presents students with the opportunity to:

  1. Analyze data from a variety of disciplines and present its inherent features.
  2. Predict outcomes of data processes or generate forecasts.
  3. Work with computer programs, statistical packages, and data management programs.
  4. Devise methodologies to turn data information into valuable insights.

Student Learning Outcomes

Students who complete the sequence will be able to:

  1. Analyze data and present its inherent features.
  2. Have a working knowledge of advanced data analysis using a variety of platforms.
  3. Work with commonly used statistical packages and programming languages (for example R, STATA, SPSS, Python, SQL) used in research, government, nonprofit organizations, and industry.
  4. Make informed predictions, test theories, and evaluate policies.
  5. Communicate the results of such analyses to all stakeholders.