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Nov 23, 2024
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2024-2025 Catalog
Data Science Sequence
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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:
2. Data Science Principles (1 course)
One course selected from:
3. Statistics (1 course)
One course selected from:
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.
5. Capstone (1 course)
One course selected from:
Notes:
- 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:
- Analyze data from a variety of disciplines and present its inherent features.
- Predict outcomes of data processes or generate forecasts.
- Work with computer programs, statistical packages, and data management programs.
- Devise methodologies to turn data information into valuable insights.
Student Learning Outcomes
Students who complete the sequence will be able to:
- Analyze data and present its inherent features.
- Have a working knowledge of advanced data analysis using a variety of platforms.
- Work with commonly used statistical packages and programming languages (for example R, STATA, SPSS, Python, SQL) used in research, government, nonprofit organizations, and industry.
- Make informed predictions, test theories, and evaluate policies.
- Communicate the results of such analyses to all stakeholders.
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