Majoring and Minoring
For complete information about majoring and minoring, see the online catalog.
Majoring
A minimum of 44 semester credits, distributed as follows:
- DSCI 140 (Introduction to Data Science)
- MATH 131 (Calculus I), MATH 132 (Calculus II), or CS 230 (Computational Mathematics)*
- CS 171 (Computer Science I) or CS 172 (Computer Science II)
- DSCI 250 (Intermediate Data Science)
- One introductory statistics course
- One advanced statistics course
- One data ethics or social impact course
- Four credits of internship, practicum, or applied learning
- One data-intensive course
- Thesis or Capstone course: DSCI 400 or DSCI 440.
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Four credits of electives chosen from a variety of courses. A few examples include
BIO 370 (Disease Ecology), CS 369 (Artificial Intelligence and Machine Learning), ECON 255 (Technology, Institutions, and Economic Growth), ESS 170 (Climate Science), PSY 425 (Human-Computer Interaction), and RHMS 360 (Digital Media and Society).
*This requirement, and associated credits, may be waived by the chair of the data science major for students eligible to begin math sequences in higher level courses.
Minoring
The minor requires a minimum of 24 credits, distributed as follows:
- DSCI 140 (Introduction to Data Science)
- CS 171 (Computer Science I)
- One introductory statistics course
- One advanced statistics course
- One core social impact course (PHIL 241: Data, Privacy, and Ethics or RHMS 241: Data and Democracy)
- One elective from a variety of courses: a few examples include CS 369 (AI and Machine Learning), ECON 312 (Global Health Economics), POLS 420 (Policy Analysis), PSY 425 (Human-Computer Interaction).
- At least 12 credits applied to the minor cannot be used for another minor or major program. In addition, at least four of the courses for the minor must be taken at Lewis & Clark College.
Data Science FAQ Anticipated Data Science Minor Courses Sample Schedules