Curriculum & Requirements
Curriculum Overview
The minor in Machine Learning and Data Science consists of 8 courses:
- 1 course in Programming Foundations
- 1 course in Statistics Foundations
- 4 specialization courses focused in Machine Learning, Data Science, or a hybrid between the two
- 2 electives in Machine Learning and Data Science.
AT a Glance
Important Notes
- At least 4 courses must be unique to the minor, and may not be used towards the 21-unit major program, or towards other minors or certificates.
- Students are strongly encouraged to discuss curriculum choices for the MLDS minor with their major advisors before proceeding. See the advising page for more major-specific curriculum guidance.
- Courses with a grade lower than C- cannot be applied to the minor.
Minor Requirements
Students must complete the specified credits in each of the following areas:
Programming Foundations (1 credit)
- COMP_SCI 150 Fundamentals of Computer Programming 1.5
- GEN_ENG 150 Programming for Engineers
- GEN_ENG 151 Honors Programming for Engineers
Statistics Foundations (1 credit)
- BMD_ENG 220 Introduction to Biomedical Statistics
- CHEM_ENG 312 Probability and Statistics for Chemical Engineering
- CIV_ENV 306 Uncertainty Analysis
- GEN_ENG 231 Probability and Statistics for Engineers
- IEMS 201 Introduction to Statistics
- IEMS 303 Statistics
Specialization (4 credits)
Data science track:
- COMP_SCI 217 Data Management and Information Processing
- IEMS 304 Statistical Learning for Data Analysis
- DATA_ENG 200 Foundations of Data Science
- DATA_ENG 300 Data Engineering Studio
Machine learning track*:
- COMP_SCI 111 Fundamentals of Computer Programming I
- COMP_SCI 208 (formerly 214) Data Structures and Algorithms
- COMP_SCI 348 Intro to Artificial Intelligence
- COMP_SCI 349 Machine Learning
*Note: Students majoring in Computer Science are not eligible for the Machine Learning specialization.
Hybrid track:
- COMP_SCI 208 (formerly 214) Data Structures and Algorithms
- COMP_SCI 349 Machine Learning
- DATA_ENG 200 Foundations of Data Science
- DATA_ENG 300 Data Engineering Studio
MLDS Electives (2 credits)
*Note: special topics courses in areas other than those listed will not be accepted.