Minor

The Minor in Data Science is open to ALL students! The Data Science Minor is designed to equip students to become proficient in the principles of computation, statistical inference, and data management, and their applications in a specific domain/field.

These goals are achieved by students completing 6 courses plus a 1-credit mini-capstone. Students must maintain a G.P.A. of 2.0 in the courses applied to the minor. No courses with grade D can be counted toward the minor.

Students are advised to check with their major department for any restrictions on counting courses for both the Data Science minor and their major.

docxPlease use this form to track your progress

Courses:

There are three foundational courses followed by an advanced domain-specific course and a mini-capstone course, which are the same as that for the Data Science Certificate program. See here for details.

The minor requires two additional courses which are differentiated into four tracks to allow students to follow their career pathway.

Track 1.

This track targets students with existing programming experience. It requires courses in statistics, data-centric programming, data management, and data analysis. Introduction to Discrete Structures (CS205) is a prerequisite.

  • Regression Methods 01:960:463 (3) and
  • Choose from one of the following Machine Learning courses

Track 2.

This track targets students with a quantitative background but perhaps little programming experience. It can be pursued without any additional prerequisite courses beyond those in requirements I, II, and III.

  • Computing and Graphics in Applied Statistics 01:960:486 (3) and
  • Choose from one of the following

Track 3.

This track is intended mainly for Economics majors or Quantitative Economics minors. In any case, completion of the intermediate economics core courses (01:220:320, 321 and 322) is required, as these courses are prerequisites to the Economics machine learning course, 01:220:424.

  • Advanced Analytics for Economics 01:220:424 (3) and
  • Choose from one of the following

Track 4.

This track will allow students to develop skills in human-centered aspects of data science. Introduction to computer concepts (04:547:201) is a prerequisite for the following courses. A prerequisite override articulation agreement, using Data Science Certificate courses I, II, and III, equivalency, is being pursued.