MIDS Students must enroll in and receive credit for 12 additional credit hours of MIDS-related electives. Popular electives include those from the Electrical and Computer Engineering (ECE), Mathematics, Statistics, Energy and Public Policy departments. Once enrolled, the MIDS Assistant Director will go over your options with you. While 12 credits (or four elective classes) is required, MIDS students are able to take up to six (6) electives total.
In addition to these MIDS electives, the rest of the university’s course catalogue is open to students.
MIDS currently offers two electives:
Practicing Data Science (IDS 720)
This course will provide students with extensive hands-on experience manipulating real (often messy, error ridden, and poorly documented) data using the a range of bread-and-butter data science tools (like the command line, git, python (especially numpy and pandas), jupyter notebooks, and more). The goal of these exercises is to ensure students are comfortable working with data in most any form.
Data Analysis at Scale in Cloud (IDS 721)
- Instructor: Noah Gift
Data Analysis at Scale in the Cloud is a project based course with extensive hands-on assignments. This course is designed to give students a comprehensive view of cloud computing including Big Data and Machine Learning. A variety of learning resources will be used including interactive labs on Cloud Platforms (Google, AWS, Azure).
Quantitative Finance Electives (for students interested in the finance industry)
Learn more about Quantitative Finance and its electives.
Other Sample Electives
- Intro to Deep Learning (COMPSCI 675D)
- Statistical Computation (STA 663L)
- Probability (MATH 730)
- Theory & Algorithm Machine Learning (ECE 687D)
- Machine Learning and Imaging (BME 548L)
- Foundations of GIS and Geospatial Analysis (ENVIRON 559)
- Introduction to Social Networks (SOCIOL 728)
- Machine Learning for FinTech (FINTECH 540)
- Research Tech Translation (I&E 710)
- Social Networks & Pol Interdependence (POLSCI 634)