Carnegie Mellon University

Master's in Machine Learning Electives

All 12-unit courses from the School of Computer Science or Department of Statistics & Data Science at the 700-level or above are pre-approved for Machine Learning MS students, as are all courses in the Menu Core.

This page highlights some electives that may be of particular interest, and also adds some additional pre-approved courses at the 600-level or outside SCS. It also indicates some 6-unit mini-courses, where two mini-courses can be taken to count for one full 12-unit elective.

With their advisor's permission, students can petition the MS Program Co-Directors to have additional courses be counted as electives. Students should consider whether the course contains technical and mathematical content that will help in learning and applying machine learning. Students are also welcome to take courses beyond the two electives that are required by the program.

Some Suggested Electives

10-605/-805 Machine Learning with Large Datasets
10-709 Fundamentals of Learning from the Crowd
10-808 Language Grounding to Vision & Control
11-641 Machine Learning for Text Mining
11-642 Search Engines
11-643 Scalable Analytics
11-661 Language and Statistics
11-704 Information Processing and Learning
11-711 Algorithms for NLP
11-727 Computational Semantics for NLP
11-751 Speech Recognition and Understanding
11-755 Machine Learning for Signal Processing
11-785 Lab Course on Deep Learning
11-791 Design & Engineering of Intelligent Information Systems
15-615 Database Applications
15-619 Cloud Computing
15-640 Distributed Systems
15-650 Algorithms & Advanced Data Structures
15-651 Algorithm Design & Analysis
15-719 Advanced Cloud Computing
15-855 Introduction to Computational Complexity Theory
15-857 Analytical Performance Modeling & Design of Computer Systems
15-887 Planning, Execution and Learning
16-720 Computer Vision
16-811 Mathematical Fundamentals for Robotics
16-824 Visual Learning & Recognition
16-843 Manipulation Algorithms
16-868 Biomechanics & Motor Control
18-755 Networks in the Real World
36-754 Adv. Probability
36-759 Statistical Models of the Brain

MINI Courses (must take two for a total of 12 units)

11-714 Tools for NLP, 6 units
36-720 Discrete Multivariate Analysis, 6 units
36-723 Survey Sampling, 6 units
36-728 Time Series, 6 units
36-762 Data Privacy, 6 units
36-763 Hierarchical Models, 6 units
36-794 Astrostatistics, 6 units