Electives

Note: Both Statistics and Tepper offer "mini" half-term courses. Two such "mini" courses are equivalent to one (12 unit) graduate course.

Suggested Electives from Statistics (12 units, must be chosen from Statistics)

36-703 Intermediate Probability
36-707 Regression Analysis
36-708 Experimental Design, 6 units, A4 mini
36-709 Linear Models, 6 units, A3 mini
36-713 Math Master Class, 6 units
36-713 Nonparametric Methods
36-720 Discrete Multivariate Analysis
36-722 Continuous Multivariate Analysis
36-724 Applied Bayesian Methods, 6 units, A3 mini
36-728 Time Series Analysis
36-752 Adv. Probability Overview
36-754 Adv. Probability
36-900 Selected Topics of the Contemporary Frontiers of High Dimensional Inference
36-905 Seminar on Latent Variable Models, 6 units

Suggested Depth Requirement Electives from SCS

Al:
10-725 Optimization
10-708 Graphical Models
15-780 Graduate Artificial Intelligence
15-887 Planning, Execution, and Learning

Algorithms & Theory:
10-725 Optimization
15-855 Computational Complexity Theory
15-859 Special Topics in Theory - check for appropriate topics
16-811 Mathematical Fundamentals for Robotics
21-801 Adv. Topics Discrete Math (Random Graphs)

Computational Biology:
10-708 Graphical Models
10-810 Computational Genomics

Computer Vision:
16-720 Computer Vision
16-721 Learning Based Methods in Computer Vision

Databases:
15-823 Advanced Database Topics

NLP or Text Analysis:
10-707/11-741 Information Retrieval
10-708 Graphical Models
10-709 Reading the Web
11-711 Algorithms for NLP
11-744 Experimental Information Retrieval
11-761 Language and Statistics
11-762 Language and Statistics II
11-773 Text-Driven Forecasting

Robotics:
15-887 Planning, Execution, and Learning
16-811 Mathematical Fundamentals for Robotics
16-831 Statistical Techniques in Robotics
16-899C Adaptive Control and Reinforcement Learning

Other electives from SCS approved but don't have a Depth Requirement category:
11-755 Machine Learning for Signal Processing

Suggested Concentration Electives from School of Public Policy & Management:
10-830/90-904 Research Seminar in Machine Learning & Policy, 6 units, A4 mini
10-831/90-921 Special topics in Machine Learning & Policy, 6 units, A3 mini

Suggested Concentration Electives from Tepper (Must follow Tepper special registration rules)

Finance Track:
45-814 Options
46-926 Linear Models/Equity Portfolio Management
46-929 Financial Time Series Analysis
46-944 Stochastc Calc Fin 1

Marketing Track:
15-892 Foundations of Electronic Marketplaces (CS course)
47-800 Intermediate Microeconomic Analysis
47-741 Seminar in Marketing I
47-742 Seminar in Marketing II
47-743 Seminar in Marketing III
47-744 Analytical and Structural Marketing Models
45-821 Interactive Marketing and Leveraging Technology
45-824 Database Marketing

Information Systems Track:
47-800 Intermediate Microeconomic Analysis
45-870 Management of Information Systems
45-871 Information Strategy, Systems and Economics
47-951 Seminar in Information Systems I
47-952 Seminar in Information Systems II
47-953 Seminar in Information Systems III
47-954 Seminar in Information Systems IV

NOTE: Tepper courses are on the mini-system.45-* and 46-* are Master level courses and the 47-* are PhD level courses Suggested

Concentration Electives from Philosophy · 80-605 Rational Choice · 80-614 Logic in Artificial Intelligence · 80-616 Probability and Artificial Intelligence · 80-621 Causality in the Social Sciences