Carnegie Mellon University

Statistics and Machine Learning

This joint major develops the critical ideas and skills underlying statistical machine learning — the creation and study of algorithms that enable systems to automatically learn and improve with experience.

It is ideal for students interested in statistical computation, data science, or “Big Data” problems, including those planning to pursue a related Ph.D. or a job in the tech industry.

Contact the Statistics & Data Science Academic Advisors

Major Requirements

Theory Requirements

Course Topic/Title Course Number Units Prerequisites
Calculus 21-111 and 112, or 21-120 20 or 10
Integration and Approximation 21-122 10 21-112 or 21-120
Multivariate Calc/Analysis 21-256, 21-259, or 21-268  9–10 21-112 or 21-120
Concepts of Mathematics 21-127 10
Linear/Matrix Algebra 21-240, 21-241, or 21-242 10
Probability 36-225, 36-218, 36-219, 21-325, or 15-359  9 various
Statistical Inference 36-226 or 36-326  9 C or higher in 36-225, 36-218, 36-219, 21-325, or 15-359

Data-Analysis Requirements (Option 1)

Course Topic/Title Course Number Units Prerequisites
Beginning Data Analysis 36-200  9
Intermediate Data Analysis 36-202, 36-208, 36-290, or 36-309  9 various
Advanced Elective 36-303, 36-311, 36-315, 36-318, 36-46x, 36-490, 36-493 or 36-497  9 various
Advanced Elective 36-303, 36-311, 36-315, 36-318, 36-46x, 36-490, 36-493 or 36-497  9 various
Modern Regression 36-401  9 C or higher in 36-226, 36-326, or 36-625 and pass (21-240 or 21-241) and (21-256 or 21-259 or 21-268)
Advanced Methods for Data Analysis 36-402  9 C or higher in 36-401

Data-Analysis Requirements (Option 2)

Course Topic/Title Course Number Units Prerequisites
Advanced Elective 36-303, 36-311, 36-315, 36-318, 36-46x, 36-490, 36-493 or 36-497  9 various
Advanced Elective 36-303, 36-311, 36-315, 36-318, 36-46x, 36-490, 36-493 or 36-497  9
Advanced Elective 36-303, 36-311, 36-315, 36-318, 36-46x, 36-490, 36-493 or 36-497  9
Modern Regression 36-401  9 C or higher in 36-226, 36-326, or 36-625 and pass (21-240 or 21-241) and (21-256 or 21-259 or 21-268)
Advanced Methods for Data Analysis 36-402  9 C or higher in 36-401

Computing Requirements

Course Topic/Title Course Number Units Prerequisites
Statistical Computing 36-350 or 36-650  9 (36-202, 36-208, 36-290, 36-309, 70-208, or equivalent) and 36-225
Fundamentals of Programming 15-112 12
Principles of Iterative Computation 15-122 10 C or higher in 15-112
Machine Learning 10-301/701 12 C or higher in (15-122 or 15-123) and (15-151 or 21-127)
Algorithms and Advanced Data Structures 15-351 12 15-111, 15-123, 15-121, or 15-122
Machine Learning Elective See StatML audit in Stellic for current list  9 vary by elective