Coursework @ CMU

Graduate courses are marked with *

Computer Science

  • F23: 10-708* Probabilistic Graphical Models
  • F23: 10-718* Machine Learning in Practice
  • S23: 10-422 Foundations of Learning, Game Theory, and their Connections
  • S23: 15-317 Constructive Logic
  • F22: 10-703* Deep Reinforcement Learning and Control
  • F22: 15-440 Distributed Systems
  • S22: 15-751* A Theorist’s Toolkit
  • F21: 15-859* Algorithms for Big Data
  • F21: 15-459 Quantum Computation
  • F21: 15-451 Algorithm Design and Analysis
  • S21: 10-725* Convex Optimization
  • S21: 15-462 Computer Graphics
  • S21: 16-385 Computer Vision
  • F20: 10-701* Introduction to Machine Learning
  • F20: 15-210 Parallel and Sequential Data Structures and Algorithms
  • M20: 15-213 Introduction to Computer Systems
  • S20: 15-251 Great Ideas in Theoretical Computer Science

Mathematics & Statistics

  • F23: 36-705* Intermediate Statistics
  • S23: 21-640* Introduction to Functional Analysis
  • F22: 21-301 Combinatorics
  • F22: 21-341 Linear Algebra
  • S22: 21-484 Graph Theory
  • S22: 21-356 Principles of Real Analysis II
  • S22: 80-405 Game Theory
  • F21: 21-373 Algebraic Structures
  • S21: 36-226 Introduction to Statistical Inference
  • F20: 21-355 Principles of Real Analysis I
  • M20: 21-325 Probability
  • S20: 21-270 Introduction to Mathematical Finance