CMU Course Reviews (which I haven’t written yet)
This is a list of reviews of courses I’ve taken during my time at Carnegie Mellon as a double major in Statistics (Dietrich) and Artificial Intelligence (SCS), with a minor in mathematics.
Junior Year
Spring 2025:
- 10-708: Probabilistic Graphical Models
- 15-451: Algorithm Design and Analysis
- 36-402: Advanced Methods for Data Analysis
- 36-462: Statistical Machine Learning
- 15-281: AI Representation and Problem Solving
- 85-211: Cognitive Psychology
Fall 2024:
- 10-701: Introduction to Machine Learning
- 36-700: Probability and Mathematical Statistics I
- 21-387: Monte Carlo Methods and Applications
- 36-401: Modern Regression
- 80-335: Social and Political Philosophy
Sophomore Year
Spring 2024
- 15-210: Parallel and Sequential Data Structures and Algorithms
- 21-355: Principles of Real Analysis I
- 33-104: Experimental Physics
- 36-226: Introduction to Statistical Inference
- 36-350: Statistical Computing
- 70-415: Introduction to Entrepreneurship
- 84-323: War and Peace in the Middle East
Fall 2023
- 11-785: Introduction to Deep Learning
- 21-325: Probability
- 33-141: Physics 1 for Engineering Students
- 80-101: Dangerous Ideas in Science and Society
- Dropped 15-213: Introduction to Computer Systems
Freshman Year
Spring 2023
- 15-150: Principles of Functional Programming
- 15-251: Great Ideas in Theoretical Computer Science
- 21-241: Matricies and Linear Transformations
- 36-202: Methods for Statistics and Data Science
- 76-101: Interpretation and Argument
- 66-122: Dietrich College First-Year Seminar
Fall 2022
- 15-122: Principles of Imperative Computation
- 21-127: Concepts of Mathematics
- 21-259: Calculus in 3D: This is a standard Calculus III course. Unfortunately, the quality of many 21-2XX courses varies greatly. I wish CMU would make it a greater priority to make these general math courses more streamlined and more enjoyable.
- 73-102: Principles of Microeconomics
- 80-100: Introduction to Philosophy: If you want to learn about philosophy, take this course. If you don’t, don’t take this course. Weekly readings, weekly writings, and a few papers.