Classes at CMU can be hard. This guide is to give some insight on what to expect from the core classes from the ECE and CS programs at CMU.
- 18-100: Introduction to ECE
- 18-213: Introduction to Computer Systems
- 18-220: Electronic Devices and Analog Circuits
- 18-240: Structure and Design of Digital Systems
- 18-290: Signals and Systems
- 18-500: ECE Design Experience
- 15-122: Principles of Imperative Computation
- 15-150: Principles of Functional Programming
- 15-210: Parallel and Sequential Data Structures and Algorithms
- 15-213: Introduction to Computer Systems
- 15-251: Great Ideas in Theoretical Computer Science
- 15-451: Design and Analysis of Algorithms
- 21-127: Concepts of Mathematics
- 21-241: Matrix Algebra
- 36-219: Probability Theory and Random Processes
- 36-225: Introduction to Probability Theory
- 10-601: Introduction to Machine Learning
- 11-411: Natural Language Processing
- 11-755/18-797: Machine Learning and Signal Processing
- 11-785: Introduction to Deep Learning
- 15-410: Operating Systems
- 15-418: Parallel Computer Architecture and Programming
- 15-424: Logical Foundations of Cyber-Physical Systems
- 15-440: Distributed Systems
- 15-455: Undergraduate Complexity Theory
- 16-385: Computer Vision
- 16-720: Computer Vision
- 16-833: Robot Localization and Mapping
- 17-214: Principles of Software Construction
- 17-437: Web Application Development
- 18-341: Logic Design and Verification
- 18-349: Introduction to Embedded Systems
- 18-447: Introduction to Computer Architecture
- 18-661: Introduction to Machine Learning for Engineers
- 18-793: Image and Video Processing
- 18-847F: Foundations of Cloud and Machine Learning Infrastructure
- 18-898D: Graph Signal Processing and Geometric Learning