10-202 Introduction to Modern AI
12 units, Carnegie Mellon University
This course provides an introduction to how modern AI systems work. By "modern AI", we specifically mean the machine learning methods and large language models (LLMs) behind systems like ChatGPT, Gemini, and Claude. Despite their seemingly amazing generality, the basic techniques that underlie these AI models are surprisingly simple: a minimal LLM implementation leverages a fairly small set of machine learning methods and architectures, and can be written in a few hundred lines of code. This course will guide you through the basic methods that will let you implement a basic AI chatbot. You will learn the basics of supervised machine learning, large language models, and post-training. By the end of the course you will be able to write the code that runs an open source LLM from scratch, as well as code train these models based upon a corpus of data. The material we cover will include: a brief history of AI; supervised machine learning -- including linear models, loss functions and optimization, and neural networks; large language models -- including self attention and transformers, tokenizers, and efficient inference; and post-training -- including supervised fine tuning, alignment and instruction tuning, reasoning models and reinforcement learning, and safety and security of AI systems.
Prerequisites: 21-111 (min C) and 15-112 (min C)
Offered: Spring 2026
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