How to Learn About AI: Free Courses and Explainers, in Order

Learn more about MinnaLearn's and the University of Helsinki's AI course - no programming or complicated math required.

You're busy. You don't have much time to figure out the deal with Large Language Models (aka LLMs). But you have some curiosity.

Ethan Mollick's post explaining, at a simplified level, how Large Language Models work, including next-token prediction and how tokens are formed, to build intuition for using AI well.

Ethan Mollick's guide to choosing and using AI systems, recommending Claude, Google's Gemini, or ChatGPT and describing their main features and costs.

Anthropic's Interactive Prompt Engineering Tutorial - anthropics/prompt-eng-interactive-tutorial

An overview of what a neural network is, introduced in the context of recognizing hand-written digits.

Google's Machine Learning Crash Course, an interactive introduction to ML topics including linear and logistic regression, classification, working with data, and overfitting.

A free course designed for people with some coding experience, who want to learn how to apply deep learning and machine learning to practical problems.

Discussions: Hacker News (65 points, 4 comments), Reddit r/MachineLearning (29 points, 3 comments) Translations: Arabic, Chinese (Simplified) 1, Chinese (Simplified) 2, French 1, French 2, Italian, Japanese, Korean, Persian, Russian,…

Stanford's CS224N course page for Winter 2026 on natural language processing with deep learning, listing instructors, staff, lecture logistics, and public video access.

Podcast Episode · A Bit of Optimism · June 16 · 59m · Video

The Practical AI podcast, hosted by Daniel Whitenack and Chris Benson, featuring episodes on applied AI, including a recent episode with talks from the Midwest AI Summit.

In this post, we explore strategies for effectively curating and managing their context.