Courses and Resources

Curated external starting points for building artificial intelligence (AI) skills, organized by what you are trying to do. Every link was verified live when added, and all resources are free unless noted. For this site's own structured introduction, start with the AI Literacy Pathway, and The Hub's Films are short narrated versions of its modules and agent guides. Resources on prompting specifically have their own list in Learning to Prompt.

Getting Started

For anyone who has not used AI tools seriously yet and wants a structured, non-technical foundation. Read How LLMs Work on this site first; it makes both courses land better.

Google AI Essentials Google, self-paced course (paid subscription after a 7-day free trial) A short course on using AI tools productively and responsibly at work. No technical background required. Elements of AI University of Helsinki, free course What AI is, what it can and cannot do, and how it affects society. Calibrated for complete beginners and free.

Teaching with AI

For faculty integrating AI into courses, assessment, and curriculum, or setting expectations for students. Pair these with this site's step-by-step guides, which turn the principles into task-level workflows.

Advancing AI Across Academic Medicine Resource Collection AAMC, resource collection The Association of American Medical Colleges (AAMC) collection of practical resources for integrating AI into medical education. Principles for the Responsible Use of AI in and for Medical Education AAMC, guidance A concise statement of principles, useful when drafting course policies and AI statements. Anthropic Academy Anthropic, free courses Courses ranging from AI fluency for general audiences to technical material for builders. Simple AI Tips for Teaching: a four-part series Dan Levy and Angela Perez Albertos, Harvard Business Publishing Education, article series Four short articles from 2025 on designing a course, revising one, running class sessions, and building assessments.

For Students

The Getting started courses above fit students too. Beyond those, one hour-long lecture is worth the time, and pairs well with the Common Misconceptions page here. The tools directory describes the tools covered on this site, and a tool's card notes any specific concern worth knowing before you use it. Module 3 of the pathway is a five-minute guide to the AI Responsible Use Policy.

Intro to Large Language Models Andrej Karpathy, video, 1 hr (2023) A one-hour lecture on how large language models work, aimed at a general audience. Recorded in late 2023, so it predates current reasoning models, but the fundamentals hold.

Going Deeper (Technical)

For anyone who wants to understand the machinery, not just use it. The DeepLearning.AI short courses below cover retrieval-augmented generation (RAG), agents, and fine-tuning with working code, and Anthropic Academy, listed under Teaching with AI above, also includes hands-on courses for building with the Claude application programming interface (API).

DeepLearning.AI short courses DeepLearning.AI, hands-on courses One-to-two-hour courses on specific skills such as prompting and retrieval. Pick individual courses as needed rather than working through the catalog. 3Blue1Brown: Neural networks series 3Blue1Brown, video series Animated explanations of neural networks, gradient descent, and transformers, rigorous but accessible without heavy math.

The Medical Education Shelf

Current AI-in-medicine resources from the major professional bodies, worth checking a few times a year.

Artificial Intelligence and Academic Medicine AAMC, hub The AAMC's hub for AI initiatives, webinars, and guidance, worth checking a few times a year. Augmented Intelligence in Medicine AMA, hub The American Medical Association (AMA) hub for AI policy, physician survey data, and practice guidance.

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Content last reviewed October 12, 2026. Review dates are maintained as described on the About page.

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