Practical, fast-payoff skills: structuring prompts, few-shot examples, chain-of-thought, system prompts, evaluation, and model-specific techniques for Claude, GPT, and Gemini.
Sorted cheapest first. Click a column header to re-sort. Anyone using AI tools daily; developers building on model APIs.
| Course | Level | Duration | Price | Certificate | |
|---|---|---|---|---|---|
Anthropic · GitHub |
intermediate | 9 chapters, self-paced | Free | No | Visit |
Google · Coursera |
beginner | Under 10 hours (4 courses) | Paid $49/mo |
Yes | Visit |
Vanderbilt University · Coursera |
beginner | ~18 hours (6 modules) | Free to audit Free to audit · ~$49 |
Yes | Visit |
Vanderbilt University · Coursera |
beginner | 4 weeks at ~10 hrs/week (3 courses) | Paid ~$49/mo |
Yes | Visit |
DeepLearning.AI and OpenAI · DeepLearning.AI |
beginner | ~1 hour 40 minutes | Free to audit Free to audit |
Yes | Visit |
DAIR.AI |
intermediate | Self-paced | Free to audit Free to audit |
No | Visit |
Learn Prompting |
beginner | Self-paced | Free to audit Free to audit |
No | Visit |
No payment required. Several of these are complete university courses.
Anthropic's nine-chapter tutorial with exercises on prompt structure, roles, separating data from instructions, step-by-step thinking, few-shot examples, avoiding hallucinations, and building complex prompts. The definitive hands-on resource for anyone building with Claude.
Watch everything free; pay only if you want graded assignments and a credential.
Dr. Jules White teaches reusable prompt patterns (persona, template, few-shot, chain-of-thought, and more) so anyone can get reliable results from ChatGPT without coding. One of the most popular prompting courses for students, writers, and knowledge workers.
Isa Fulford (OpenAI) and Andrew Ng teach two core prompting principles plus summarizing, inferring, transforming, and expanding text via the OpenAI API in Jupyter notebooks. The classic starting point for developers who want to prompt LLMs systematically rather than by trial and error.
DAIR.AI's widely cited guide to prompting techniques (chain-of-thought, ReAct, RAG, context engineering) with model-specific notes, risks, and links to papers and notebooks. For developers and researchers who want a technical, research-grounded reference.
A comprehensive, open-source written course covering prompting basics, research-backed techniques, reliability, image prompting, prompt hacking, and tooling, written for non-technical readers. Use it as a free reference-style curriculum you can dip into as needed.
Structured programs with instructors, cohorts, projects or formal credentials.
Google's four-course series teaches a five-step prompting framework for everyday tasks, data analysis, presentations, and using AI as a creative or expert partner. Suited to professionals who want practical, tool-agnostic prompting habits and a Google certificate in a few hours.
Three Vanderbilt courses (Prompt Engineering for ChatGPT, ChatGPT Advanced Data Analysis, Trustworthy Generative AI) that take you from prompt patterns to data analysis and reliability. For learners who want a university-branded certificate and a deeper path than a single course.
Understand what AI is, how it works, and how to use it — no coding required.
Transformers, large language models, fine-tuning, and building with foundation models.
Build agents, use the Model Context Protocol, and ship with vendor SDKs.