ChatGPT Prompt Engineering for Developers ★
FreeFree short course by Andrew Ng and OpenAI’s Isa Fulford.
Visit ↗Official prompting guides from model makers, plus free courses and references for learning prompt engineering.
Free short course by Andrew Ng and OpenAI’s Isa Fulford.
Visit ↗Anthropic’s official prompt engineering documentation for Claude.
Visit ↗AI21 Labs documentation on prompting its Jamba models.
Visit ↗AWS guide to prompt engineering with links to each model provider’s guide.
Visit ↗Official prompting guide for Amazon Nova understanding models.
Visit ↗Anthropic’s free course platform for Claude, prompting and agents.
Visit ↗Anthropic’s free educational notebooks, from API basics to prompt evaluations.
Visit ↗Free interactive, step-by-step prompt engineering course from Anthropic.
Visit ↗Microsoft’s prompt engineering techniques for models on Azure.
Visit ↗Practical prompt engineering notes from the Brex engineering team.
Visit ↗Cohere’s introduction to prompt engineering for its models.
Visit ↗Google’s official prompt design guide for Gemini.
Visit ↗Google’s beginner course on prompting, with an optional certificate.
Visit ↗Free open course on prompt engineering, plus paid advanced courses.
Visit ↗In-depth survey of prompting techniques and the research behind them.
Visit ↗Meta’s getting-started notes on prompting Llama models.
Visit ↗Official Midjourney documentation for prompts and parameters.
Visit ↗Mistral AI’s official guide to prompting its models.
Visit ↗OpenAI’s free learning hub with videos and guides on using AI.
Visit ↗Example code and prompting guides from OpenAI.
Visit ↗OpenAI’s official guide to prompting GPT models.
Visit ↗Vanderbilt University’s popular Coursera course on prompt patterns.
Visit ↗Comprehensive open guide to prompting techniques by DAIR.AI.
Visit ↗A systematic survey of prompting techniques with a shared vocabulary.
Visit ↗Model makers publish prompting guides for their own models. They are free, kept up to date as models change, and are the most reliable source for what a model actually expects.