Learn Prompting is an open-source, community-maintained guide covering everything from basic prompt construction to advanced techniques like chain-of-thought, few-shot learning, retrieval-augmented generation, prompt injection defense, and agent design. It is written for non-technical and technical readers alike and updated regularly as the field evolves. Completely free.
Learn Prompting is an open, community-maintained guide to prompt engineering, published as a structured web course rather than a video series. It starts with basic prompt construction and works upward through few-shot prompting, chain-of-thought and other reasoning patterns, structured output, retrieval augmented generation, agent design, and prompt injection and jailbreak defense. Coverage is model-agnostic, with examples across the major assistants and image models rather than tied to a single vendor. Because the project is open source and maintained by contributors, it tends to absorb new techniques as the field publishes them, and it carries more of the adversarial and security-oriented material than vendor documentation usually does. The writing is aimed at both non-technical readers and engineers, so early sections move slowly and later sections assume you are wiring prompts into an application rather than typing them into a chat box.
This is the reference to keep open when you are building something that calls a language model in production and the output needs to be reliable rather than impressive. The sections on structured output, reasoning patterns, and injection defense are the ones that matter once user input reaches your prompts, and those are exactly the areas most short prompting courses skip. It also works as a starting point for a non-engineer who wants to get systematically better at using assistants at work, since the opening material assumes nothing. If you want a one-sitting introduction with an instructor walking you through examples, a short video course will get you moving faster, and you can return here for depth.
ChatGPT Prompt Engineering for Developers is a short, guided course covering core practices with notebooks, and it is the faster way to get the fundamentals in one sitting. Learn Prompting is a reference rather than a course, so it goes considerably wider, including adversarial prompting and defense, and it is better suited to looking things up than to being watched end to end. DeepLearning.AI offers a whole catalog of applied short courses around building with language models, which covers ground Learn Prompting touches but with graded exercises and more structure. Hugging Face NLP Course sits underneath all of them, teaching how the models themselves are trained and fine-tuned rather than how to prompt them. Use Learn Prompting as the standing reference and the others for guided progression.
Compare with: ChatGPT Prompt Engineering for Developers, DeepLearning.AI, Hugging Face NLP Course
The catalog lists Learn Prompting as free. The guide is open source and community maintained, so the written material is readable in full without an account or payment and improves through contributions rather than subscriptions. That also means you can read the repository history to see how guidance has changed as techniques come and go, which is unusual for teaching material in this area. Anything the project offers beyond the open guide is separate from the reference content itself.
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