Intermediate
Prompt Engineering
Get reliable results out of generative AI. Learn how large language models produce text, the five principles behind every good prompt, few-shot and structured output, function calling, retrieval-augmented generation, autonomous agents, and how diffusion models turn prompts into images. You finish by wiring text, images, and agents into one working application.
10 lessons5.8h hands-on11 languages
Start learning freePrompt Engineering course10 lessons, in order
- 130 min
The Five Principles of Prompting
Giving directionSpecifying formatProviding examplesEvaluating qualityDividing labor - 230 min
How Large Language Models Generate Text
Tokens and tokenizationNext-token predictionTemperature and top-p samplingContext windowWhy models hallucinate - 335 min
Standard Practices for Text Generation
Prompt formatting and delimitersSystem, user, and assistant rolesFew-shot promptingParsing structured output like JSON - 435 min
Prompt Templates and Function Calling
Prompt templates with variablesSeparating template from dataFunction calling and tool schemasReading a tool call and returning a result - 540 min
Vector Databases and Retrieval-Augmented Generation
Embeddings and vector similarityChunking documentsVector databases and nearest-neighbor searchRetrieval-augmented generationGrounding answers with citations - 640 min
Autonomous Agents: Memory and Tools
The agent loop of reason, act, observeGiving an agent toolsShort-term and long-term memoryStopping conditions and guardrails - 730 min
How Diffusion Models Generate Images
Diffusion as iterative denoisingText conditioning of the imageSeeds and reproducibilitySampling steps and guidance scale - 835 min
Standard Practices for Image Generation
Prompt structure of subject, medium, style, and lightingArt styles and artist or era modifiersComposition and camera modifiersNegative prompts and aspect ratio - 935 min
Advanced Image Techniques: Inpainting, Outpainting, and ControlNet
Image-to-image generationInpainting with masksOutpainting to extend a canvasControlNet for pose, depth, and edge guidance - 1040 min
Building AI-Powered Applications
Composing text, images, and agents into a workflowOrchestration and chaining stepsEvaluation and guardrailsCost, latency, and failure handling
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