Master the art of chaining AI prompts and building sophisticated workflows. Learn to design multi-step AI pipelines, handle errors gracefully, implement branching logic, manage context, and build production-ready AI workflows for research, content creation, and code generation.
Single prompts can only take you so far. This free intermediate course on AI prompt chaining and workflows teaches you how to break complex tasks into coordinated sequences of prompts, passing outputs from one step as inputs to the next. You will move from understanding why single prompts fall short to designing multi-step AI pipelines with clear interfaces, branching logic, and parallel execution patterns.
The course covers the full lifecycle of a production workflow: planning chain architecture, validating outputs, handling failures with retry and fallback strategies, and managing context across long chains using summarization and external memory systems. You will also learn how to integrate external tools into your chains and orchestrate multiple tools together for richer results.
By the end, you will have built working workflows for three common real-world scenarios: research pipelines that synthesize information from multiple sources, content pipelines that take a brief from outline all the way to multi-format output, and code generation chains that move from specification through implementation and test generation. The course is completely free and finishing it along with the final exam earns a certificate of completion you can add to your LinkedIn profile or resume.
12 modules • 43 lessons
Finish every lesson and pass the final exam to earn this free, shareable certificate.
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June 15, 2026
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This course teaches you how to move beyond one-off prompts by chaining multiple AI calls together into structured workflows. You will learn chain design principles, error handling, branching logic, parallel execution, context management, tool integration, and how to apply all of these inside real pipelines for research, content, and code generation tasks.
Yes, the course is completely free and no sign-up is required to start. Completing all lessons and passing the final exam earns you a certificate of completion, which you can share on LinkedIn or attach to a resume.
This is an intermediate course, so you should already be comfortable writing and refining individual prompts with a large language model. You do not need a programming background, though familiarity with basic logic concepts such as conditionals and loops will help you follow the branching and parallel execution modules more easily.
The course focuses on prompt chaining concepts and workflow design patterns that apply across AI tools and APIs rather than locking you into one platform. Topics include output transformation, tool use and multi-tool orchestration, and external memory systems, giving you transferable skills you can apply with whichever AI system you already use.
Prompt chaining is the skill that turns AI from a single-question assistant into an automated collaborator for your own field. The course builds three applied workflow types, research, content, and code, so whether you are a student automating literature reviews, a writer building content pipelines, or a developer generating and reviewing code, the patterns you learn here apply directly to tasks you already do.
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