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Coursera

Context Engineering for Beginners

via Coursera

Overview

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Most people using AI tools are getting a fraction of what they're capable of — not because of the tools, but because of how they're being used. This course teaches you context engineering: the practice of managing everything the AI has access to, so every session starts from a position of strength. You'll learn how the context window works and why AI responses drift in long sessions, how memory and knowledge bases extend what the AI knows about your work, and how to structure prompts, system instructions, and large documents for consistently better results. Whether you're using ChatGPT, Claude, or Gemini, these skills apply across every tool and every task. What makes this course different is its focus on the full picture — not just how to phrase a question, but how to engineer the entire environment the AI works from. Step-by-step demonstrations, real-world examples, and a hands-on approach mean you can apply what you learn from your very first session — no technical background required. By the end, you won't just use AI better — you'll understand why it works, so you can adapt as the tools keep evolving.

Syllabus

  • Welcome & Foundations
    • Build a clear mental model of context engineering and understand how the AI's working space shapes every response.
  • How AI “Remembers” — Context Windows & Tokens
    • Explore the mechanics behind AI memory limits and learn how to manage sessions so nothing important gets lost.
  • Memory — How AI Remembers You Over Time
    • Discover how AI tools retain information across sessions and learn to manage your memory profile with intention.
  • Giving AI Your Own Information — Knowledge Bases & RAG
    • Learn how to make your own documents available to the AI and build a knowledge base that produces accurate, specific answers.
  • Context Management Techniques
    • Put everything together with practical techniques for prompts, system instructions, and handling large information.
  • Course Wrap-Up & Next Steps
    • Consolidate everything you've learned with a practical checklist, a look ahead, and a final assessment.

Taught by

Anton Voroniuk

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