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Learning path

AI Engineer

Build production AI applications with LLMs, RAG, agents, tool use and evaluation.

L2 · IntermediatetoL5 · Research4 courses~9 h

What you’ll be able to do

  • Reason about tokens, embeddings, context windows and sampling well enough to debug model behaviour.
  • Design and build a retrieval-augmented generation pipeline end to end.
  • Implement tool-calling agents and know when a plain workflow is the better choice.
  • Estimate inference memory and evaluate an AI system before shipping it.

Your course sequence

Work through these courses in order. Each lesson links straight into the reader.

  1. 1
    AI FoundationsAbsolute Beginner~1 h

    Understand what AI is and how machines learn, no math or code required.

  2. 2
    LLM FoundationsIntermediate~2 h

    How large language models turn text into tokens, attention, and predictions.

  3. 3
    Applied LLM Systems: RAG, Agents & MCPAdvanced~3 h

    Build systems around a model: retrieve knowledge, call tools, and run agent loops.

  4. 4
    AI Systems Engineering: Run, Operate & EvaluateExpert~3 h

    Make a model fit, serve it fast, keep it working, and prove it improved.