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Developer → AI Engineer

Learn how AI works, then build reliable AI features, RAG systems and agents, and grow into an AI Engineer.

For: Developers and software engineers. 24 lessons in this path.

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0 of 13 published lessons completed

Start lesson 1: What AI really is (and what it isn't) →

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Step 1

Foundations

How AI works, why it fails, how to ask it well and how to use it safely.

  1. 1What AI really is (and what it isn't)
  2. 2How machines learn: data, training and models
  3. 3How large language models work
  4. 4Why AI gets things wrong: hallucinations, bias and limits
  5. 5Prompting fundamentals: getting useful answers
  6. 6Using AI safely at work

Step 2

Practitioner

The building blocks behind real AI products, explained without code.

  1. 7Advanced prompting and structured output
  2. 8Embeddings and semantic search
  3. 9Retrieval-augmented generation (RAG)
  4. 10Tool calling and AI agents
  5. 11Evaluating AI quality
  6. 12Cost, speed and scale
  7. 13AI across the software lifecycle

Step 3

Track: AI Engineer

Build reliable AI features and agents. For developers moving into AI engineering.

  1. 14Your first LLM-powered featureComing soon
  2. 15RAG in practiceComing soon
  3. 16Agents and MCP in practiceComing soon
  4. 17Guardrails and security for AI appsComing soon
  5. 18Shipping and monitoring AI featuresComing soon

Step 4

Track: AI Technical Architect

Design AI systems that are secure, scalable and affordable.

  1. 24Reference architectures for AI systemsComing soon
  2. 25Choosing models: build, buy or fine-tuneComing soon
  3. 26Security, privacy and governance by designComing soon
  4. 27Scaling and LLMOpsComing soon

Step 5

Capstone and career

Put it all together, build proof of your skills and plan your next role.

  1. 37Capstone projects by roleComing soon
  2. 38Your AI career planComing soon

Other learning paths

🧪 Tester / QA📋 Business Analyst / PO🏗️ Tech Lead / Architect📈 Project / Delivery Manager🔄 Scrum Master / Agile