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Phase 13 · Data, AI and operations

AI Engineering

Design useful AI systems with machine-learning foundations, grounded retrieval, evaluation, safety and observability.

Open repositoryWatch on YouTubeStarter branch

Company-level project

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Begin from the starter branch, work through the modules and use the main branch as a completed reference after making a genuine attempt.

Pythonscikit-learnRetrievalLLM AbstractionEvaluation
Open starter projectView completed referenceAssessment resources

Recommended sequence

Complete the modules at your own pace.

Every module links to the exact GitHub resource folder and its stable code-reference tag.

  1. 01

    AI, Machine Learning and Responsible Data

    Study the resources, complete the practical lab, validate the result and record any limitation.

    Code referencep13-module-01-ai-machine-learning-and-responsible-data
    ResourcesVideo
  2. 02

    Applied Machine Learning with scikit-learn

    Study the resources, complete the practical lab, validate the result and record any limitation.

    Code referencep13-module-02-applied-machine-learning-with-scikit-learn
    ResourcesVideo
  3. 03

    LLM APIs, Retrieval and Tools

    Study the resources, complete the practical lab, validate the result and record any limitation.

    Code referencep13-module-03-llm-apis-retrieval-and-tools
    ResourcesVideo
  4. 04

    Evaluation, Safety, Observability and Release

    Study the resources, complete the practical lab, validate the result and record any limitation.

    Code referencep13-module-04-evaluation-safety-observability-and-release
    ResourcesVideo

Project review

Build first. Compare second. Explain every decision.

Build from starter
Run validation
Compare with main
Document limitations
Explain the architecture