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Common AI Core · 7 modules

Enterprise AI Core

Seven modules. One running enterprise project. Production-ready AI engineering literacy.

The Common AI Core every engineer completes before specialising. You build one Northgate Bank assistant and evolve it, module by module, from a single model call into a production-style AI application.

Explainer videos Real Python in your browser One running enterprise project
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Start here: Northgate's challenge
Module 1 · Lesson 0 · Start here

Your learning journey

One Northgate Bank assistant, evolved across seven modules into a production-style AI application.

  1. Technical readiness gate
    Git · command line · HTTP/API · JSON · basic SQL · can read and modify Python
  2. 1
    Module 1Available now

    LLM Fundamentals & Solution Choices

    Can explain how LLMs behave and choose appropriately between prompting, RAG, fine-tuning, workflow, or agent

    ≈ 6 h 38 min Project: Simple LLM applicationOpen module
  3. 2
    Module 2 Lessons coming soonStarting point ready

    Prompt, Context & Structured Outputs

    Can design a reliable prompt/context flow and diagnose whether a bad response is caused by instructions, context, or the model

    Duration set after labs are built Project: Prompt + structured response
    See where you'll start: your code or a clean copy
  4. 3
    Module 3 Lessons coming soon

    AI Evaluation Fundamentals

    Can define expected behavior, build a small eval set, measure quality, and compare two versions objectively

    Duration set after labs are built Project: Evaluation dataset + graders
  5. 4
    Module 4 Lessons coming soon

    RAG & Enterprise Knowledge

    Can explain and build the basic ingestion → retrieval → context → generation pipeline and diagnose retrieval failures

    Duration set after labs are built Project: Enterprise document RAG
  6. 5
    Module 5 Lessons coming soon

    Agents, Tools & MCP

    Can build a basic tool-using agent/workflow and explain state, memory, approvals, permissions, and agent failure modes

    Duration set after labs are built Project: A tool + approval workflow
  7. 6
    Module 6 Lessons coming soon

    Production, Observability, Performance & Cost

    Can trace an AI request, identify latency/cost/failure issues, and explain basic caching, retries, rate limits, and reliability patterns

    Duration set after labs are built Project: Tracing + caching + latency/cost monitoring
  8. 7
    Module 7 Lessons coming soon

    AI Security, Governance & Enterprise Boundaries

    Can identify common AI risks, design basic controls, and explain data boundaries, authorization, auditability, and governance expectations

    Duration set after labs are built Project: Permissions + security + auditability
  9. Common Core exit gate
    Practical build + diagnosis exercise + scenario-based core assessment
  10. Then specialise:EvaluationGenAIDataPlatformSecurityArchitectFDE