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01Programs

AI engineering programs for working developers.

Online programs covering LLM application development, retrieval-augmented generation, AI agents, LLM evaluation and deployment. Each one is project-based and ends with something you can run, test and explain.

Not sure where to start?

Learning paths put these programs in a recommended order for the kind of system you want to build.

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Topic
Level
Format

Showing 6 of 6 programs

  • LLM Foundations

    AI Engineering: From Foundations to Production

    Build, evaluate, and ship a working LLM application end to end.

    Level
    Intermediate
    Format
    Self-paced
    Modules
    6
    Duration
    12 weeks (sample schedule)
  • RAG

    RAG & Knowledge Systems

    Build retrieval pipelines that return grounded, cited answers.

    Level
    Intermediate
    Format
    Mentor-guided
    Modules
    5
    Duration
    8 weeks (sample schedule)
  • AI Agents

    AI Agents & Workflow Engineering

    Design tool-using, multi-step systems you can test and control.

    Level
    Advanced
    Format
    Mentor-guided
    Modules
    5
    Duration
    10 weeks (sample schedule)
  • Evaluation

    LLM Evaluation & Reliability

    Measure what your LLM system does and catch regressions before users do.

    Level
    Intermediate
    Format
    Self-paced
    Modules
    5
    Duration
    6 weeks (sample schedule)
  • LLM Foundations

    LLM Foundations for Developers

    Understand how language models work and call them reliably from code.

    Level
    Foundation
    Format
    Self-paced
    Modules
    4
    Duration
    4 weeks (sample schedule)
  • Deployment

    Deploying LLM Applications

    Run LLM features in production with visibility, cost control, and security.

    Level
    Advanced
    Format
    Self-paced
    Modules
    6
    Duration
    8 weeks (sample schedule)

Durations, formats, pricing and availability are editable sample values for this template.

Move from experimenting with AI to engineering it.

Build the foundations, projects, and habits needed to design more dependable AI applications.