Free self-paced course

AI Application Engineering Course

This AI application engineering course helps software developers build reliable applications around language models. It focuses on typed interfaces, API contracts, retrieval, tool use, tests, evaluations, observability, cost, latency, security, and production failure handling.

Start application engineeringView curriculum

For

Software developers who know Python, APIs, data structures, and automated testing but are new to production AI systems.

Study time

40–50 hours

Prerequisites

Intermediate Python, HTTP APIs, typed data, source control, and basic testing.

What you will learn

  • Design typed model and tool interfaces with validated inputs and outputs.
  • Build grounded applications with retrieval, citations, evaluations, and abstention.
  • Test model behavior with fixtures, adversarial cases, and regression gates.
  • Operate AI applications with traces, budgets, latency targets, and recovery paths.

Recommended starting guides

Use these answer-first lessons to build the concepts this course depends on.

Build a leakage-safe data and preprocessing workflowBuild a grounded RAG pipeline with citations and evaluationDesign safe Model Context Protocol tools and resourcesEngineer a reproducible AI agent harness

Course format

Each topic combines a concise explanation, an animated mechanism, hands-on evidence, and an optional book-level deep dive.

  • Code-first lessons
  • API and schema contracts
  • RAG and tool use
  • Evaluation and observability
  • Grounded assistant capstone

Mastery evidence

Grounded Assistant Capstone

Ship a grounded assistant prototype with fixed evaluations, guardrails, trace evidence, and an operational readiness argument.

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