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Intermediate32 lessons🏆 Certificate

AI Engineering & Agent Development

Move from AI user to practical builder of reliable AI-powered applications.

A practical engineering track covering model APIs, structured outputs, retrieval, tool calling, agent architecture, evaluation, observability, security and deployment. Learners build toward a production-minded AI application rather than a collection of demos.

Final assessment: 24 questions · 18 correct required (75%)Purchase course →⏱ 20 hours

Course experience

8

Modules

4

Projects

5

Assessment

1

Preview lessons

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Module 1

AI Engineering Foundations

Practical ai engineering foundations skills.

4 lessons
  1. 1From model to applicationPreview
  2. 2Model capabilities and limitations🔒 Locked
  3. 3Tokens, context and structured data🔒 Locked
  4. 4Choosing models for a task🔒 Locked

Module 2

Model APIs & Application Patterns

Practical model apis & application patterns skills.

4 lessons
  1. 1Calling a model API safely🔒 Locked
  2. 2System instructions and application context🔒 Locked
  3. 3Structured outputs and validation🔒 Locked
  4. 4Building a dependable AI feature🔒 Locked

Module 3

Prompting as Engineering

Practical prompting as engineering skills.

4 lessons
  1. 1Prompt design for repeatability🔒 Locked
  2. 2Few-shot examples and constraints🔒 Locked
  3. 3Separating instructions from data🔒 Locked
  4. 4Prompt testing and versioning🔒 Locked

Module 4

Retrieval & Knowledge Systems

Practical retrieval & knowledge systems skills.

4 lessons
  1. 1Why retrieval matters🔒 Locked
  2. 2Chunking and metadata🔒 Locked
  3. 3Embedding and semantic search concepts🔒 Locked
  4. 4Building grounded responses🔒 Locked

Module 5

Tool Calling & Agent Architecture

Practical tool calling & agent architecture skills.

4 lessons
  1. 1Tools, schemas and permissions🔒 Locked
  2. 2Agent loops and planning🔒 Locked
  3. 3State, memory and task boundaries🔒 Locked
  4. 4Designing bounded agents🔒 Locked

Module 6

Evaluation, Observability & Safety

Practical evaluation, observability & safety skills.

4 lessons
  1. 1Creating evaluation datasets🔒 Locked
  2. 2Quality, latency and cost metrics🔒 Locked
  3. 3Tracing and failure analysis🔒 Locked
  4. 4Security and abuse controls🔒 Locked

Module 7

Production AI Systems

Practical production ai systems skills.

4 lessons
  1. 1Caching, rate limits and fallbacks🔒 Locked
  2. 2Data privacy and secrets🔒 Locked
  3. 3Deployment architecture🔒 Locked
  4. 4Monitoring a live AI feature🔒 Locked

Module 8

Engineering Capstone

Practical engineering capstone skills.

4 lessons
  1. 1Defining an AI product specification🔒 Locked
  2. 2Implementing the core workflow🔒 Locked
  3. 3Testing and hardening the system🔒 Locked
  4. 4Presenting a production-readiness review🔒 Locked