AI Application Engineering (RAG and Agents)
0 of 18 lessons complete (0%)
Exit Course
Stage One — What These Systems Can and Cannot Do
The Component You Are Building Around
Preview
Choosing a Model and Where to Run It
Deciding Whether the Model Belongs Here At All
3 lessons
Stage Two — Prompting and Structured Output
Prompt Construction That Holds Up
Structured Output and Defensive Parsing
Decomposition and Chaining
3 lessons
Stage Three — Retrieval Augmented Generation
Why Retrieval and What It Fixes
Chunking Embedding and Indexing
Improving Retrieval Quality
3 lessons
Stage Four — Agents and Tool Use
What an Agent Is and When It Helps
Designing Tools the Model Can Use
Safety Boundaries for Actions
3 lessons
Stage Five — Evaluation and Testing
Building an Evaluation Set
Grading Non-Deterministic Output
Regression Testing and Shipping Changes
3 lessons
Stage Six — Production Cost Latency and Safety
Cost and Latency Control
Safety Guardrails and Prompt Injection
Monitoring Feedback and the Career Path
3 lessons
Stage Four — Agents and Tool Use
Safety Boundaries for Actions
You don’t have access to this lesson
Please register or sign in to access the course content.
Take course
Sign in
Previous
Next