Module · Beginner
How LLMs Work
Tokens, embeddings, attention and next-token prediction — the mechanics that explain almost every LLM behaviour.
- 4 lessons
- 1h 4m
- 3 simulations
Included in LLMs, Prompt Engineering & Context Engineering· $9
Building with LLM APIs
Calling APIs, streaming, tool calling, caching, and keeping cost and latency under control in production.
- Level
- Intermediate
- Lessons
- 4
- Total time
- 1h 6m
- Simulations
- 5
Included in LLMs, Prompt Engineering & Context Engineering · $9
Tools you'll use
Python
Claude
OpenAI
Gemini
Skills
- Streaming
- Tool calling
- Prompt caching
What you will be able to do
- Integrate an LLM into an app with proper error handling
- Cut cost with caching and model choice
Before you start
A suggestion, never a lock — you can start here.
- prompt-engineering-fundamentals
Modules that help first
Syllabus
4 lessons · 1h 6mEvery lesson's title and summary is public. The lessons themselves open once you own the track.
Every lesson in LLMs, Prompt Engineering & Context EngineeringYour First API Call
16 minOne endpoint, one request shape: messages, roles and parameters — then streaming so the user is not staring at a blank screen.
Included with the track SimulationTool Calling
20 minThe model runs nothing: it asks, your code executes, and the result goes back. Understanding that division of labour is the whole of tool-calling safety.
Included with the track SimulationCost, Latency and Caching
16 minAn LLM bill is dominated by input tokens sent over and over. Prompt caching, a trimmed context, batching, and a model that is good enough — in that order.
Included with the track SimulationRetries and Rate Limits
14 minThe API will slow down and occasionally fail. An app that survives knows which errors to retry, waits with backoff and jitter, limits concurrency, and has a fallback.
Included with the track Simulation
Lifetime access
$9More in LLMs, Prompt Engineering & Context Engineering
Module · Beginner
Prompt Engineering Fundamentals
Clear instructions, examples, step-by-step reasoning and structured output — proven techniques, no incantations.
- 4 lessons
- 58 min
- 1 simulation
Included in LLMs, Prompt Engineering & Context Engineering· $9
Module · Intermediate
Context Engineering
What goes into the context window, where it comes from and in what order — the core skill of building LLM applications.
- 4 lessons
- 1h 4m
- 2 simulations
Included in LLMs, Prompt Engineering & Context Engineering· $9
Module · Intermediate
Evaluating LLM Applications
Eval sets, LLM-as-judge and regression tests for prompts — replacing "looks good to me" with a number.
- 3 lessons
- 44 min
- 1 simulation
Included in LLMs, Prompt Engineering & Context Engineering· $9