Path 01 / Learning syllabus
AI basics
Understand what happens between a prompt and an answer, learn how to check the result, and build a small document assistant that shows its evidence.
Explore the syllabus
Your course project
A small document assistant
Build a small assistant over synthetic service documentation. Each lesson adds a capability or checks whether it works. You can open lessons individually and follow their stated prerequisites.
Before you begin
Start where it makes sense.
For technically curious beginners. No prior AI knowledge or model training experience is required.
Already know the foundations? Jump to any lesson in the syllabus.
Start with the supplied examples. Each exercise explains what you need, what to try and how to check the result; software-based exercises use a disposable practice environment.
The ordered path
What you will learn
Follow the sequence to build the course project, or open the lesson that answers your question.
- 01BeginnerLesson · 7 min read
What AI can and cannot do
Explore how AI can recognize patterns, generate and transform content, write code and use tools. Distinguish the model from its application, then examine where evidence and human judgment are needed.
What you will try
Match several tasks to AI capabilities, then check a document assistant’s answers against the supplied source and identify what it cannot establish.
- 02IntermediateLesson · 16 min read
Run your first model request
Send a prompt, inspect the response, and understand hosted versus local inference. Use synthetic data and keep credentials out of prompts.
What you will try
Send the guide’s small readiness-probe question to a local model, inspect its answer and finish state, and check the distinction between readiness and liveness.
- 03IntermediateLesson · 7 min read
Prompts, tokens and context
Control instructions and supplied information; recognize context and output limits.
What you will try
Change one instruction while keeping the reference document fixed.
- 04IntermediateLesson · 9 min read
Weights, training and inference
Explain what a model learns, what a checkpoint contains and why supplying a document usually does not retrain it.
What you will try
Identify which changes affect request context and which require a training update.
- 05BeginnerLesson · 5 min read
Evaluate an answer
Check claims and compare results against a small, repeatable test set.
What you will try
Score the assistant on answerable, ambiguous and unsupported questions.
- 06BeginnerLesson · 5 min read
Choose a model for a task
Compare quality, latency, cost, privacy and operational requirements.
What you will try
Compare two configurations using the same questions and acceptance criteria.
- 07IntermediateLesson · 7 min read
Embeddings and semantic search
Retrieve relevant passages and recognize misleading matches.
What you will try
Inspect a relevant result and a similar passage that does not answer the question.
- 08IntermediateLesson · 8 min read
Ground answers with RAG
Inspect retrieval, supporting evidence and citations. Treat instructions inside retrieved documents as untrusted content.
What you will try
Check a supported answer and an unsupported answer, then add a document containing a conflicting instruction.
- 09IntermediateLesson · 6 min read
Tools, workflows and agents
Follow an action from model proposal through validation, permission and execution.
What you will try
Inspect a proposed tool call using a harmless stub; verify the result without giving production access.
- 10IntermediateLesson · 6 min read
Build a small document assistant
Combine retrieval and evaluation, measure cost, and handle missing evidence with explicit access limits.
What you will try
Deliver the assistant with a fixed test set, source references and documented failure cases.
