Self-paced · Hands-on · Colab-style
Build AI agents,
one lesson at a time.
A complete hands-on course for developers learning to build with LLMs. Read the explanation, copy the code, run it on your own machine, and reveal solutions whenever you get stuck.
6
Sessions
70+
Lessons
4
Projects
Self
Paced
How the portal works
3 simple steps per lesson1
Read the lesson
Each exercise has a short explanation of what the code does and why it matters.
2
Copy & run locally
Click copy on any code block, paste into your editor, run from the terminal.
3
Check yourself
Knowledge-check quizzes, hint reveals, and full solution toggles when you need them.
The learning path
6 sessions, in order0
1 hour
Session 0 — Foundations
Understand LLMs, providers, costs, and how to choose a model before you write code.
LLM basicsML vs LLMProvidersCostModel choice
1
2.5–3 hours
Session 1 — OpenAI SDK Fundamentals
Text, vision, image generation, and text-to-speech from scratch.
Text generationVisionDALL·ETTSCLI apps
2
3 hours
Session 5 — Structured Outputs & Function Calling
Force the model into JSON, call tools, and orchestrate multi-tool flows.
JSON modeJSON SchemaPydanticTool callingRefusals
3
60–90 minutes
Session 6 — LangChain Multi-Provider
Same code, three providers: OpenAI, Anthropic, and Gemini.
LangChainOpenAIClaudeGeminiStreaming
4
1 hour
Session 7 — Choosing Agent Architecture
When to use workflows vs agents vs multi-agent — pick the right pattern before you code.
WorkflowsAgentsMulti-agentArchitectureDecision framework
5
3 hours
Session 8 — Building Agents with LangChain
Build your first agent, add memory, streaming, structured output, and multi-agent handoffs.
create_agentReActMemoryStreamingHITL
What you'll have built
Real artifacts — not just toy snippets — that you can run, show off, and extend.
💬
A multi-modal CLI app
Summarise, analyse images, generate art, and speak — all from one Python script you build in Session 1.
🛠️
A tool-calling agent
Define Python functions, let the LLM call them, and build a loop that handles errors and parallel requests.
🏨
A real booking agent
The BookingAgent capstone — LangChain + SQLite, a full hotel reservation chatbot with persistent data.
🎤
A full-stack interview bot
InterviewerBOT — React frontend, Express backend, OpenAI streaming, end-to-end architecture.