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LLMs

Hands-on LLM engineering - from prompting to agents and MCP servers.

8 weeks · Sat & Sun 13:00–16:00 (UTC+1) Live on Google Meet

Large language models are reshaping how we build software - and the best way to learn them is by building with them.

This 8-week intensive takes you from your first API call to deploying RAG pipelines, conversational chatbots, AI agents with LangGraph and your own MCP servers. Every session is live and hands-on: we code together, you build, and you leave with real projects.

By the end you will have built a complete LLM application - from embedding documents and querying them, to orchestrating multi-step agent workflows - ready for your portfolio.

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8Weeks
15Live lessons
45hHands-on hours
LiveSat & Sun online
GroupLive instruction
100%Project-based
Outcomes

What you'll learn

By the end, you'll have a live database chatbot running on your own server, and the skills to build the next one faster.

  • Understand how LLMs work - transformers, tokens and context windows
  • Master prompting techniques that get reliable, structured output
  • Build RAG pipelines with vector stores (pgvector, Qdrant, ChromaDB)
  • Create conversational chatbots with memory and context
  • Build AI agents with LangChain and LangGraph
  • Deploy MCP servers and connect agents to external tools
  • Evaluate LLM applications for quality, cost and safety
  • Ship a portfolio-ready LLM project
Syllabus

Week by week, building real skills

Two live lessons each week — a Saturday lesson introducing fresh material and a Sunday guided lab to embed it.

Week 1 · LLM foundations

What are LLMs - transformers, tokens, context windowsSetting up: API keys, environment, first API callPrompting fundamentals and best practicesUnderstanding cost, latency and model selection

Week 2 · Prompting and text generation

Advanced prompting: few-shot, chain-of-thoughtStructured output: JSON mode and function callingBuilding a CLI chatbot with the OpenAI / Anthropic APITemperature, top-p, and sampling parameters

Week 3 · RAG - Retrieval-Augmented Generation

What is RAG and why it mattersDocument loading, chunking strategies and embeddingVector stores: pgvector, ChromaDB, QdrantBuilding a complete RAG pipeline from scratch

Week 4 · Embeddings and vector stores deep dive

Embedding models: OpenAI, open-source alternativesSimilarity search, filtering and hybrid strategiespgvector with PostgreSQL in productionQdrant: indexing, search and performance tuning

Week 5 · LangChain fundamentals

LangChain architecture: chains, prompts, output parsersSequential and parallel chainsMemory and conversation historyTooling: web search, calculators, code execution

Week 6 · LangGraph agents

What are AI agents and when to use themLangGraph: state machines for multi-step reasoningTool-calling agents with persistent memoryBuilding a research agent that plans and acts

Week 7 · MCP servers and integration

Model Context Protocol (MCP) - architecture and specBuilding an MCP server from scratchConnecting agents to external tools via MCPReal-world MCP integrations and deployment

Week 8 · Capstone - build your LLM app

Design your LLM-powered applicationBuild it hands-on, session by sessionDeployment, monitoring and production safetyProject showcase and next steps
Live schedule

Your live classroom

Times are shown in UTC+1 (the academy's default). Add your phone number to your account to see every lesson in your own local time. Lessons run Saturdays & Sundays, 13:00–16:00 UTC+1.

Free demo & orientation

Thursday 19 November 2026 13:00–16:00 3 days before the course starts

Join us before anything begins — meet your instructor, watch a live sample lesson and get all your questions answered. No commitment required.

Join the demo
Week 1

LLM foundations

Sun22 Sunday 22 November 2026 13:00–16:00UTC+1
Sat28 Saturday 28 November 2026 13:00–16:00UTC+1
Week 2

Prompting and text generation

Sun29 Sunday 29 November 2026 13:00–16:00UTC+1
Sat5 Saturday 05 December 2026 13:00–16:00UTC+1
Week 3

RAG - Retrieval-Augmented Generation

Sun6 Sunday 06 December 2026 13:00–16:00UTC+1
Sat12 Saturday 12 December 2026 13:00–16:00UTC+1
Week 4

Embeddings and vector stores deep dive

Sun13 Sunday 13 December 2026 13:00–16:00UTC+1
Sat19 Saturday 19 December 2026 13:00–16:00UTC+1
Week 5

LangChain fundamentals

Sun20 Sunday 20 December 2026 13:00–16:00UTC+1
Sat26 Saturday 26 December 2026 13:00–16:00UTC+1
Week 6

LangGraph agents

Sun27 Sunday 27 December 2026 13:00–16:00UTC+1
Sat2 Saturday 02 January 2027 13:00–16:00UTC+1
Week 7

MCP servers and integration

Sun3 Sunday 03 January 2027 13:00–16:00UTC+1
Sat9 Saturday 09 January 2027 13:00–16:00UTC+1
Week 8

Capstone - build your LLM app

Sun10 Sunday 10 January 2027 13:00–16:00UTC+1
Classroom & community

Learn together, online

Live Google Meet classroom

Every lesson happens in a private Google Meet room with screen sharing, code-alongs and instant help.

The room link is shared with booked students before the course starts.
WhatsApp study group

Stay connected between sessions — homework help, classmates and weekly reminders in one group.

Get the group invite when you'd like to join.
Toolkit

What you'll work with

Python 3.12+VS CodeOpenAI APIAnthropic APILangChainLangGraphpgvectorQdrantDockerGit and GitHub

Ready to start building?

Pre-book your seat for the 22 November cohort — or join the free demo and see for yourself.

View the flier