We do not offer a scattering of short courses. We offer one complete, carefully built journey that takes you from how large language models actually work, all the way to designing, building and shipping real GenAI applications and AI agents. It is structured, mentor-led and project-based, built for graduates who simply need a way in. You learn by building, and you leave with work, confidence and dignity you can carry into any room.
| Detail | Description |
|---|---|
| Program | AI Engineer (Generative AI) |
| Journey | From how LLMs work, to prompting and APIs, to RAG, to AI agents, to building and deploying GenAI apps |
| Format | Offline, in person, mentor-led |
| Duration | 30 Days |
| Level | Beginner-friendly start, ramping to advanced |
| Cost | Completely free |
The program is organised into focused modules. You begin with the foundations and steadily build toward shipping production-grade GenAI systems.
| Module | What You'll Master |
|---|---|
| How LLMs Actually Work | Transformers and attention, tokens and embeddings, pretraining vs fine-tuning, context windows, sampling and temperature, why models hallucinate, evaluating model behaviour |
| Prompt Engineering & LLM APIs | Prompt design patterns, chain-of-thought, few-shot, structured/JSON outputs, tool and function calling, OpenAI and Anthropic Claude APIs, cost, latency and token management |
| RAG & Knowledge Systems | RAG pipelines, GraphRAG, hybrid search, Pinecone, Weaviate, ChromaDB, FAISS, pgvector, Graphiti, mem0, Zep (long-term agent memory) |
| AI Agents & Orchestration | LangChain, LangGraph, CrewAI, AutoGen, multi-agent systems, tool use, memory and planning, Anthropic Claude API, OpenAI Agents SDK, Google ADK (Agent Development Kit), MCP (Model Context Protocol) |
| Building & Deploying GenAI Apps | Full-stack GenAI architecture, streaming, guardrails and safety, evaluation and observability (LangSmith, Langfuse), production vector stores, FastAPI, Streamlit, Docker, cost and latency optimisation |
Career paths this prepares you for:
Every module ends in real work, not a quiz. By the end of the 30 days you will have shipped a GenAI application with your own hands, the kind of project that proves what you can do long after the program is over.
If you are a graduate ready to learn, build and prove what you can do, this is your way in. It takes only a few minutes to apply, and every batch is kept small so every graduate is truly seen.