Generative AI & LLMs

About this course

A deep technical course on large language models: tokenisation, embeddings and transformer internals; vector databases and retrieval-augmented generation (RAG); and prompt engineering through to deploying GenAI applications.

What you will learn

1. 1

   Course 3.1 — LLM Architecture Internals

   • •Foundations Review
   • •Tokenization Deep Dive
   • •Embeddings
   • •Transformer Architecture
   • •LLM Training Pipeline
   • •LLM Inference Optimisation
   • •LLM Limitations & Challenges
2. 2

   Course 3.2 — Vector Databases & RAG

   • •Foundations Review
   • •Vector DB Fundamentals
   • •Vector DB Architecture
   • •Document Processing & Chunking
   • •RAG Architecture Patterns
   • •RAG Evaluation & Quality
   • •Advanced RAG Patterns
3. 3

   Course 3.3 — Prompt Engineering & Apps

   • •Foundations Review
   • •Prompt Engineering Fundamentals
   • •Advanced Prompting Techniques
   • •ChatGPT App Development
   • •AI Productivity Tools
   • •Deploying GenAI Apps