GenAI • LLMs • Agents • ML • DS

GenAI Learning Hub & Dashboard

Use this index page as your central dashboard for the whole Generative AI module: overview, data science, machine learning, LLMs, prompting, agents and agentic AI. Every card below opens a dedicated teaching page.

🧠Concepts + Intuition
🧪Interactive teaching pages
🪄Designed for students
Core & overview Data science ML & models LLMs & agents

Dashboard

Start with the GenAI Overview, then follow the recommended pathway — or jump straight to any topic you want.

🗺️ GenAI Overview & Roadmap Start here

Big-picture map of the whole course: how generative AI, data science, ML, LLMs and agents fit together.
Core concept Visual roadmap

What is Generative AI?

Explore what makes an AI “generative”, from text and images to music and code, with everyday examples.
Foundations Use cases

📊 Data Science — Part 1

The role of data science in AI: data pipeline, exploration, simple statistics and why data quality matters.
Data pipeline Fundamentals

📈 Data Science — Part 2

Go deeper into data cleaning, feature preparation, basic visualisation and how DS supports ML and GenAI.
Cleaning & features Bridge to ML

🤖 Machine Learning Basics

Understand classic ML ideas: supervised vs unsupervised, training data, evaluation, and how ML connects to GenAI.
Core ML concepts Model mindset

💬 Large Language Models (LLMs)

What an LLM really is: tokens, parameters, context windows and why models like ChatGPT can “reason”.
Transformers Capabilities & limits

🪄 Prompting & Cues

How to talk to LLMs effectively: structures, cues, examples, system prompts and simple chain-of-thought ideas.
Prompt patterns Practical tips

🕹️ AI Agents

Move beyond one-off prompts: agents that plan, call tools, use memory, and complete multi-step tasks.
Tools & planning From chat to action

🌐 Agentic AI & Autonomy

From simple agents to agentic systems: orchestration, autonomy, evaluation, and safety/oversight ideas.
Agentic patterns Risks & guardrails