Module 1: Introduction to AI, ML, Deep Learning, GenAI, and LLMs

Understand what AI, machine learning, deep learning, generative AI, and large language models actually are, how they differ, and where they fit in the 2026 AI stack.

Module 1: Introduction to AI, ML, Deep Learning, GenAI, and LLMs

What this module gives you

Build a rock-solid mental model of the AI landscape so that every later module makes sense. By the end of this module you will be able to draw the AI to ML to DL to GenAI to LLM hierarchy from memory and explain when each one is the right tool.

Skills you will pick up

Distinguishing AI, machine learning, deep learning, generative AI, and LLMs
Reading AI news without getting confused by buzzwords
Identifying which problems suit which technique
Spotting marketing dressed up as "AI"

Why it matters in production

In 2026 every product team is "doing AI." Most of them confuse machine learning with LLMs and waste months. The first skill of an AI engineer is calling the right tool by its right name and choosing it for the right reason.

Lessons in this module

Recap

You can now place any AI buzzword in its correct ring, distinguish discriminative from generative, name the 2026 LLM landscape, and decide when an LLM is and is not the right tool.

Ready to start?

Open Lesson 1.1: What is AI, really? (and what it is not)

Start first lesson