AI & ML Foundation Course
From “what is AI?” to how ChatGPT writes its answers. Thirteen short, illustrated lessons with hands-on demos and a quiz at the end of each one — written for people starting from zero. About 2.6 hours in total, at your own pace. Free for everyone, no registration.
13
Lessons
2.6
Hours, self-paced
6
Tracks
13
End-of-lesson quizzes
Six tracks, in order
Each lesson builds on the one before. Follow the path in order, or jump to whichever topic you need — the lessons are written to stand alone as well.
Lessons 1–2
Start here
What AI is and the different ways machines learn.
Lessons 3–4
Machine learning
Choosing algorithms, and the difference between learning and using.
Lessons 5–7
Deep learning
Neural networks, and how they let computers see and read.
Lessons 8–10
Transformers and LLMs
The ideas behind ChatGPT, Claude and Gemini.
Lessons 11–12
Generative models
Networks that create brand-new images, faces and more.
Lesson 13
AI on AWS
Mapping every idea in this course to real cloud services.
All thirteen lessons
Plain-language explanations with diagrams and analogies — no maths degree needed. Click any lesson to open it.
AI vs ML vs Deep Learning vs Generative AI
How the four terms fit inside each other, with one banking example.
10 min
2Types of Machine Learning
Supervised, unsupervised, semi-supervised and reinforcement learning.
12 min
3Machine Learning Algorithms
Which algorithm to use for which problem, plus the interview favourites.
15 min
4Training vs Inference
Learning from data versus using what was learned.
8 min
5Deep Learning Fundamentals
Neurons, activation, backpropagation and the tricks that make deep nets work.
20 min
6Computer Vision
How computers turn pixels into understanding.
12 min
7Natural Language Processing
How computers read, understand and generate human language.
12 min
8Transformers and Attention
The architecture behind ChatGPT, Claude and Gemini.
15 min
9How LLMs Work: The Intuition
A story-first walkthrough: patterns, next-token prediction and tokens.
12 min
10How LLMs Work: Under the Hood
Embeddings, self-attention, generation and the three stages of training.
15 min
11Generative Adversarial Networks (GANs)
Two networks compete: a faker and a judge.
8 min
12Variational Autoencoders (VAEs)
Compress data into a smooth map, then generate from it.
10 min
13AWS Services for AI, ML and GenAI
Which AWS service belongs to which category, and which to learn first.
10 min
Read, try, discuss, check
Read
Plain-language explanations with diagrams, analogies and real examples.
Try
Small interactive demos: roll a ball down a loss curve, watch attention work, generate text token by token.
Discuss
Classroom activities you can do alone or with others, with suggested answers to check yourself against.
Check
A short quiz at the end of every lesson, with instant feedback and explanations.
Your reading progress is saved in your own browser only — nothing is sent to us, and there is nothing to sign up for.
Who this course is for
Complete beginners
Students and professionals who keep hearing these terms and want them to finally make sense.
Engineers moving into AI
Developers, DBAs and analysts who need the concepts underneath the tools before picking a specialism.
Managers and decision-makers
Anyone who has to judge an AI proposal and wants to know what is real and what is marketing.
Independent training material by Pushpjeet Cholkar. Not affiliated with, endorsed by or sponsored by Amazon Web Services, OpenAI, Anthropic, Google or any other vendor named in it.
Where to go after this
AWS Cloud Foundations
Our other free course — eleven modules on networking, Linux, cloud concepts, IAM, VPC and the AWS services worth knowing, with labs and a 50-question final test. Lesson 13 here leads naturally into it.
Instructor-led for your team
The same material delivered live, tailored to your stack, with labs in your own environment and someone in the room to answer the awkward questions.
Start with lesson one
Ten minutes, and the four terms everyone confuses will stop being confusing.

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Contact
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