AI for Everyone
No maths, no code, no jargon. What AI actually is, what it can and cannot do, and how to use it well. Written for students, teachers, and anyone who keeps hearing about it.
Resources
Everything we teach, free to download.
Course notes written for Fulcrum, plus the slides from sessions we have delivered. Open any of them in your browser or save the PDF. No sign-up, no email wall, take them and use them.
Where to start
If you are not sure which to read first.
Nine documents is a lot to land on at once, and a few of them assume things the others teach. This is the order we would read them in. Nothing here is compulsory, and if you already know a stage, skip it.
Start here
No maths, no code, no background assumed.
- 1AI for Everyone15 slides
What AI actually is, what it can and cannot do, and how to study with it without letting it do the studying.
- 2AI Basics, Day 1
The seminar version of the same ground, plus how models learn and how images become numbers.
- 3AI Basics, Day 2
Where AI is applied, what the jobs actually involve, and how research gets done.
The core ideas
Everything after this leans on these two. Read them in order.
- 4Machine Learning: Foundations14 slides
Model, loss, optimiser, and how to tell a real result from a flattering one. The vocabulary the rest of the field assumes.
- 5Deep Learning: Foundations26 slides
Neurons to backpropagation to attention to language models. The longest core deck, and the one that unlocks the specialised ones.
Pick a direction
Both branches stand on their own. Take whichever matches what you want to build.
- 6Computer Vision: Foundations17 slides
How a machine gets from a grid of numbers to something worth calling perception.
- 7Computer Vision: Advanced16 slides
Detection, segmentation, vision transformers, diffusion and video. This one says outright that it assumes the Foundations deck.
- 8Artificial Intelligence in Medicine37 slides
Every specialty, what has actually been built, and where it fails. Clinicians can come straight here after Start here, without the two core decks.
The frontier
For people already building models.
- 9AI for Experts15 slides
Scaling behaviour, evaluation that survives scrutiny, alignment, and the open problems worth your time. Assumes backpropagation and transformers.
We add to this page as we write. Articles and further notes are on the way, so it is worth checking back or asking on Discord what is coming next.
Course notes
Written for this programme.
Original material, released under CC BY 4.0. Reuse it, teach from it, adapt it for your own students, just keep the attribution.
Computer Vision: Foundations
How a machine gets from a grid of numbers to something worth calling perception. Written for people meeting the field for the first time.
Computer Vision: Advanced
Detection, segmentation, transformers, generative models and video: the architectures behind modern vision systems, and where each one breaks.
Machine Learning: Foundations
What it means for a machine to learn from data, the handful of ideas that recur everywhere, and how to tell a real result from a flattering one.
Deep Learning: Foundations
Neural networks from the single neuron up to the transformer: backpropagation, what depth actually buys you, how attention replaced recurrence, and what happens inside a large language model.
Artificial Intelligence in Medicine
Every specialty, what has actually been built, what works in a clinic rather than a paper, and where it fails. Written for clinicians, students, and researchers entering the field.
AI for Experts
For people who already build models: scaling behaviour, training at the frontier, evaluation that survives scrutiny, alignment, and the open problems worth your time.
Something missing?
We write these in response to what people actually ask for. Tell us the topic you wish existed and we will put it on the list.
Seminar slides
From sessions we have run.
The decks we actually taught from, published as-is.
AI Basics, Day 1
Foundations and the big picture: why AI broke open in the 2020s, how models learn, transformers, and how images become numbers.
Delivered with Leafclutch Technologies Pvt. Ltd., March 2026
AI Basics, Day 2
Skills, applications, careers and research: automating tasks with Python, the branches of AI, where it is applied, and how research actually gets done.
Delivered with Leafclutch Technologies Pvt. Ltd., March 2026
Other guides
Not part of the AI curriculum, but useful.
Many of the people we work with are also applying to study or work abroad. This has nothing to do with artificial intelligence and sits outside the study path above, published here for the same reason as everything else: it is useful, and it is free.
PTE Academic: Complete Course & Preparation Guide
A walkthrough of every task in the PTE Academic English test, covering the format updated in August 2026: all three sections, how scoring works, an eight-week study plan, and a test-day checklist.
In the field
Where this material has been taught.
Free AI training for grades 9 and 10
Shree Pardi Secondary School
Pokhara-17, Pardi, Kaski, Nepal · 27 May 2026
A full session for school students on using AI as a study tool rather than a shortcut, covering Wolfram Alpha for maths and science, and the honest question the students themselves keep asking: “Why use AI to study? Doesn't it make us dumb?”
- Using AI to explain difficult topics in simple ways
- Wolfram Alpha for maths and science
- Where AI weakens independent and critical thinking
- The key balance: learn with AI, don't let AI learn for you
AI Basics, a two-day workshop
Leafclutch Technologies Pvt. Ltd.
Nepal · March 2026
Two days from first principles to practice: why AI broke open in the 2020s, how models actually learn, and what a career and a research pipeline in the field really look like.
- Foundations: from the Turing test to generative AI
- Mechanics of learning: linear regression to neural networks
- The generative leap: attention, transformers, and LLMs
- How images become numbers: computer vision basics
- Automating everyday tasks with simple Python
- AI careers, role responsibilities, and how research gets done
How to Publish Research as an Undergraduate
Fulcrum open webinar
Online
55+ students, promoted by word of mouth alone
Our first open session, and the one that showed us how much unmet demand there was. Most participants rated their familiarity with academic publishing at 1 or 2 out of 5 beforehand; an hour later that had shifted sharply. Health professionals, including nurses, joined alongside engineering and science undergraduates.
- Finding a research question worth asking as an undergraduate
- Structuring a paper a journal will take seriously
- Choosing a venue and preparing a submission
- Surviving peer review and revisions
- Where AI genuinely helps in medicine and clinical research
Publishing research during an engineering degree
Engineering college session
Nepal
100+ students
A session for undergraduates who want a publication before they graduate: how to find a question worth asking, what reviewers actually look for, and how to get through submission without a supervisor holding your hand.
- Finding a research question as an undergraduate
- Structuring a paper a journal will take seriously
- Choosing a venue and preparing a submission
- Surviving peer review and revisions
Want a session?
We will come and teach this.
Schools, colleges, and organisations, if you can get the room and the students, we will run the session. Free, as always.