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The curriculum

From atoms to AI.
Nothing left out.

Most courses skip the hard parts. Not this one.
28 lectures that change how you see technology forever — not what buttons to press, but why everything works the way it does, from the physics up.

Contents · 28 lectures
01Atoms
02Electrons
03Magnets
04Light
05Sensors
06Motors
07Transistors
08Amplifiers
09Circuits
10Power
11Data
12Logic
13Memory
14FPGAs
15Computers
16Control
17Robotics
18Systems
19Linux
20Python
21Networks
22Websites
23Servers
24Security
25Audio
26Vision
27Learning
28Intelligence
The parallel.
One journey.
Two discoveries.

As you build the robot, you discover how your own brain works. Every component has a biological twin. Every circuit has a neural equivalent. By the end, you understand two of the most complex systems ever built — and why they look so much alike.

The connection.
One system.
Not ten subjects.

Physics, electronics, computing, software, networks, and AI are not separate subjects — they are layers of the same thing. This course teaches them as they actually are: connected, dependent on each other, and only fully understood together.

The foundation.
Learn once.
Understand everything after.

This isn't a course about today's technology. It's a way of thinking about all technology — past, present, and future. Once you have the foundations, every new tool, language, or system you encounter has a place in the framework you built from scratch.

All 28 lectures

The complete curriculum.

Each lecture. The technology. The neuroscience.

Part 1 — Physics & Electronics8 lectures
01 · Atoms
The physical substrate
Sub-atomic particles, forces, and the matter everything is made of.
↔ From physics to chemistry to biology to brains
02 · Electrons
Voltage, current, resistance
Ohm's Law, voltage dividers, power. The language of electronics.
↔ Neurons at rest — resting potential and passive membrane properties
03 · Magnets
Fields and forces
Electromagnetism — moving charges create force at a distance.
↔ The physics governing both wires and ion channels
04 · Light
Electromagnetic spectrum
EM radiation — the same spectrum that powers WiFi and human vision.
↔ Why the retina evolved to detect this specific slice
05 · Sensors
Transduction
Heat, light, pressure, sound → electrical signal. The world becomes data.
↔ Photoreceptors, hair cells, and mechanosensors
06 · Motors
Electromagnetism as motion
Turning electrical signals into physical force. Coils, piezos, actuators.
↔ Muscles and motor neurons — chemical synapses as actuators
07 · Transistors
The universal switch
Voltage controls current. The fundamental building block of digital logic.
↔ Action potentials — neurons as biological switches
08 · Amplifiers
Gain and feedback
Op-amps — the chip that amplifies anything. The building block of almost every analog circuit.
↔ Why a whisper from your nervous system can move your whole body
Part 2 — Circuits & Digital Logic5 lectures
09 · Circuits
Integrated circuits
How ICs are made and the Braitenberg vehicle — a robot with no code.
↔ Simple sensorimotor loops — reflex arcs
10 · Power
Regulated supply
Voltage regulators and stable power for complex mixed systems.
↔ Cellular energy efficiency and metabolic homeostasis
11 · Data
Analog to digital
Why 0s and 1s are sufficient. The moment the world becomes information.
↔ Rate coding vs. timing coding — how neurons encode information
12 · Logic
Digital computation
Five logic gates from which any computation can be built. Arithmetic from switches.
↔ Excitatory and inhibitory neurons as biological logic gates
13 · Memory
Persistent state
How information persists. Flip-flops, flash, and why memory shapes everything above.
↔ LTP and NMDA channels — the molecular basis of memory
Part 3 — Computing & Control4 lectures
14 · FPGAs
Programmable logic
Hardware you can rewrite. Verilog, HDL, and the NB3 Hindbrain board.
↔ Neural plasticity — adaptive circuits for computation
15 · Computers
From gates to programs
ALU, microcontrollers, assembly, C. The gap between hardware and software, closed.
↔ Is your brain really like a computer? The answer is more interesting than yes or no
16 · Control
Feedback and PID
Negative feedback, H-bridge, servos. How systems maintain targets under disturbance.
↔ Motor control — the cerebellum and proprioceptive feedback
17 · Robotics
Autonomous systems
Sensors, motors, microcontroller, behaviour. The NB3 drives and reacts.
↔ The architecture of behavioural complexity in nervous systems
Part 4 — Systems & Networks7 lectures
18 · Systems
Operating systems
What actually happens when a computer turns on — and how software and hardware communicate.
↔ Brain systems — sensory, motor, memory, learning
19 · Linux
Open interfaces
The kernel, the terminal, the file system. The OS that runs the world.
↔ Your nervous system runs most of its processes without your knowledge — just like an OS
20 · Python
Thinking programmatically
Python, packages, virtual environments. Software that controls hardware.
↔ Abstraction and decomposition — computational thinking
21 · Networks
Internet protocols
TCP/IP, WiFi, SSH. How packets travel and your robot talks to the world.
↔ Neural protocols — signal propagation in biological networks
22 · Websites
HTML and CSS
Structure and style. How the visual layer of the internet is built from text.
↔ How the brain structures and presents visual information
23 · Servers
HTTP and the web
Requests, responses, hosting. Your robot becomes a web server.
↔ Your neurons communicate the same way — one sends, one responds
24 · Security
Encryption
Hash functions, public keys, proof-of-work. Security as a physical constraint.
↔ Pattern recognition and secure signalling in biology
Part 5 — Perception & Intelligence4 lectures
25 · Audio
Sound to understanding
Microphones, signal processing, frequency analysis. Meaning from 1D data.
↔ Hair cells, sound localisation, auditory scene analysis
26 · Vision
Pixels to perception
Image processing, feature detection, the gap between data and seeing.
↔ How your brain processes what your eyes send — and how remarkably similar it is to a camera
27 · Learning
Reinforcement learning
How systems improve through interaction. Reward signals and clicker training.
↔ Dopamine as reward signal — the neuroscience of habit
28 · Intelligence
Neural networks and AI
NPUs, TensorFlow, LLMs — and what remains genuinely mysterious.
↔ A worm has 302 neurons. You have 86 billion. What does the difference buy?
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Inside the lectures

A taste of what
each lecture opens.

Two lectures, shown in depth. The technology concept, the biological parallel, the hands-on task — and the insight that connects them.

Part 1 — Physics & Electronics Lecture 07
Transistors

Everything in your phone, your laptop, and every piece of modern electronics is built from one idea: a switch you control with electricity. This lecture explains what a transistor is physically, how it works, and why its invention changed the world more than almost anything else in the last century.

What you learn to think
Why vacuum tubes worked — and why silicon replaced them
How a tiny voltage controls a large current (amplification)
Why billions of switches fit on a fingernail
How switching speed became the measure of computational power
Technology
The MOSFET

A gate voltage controls current through a channel. Off or on. Zero or one. The physical implementation of binary logic in silicon.

Neuroscience
The Action Potential

Your neurons are biological switches. On or off, fire or don't fire — the same binary principle as a transistor, just implemented in biology instead of silicon.

Hands-on task
Switch a motor with your sensor

Wire the photoresistor from Lecture 05 through a MOSFET to your motor. For the first time, your robot responds to the world. Sense → switch → action. Every computer ever made is a variation on this loop.

"There are more transistors on a modern CPU than there are neurons in a human brain. Both are switches. The difference is 50 years of miniaturisation — and we still don't fully understand either one."

Part 2 — Circuits & Digital Lecture 12
Logic

This lecture answers one of the most surprising questions in all of computing: why are two numbers enough? How did we get from voltage — a continuous physical quantity — to AND, OR, NOT, and ultimately to every calculation a computer has ever performed? The answer is both simpler and more profound than most people expect.

What you learn to think
Why binary representation is sufficient for any calculation
How NAND gates alone can implement any logic function
How addition emerges from switches — no mathematics required
Why all software ultimately reduces to gate operations
Technology
Logic gates

AND, OR, NAND, NOR, XOR — five gates from which every digital circuit can be constructed. The complete vocabulary of computation.

Neuroscience
E and I circuits

Excitatory and inhibitory neurons implement biological logic. Your brain decides by combining signals through AND/OR/NOT operations — in wetware.

Hands-on task
Build a circuit that adds two numbers

Using physical AND, XOR, and OR chips, construct a circuit that adds two numbers and shows the result as light. No processor, no code — just gates. Arithmetic from first principles.

"Every calculation your phone has ever done — every photo processed, every message encrypted, every game rendered — reduced, at the bottom, to gates switching. This lecture is the moment that becomes real."

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