Algorithms · Flowcharts · Logic · Binary · Problem Solving
Hiding unnecessary detail to focus on what matters.
What AI actually is, how machine learning differs from traditional programming, and its real limits.
Counting with only 0 and 1, and why computers use two symbols.
True, false, and the AND, OR, and NOT operators that let computers make decisions.
The many different jobs built on computational thinking, and how the skills in this course connect to them.
What "the cloud" really is — renting computers in data centres, and why it changed everything.
Two correct algorithms can differ wildly in speed — how to judge which solution is better.
Making files smaller — lossless and lossy compression, and the clever tricks behind ZIP, JPEG, and MP3.
Tables, records, fields, and queries — how organised data answers questions in milliseconds.
Finding and fixing errors in algorithms with tracing and testing.
Breaking big problems into smaller, solvable parts.
The hidden computers inside washing machines, cars, and toasters — small, dedicated, and everywhere.
Scrambling data so only the intended recipient can read it — the maths that keeps secrets secret.
Privacy, fairness, and responsibility — the questions computer science cannot answer with code alone.
Programs that wait — how clicks, key presses, and timers drive modern software.
How operating systems organise, store, and retrieve data on storage devices using file systems, paths, and permissions.
The gatekeepers that decide which network traffic is allowed in and out of a device or network.
Drawing algorithms with symbols: terminators, processes, decisions, and arrows.
Naming a block of instructions so you can reuse it — the most powerful idea in programming.
The physical parts you can touch, the programs you cannot — and how the operating system connects them.
Base 16 — the compact way programmers write binary, from colour codes to memory addresses.
From mechanical calculators to smartphones — how computing grew from room-sized machines to your pocket.
The CPU, memory, and storage — what actually happens inside the box when a program runs.
How data gets into an algorithm, is processed, and comes back out.
A data structure built from nodes and pointers — how it differs from an array, and why that trade-off matters.
Storing many values under one name, finding them by index, and looping over them all.
The tiny circuits that perform AND, OR, and NOT — the physical building blocks of every computer.
Viruses, worms, ransomware, and trojans — how malicious software spreads, and how to defend against it.
Loops inside loops, IFs inside IFs — combining structures to express richer logic.
How computers connect, what packets and IP addresses are, and how a message crosses the world.
Modelling the world as objects with data and behaviour — the design pattern behind most modern software.
Strong passwords, phishing, personal information, and your digital footprint — staying smart online.
How the operating system manages processes, memory, files, and devices so that applications can run at all.
Arithmetic, comparison, and the rules for combining values into expressions a computer can evaluate.
Spotting similarities and repetition to solve problems faster.
Keyboards, printers, and webcams — how external devices plug in, and the driver software that makes them speak.
What programming languages are, why there are so many, and how code becomes something a computer can run.
The agreed rules that let different devices and networks understand each other, from HTTP to TCP/IP.
Writing algorithms in structured plain language — precise enough to code, free of any language's rules.
How a function can call itself to solve problems by breaking them into smaller, identical sub-problems.
Count-controlled and condition-controlled loops, and avoiding infinite loops.
Pixels, resolution, colour depth, and sound sampling — how pictures and music become binary.
Character codes, ASCII, and Unicode — how letters and emoji become numbers a computer can store.
Linear search and binary search — two ways to find things, and why one is dramatically faster.
IF–THEN–ELSE decisions, conditions, and simple logic.
Putting steps in the right order and why order changes the result.
Putting data in order with bubble sort and merge sort, and why order is worth the effort.
Cells, formulas, and charts — the everyday tool that turns raw numbers into answers.
Two fundamental data structures — the stack (last in, first out) and the queue (first in, first out) — and where they appear in real systems.
Hard drives, SSDs, flash, and optical discs — how bits are kept safe, and how to choose between them.
Test data, edge cases, and test plans — how programmers prove their code works before users find out it doesn't.
Websites, browsers, servers, and URLs — what actually happens when you visit a page.
Running an algorithm by hand, one line at a time, to see exactly what it does — and where it goes wrong.
Named boxes that store values, and how algorithms remember things.
How developers track changes to code over time, collaborate without conflicts, and roll back mistakes using tools like Git.
Step-by-step instructions, precision, and why computers need them.
Ethernet, Wi-Fi, Bluetooth, and mobile data — how connections differ, and when to choose which.