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CHIPY Practical Technology Programme
A 24-week practical programme across software, networking, robotics and web, taught to three age groups and ending in an integrated capstone project.
- weeks
- 24
- tracks
- 4
- lessons
- 24
Tracks
Software, data and AI
Python programming, data analysis, machine learning and professional practice.
10 lessons · 5 modules
Networking and security
How networks work, cabling, IP addressing, network design and security.
5 lessons · 3 modules
Electronics, robotics and IoT
Circuits, microcontrollers, sensors, actuators and connected devices.
5 lessons · 4 modules
Web development
HTML, CSS, JavaScript and back-end APIs.
4 lessons · 2 modules
Lessons
Open any lesson to see its objectives, materials and what you will build. Full notes are for enrolled students.
10 lessons
Week 1 · Software, data and AI
Your computer is a workshop
Every builder needs a workshop: a place to keep tools, materials and projects. For the next 24 weeks your computer is that workshop. Today you set it up properly and run your first program.
Week 2 · Software, data and AI
Variables, input and calculations
A calculator forgets everything after each sum. A program can remember values, ask people for information and reuse results. Today you build a trip-cost calculator a class treasurer could actually use.
Week 3 · Software, data and AI
Decisions and loops
Real programs react: if the password is right, let the user in; while the game is not over, keep playing. Today you give your programs a brain (decisions) and stamina (loops) and build a number-guessing game.
Week 4 · Software, data and AI
Functions and debugging
Good builders make parts they can test separately: a wheel, a motor, a switch. In code those parts are functions. Today you build the first version of Project 1, a grade calculator, out of small functions — and learn how professionals hunt bugs.
Week 8 · Software, data and AI
Lists, dictionaries and files: a student record manager
A program that forgets everything when you close it is not much use to a school. Today you learn to keep many records, give each value a name, and save them in a file — then you build the first real Chipy project: a record manager a teacher could actually use.
Week 17 · Software, data and AI
Data analysis: cleaning, statistics and charts
Your sensors can take a reading every few seconds — thousands a day. Raw numbers mean nothing until someone cleans them, summarises them and shows them. That someone is a data analyst, one of the fastest-growing jobs in tech. Today you analyse a day of classroom light readings.
Week 19 · Software, data and AI
What is AI? Rules, data, learning and bias
"AI" is everywhere: in phone cameras, M-Pesa fraud checks, YouTube recommendations, chatbots, translation apps. But what is actually going on inside? Today you find out that a lot of AI is a simple idea — learn a pattern from examples — done at a very large scale. You will build the smallest possible learning program, and see how it can go wrong.
Week 20 · Software, data and AI
Machine learning with scikit-learn: training and testing a classifier
Last week your program learned one number. Today you use the same tools professional data scientists use — scikit-learn — to train a model that tells three species of iris flower apart from four measurements. It is a classic first project because the data is real, small and free.
Week 23 · Software, data and AI
Testing, debugging and using AI coding tools responsibly
Professional developers do not just write code — they prove it works, with automated tests. Today many of them also use AI assistants. That makes tests more important, not less: an AI can write code that looks right and is wrong. Today you fix buggy code with tests, call an "AI API" from Python safely, and judge an AI's suggestion the way a professional would.
Week 24 · Software, data and AI
Capstone: plan, build and present an integrated project
Twenty-three weeks ago your computer became a workshop. Since then you have written Python, crimped cables, built a network, programmed an Arduino, made websites, analysed data, trained a model and connected a sensor to the web. The capstone is where you show what you can do with all of it: a small, real project that solves a problem you care about.