Guide · Artificial intelligence
Artificial intelligence – a guide to the lessons
What artificial intelligence is, how it began, how a machine learns, how AI is programmed and how it helps in the Internet of Things. The course is written for primary and secondary school students and for teachers.
Modules 1 and 2 don't require programming. Module 3 requires Python basics, and module 4 the course Arduino and ESP32 or micro:bit. Module 5 is again without programming.
- From grade 5
- Without programming (modules 1, 2 and 5)
- Python and IoT (later modules)
1 What artificial intelligence is
Six lessons without programming – for students from grade 5, for a computer science lesson or a club.
1. What is artificial intelligence?
The difference between an ordinary program and AI, machine learning and the model, where you already use AI.
Open the lesson →2. History of artificial intelligence
From Turing and the Dartmouth meeting to Deep Blue, AlphaGo and chatbots.
Open the lesson →3. The Turing test
The imitation game, whether chatbots pass it, and the “Chinese room” thought experiment.
Open the lesson →4. Types of artificial intelligence
Narrow and general AI, image and speech recognition, generative AI, robots.
Open the lesson →5. Who makes artificial intelligence
How an AI system is made, professions, companies, open models and AI in Serbia.
Open the lesson →6. How to use AI tools
A good question (prompt), checking answers, privacy and fake videos.
Open the lesson →2 How a machine learns
Data, learning from examples, neural networks without formulas – and the first model without programming. Still without writing code.
7. How a machine learns
Examples instead of rules, training and testing, accuracy and overfitting.
Open the lesson →8. Data – food for AI
Features and labels, how much data is needed, bias and errors in data.
Open the lesson →9. Teachable Machine
The first model with a camera in the browser, without an account – and experiments that “break” it.
Open the lesson →10. Neural networks
An artificial neuron as “voting with weights”, layers and deep learning; try it yourself.
Open the lesson →11. How chatbots work
Predicting the next word, how a chatbot is made and why it sometimes makes mistakes.
Open the lesson →3 Programming artificial intelligence in Python
For students who know Python basics (lists, loops, functions): from rules to a neural network. All programs have been checked by running them, and the real output is shown with them.
12. Getting ready: Python and data
Installing libraries, a table of fruit in a CSV file, reading it and the first chart.
Open the lesson →13. Rules or learning
The same task with a rule “by eye” and with a threshold the program learns by itself.
Open the lesson →14. The nearest neighbor algorithm (k-NN)
Distance, the neighbors' vote and scaling – without libraries, only lists and loops.
Open the lesson →15. The perceptron
A neuron that learns the functions AND and OR by itself – and why it can't do XOR.
Open the lesson →16. A neural network and scikit-learn
Recognizing handwritten digits: almost 98% accuracy and an error table.
Open the lesson →17. Project: a recommendation system
Recommending books from the reading list based on the ratings of similar students.
Open the lesson →18. Ready-made models and APIs
Saving and loading a model, APIs, a local language model and the API key.
Open the lesson →4 Artificial intelligence and the Internet of Things
AI on the ESP32 and micro:bit: sensors collect data, the model learns on the computer, and the board itself makes the decisions. Prior knowledge: the course Arduino and ESP32 or micro:bit.
19. AI and the Internet of Things
The chain sensor → data → model → decision → actuator; AI in the cloud and on the device.
Open the lesson →20. ESP32 collects data
The ESP32 measures, you label the state, Python saves the table; cleaning the data.
Open the lesson →21. A model from Python on the ESP32
A decision tree learns in Python, and Python converts it into C++ for the ESP32 by itself.
Open the lesson →22. micro:bit recognizes gestures
The micro:bit learns by itself and recognizes still, waving and shaking (k-NN in MicroPython).
Open the lesson →23. TinyML
How much “intelligence” fits into a small chip: calculating the size of a model, quantization, tools.
Open the lesson →5 Artificial intelligence and society
Big questions without programming: does AI think, how can it be fair and safe, and what is its future. Each lesson has an activity for discussion in class (a debate, the ethics traffic light, a letter to yourself).
24. Is AI conscious?
Intelligence and consciousness, why a chatbot sounds as if it feels, three points of view and a debate in class.
Open the lesson →25. Ethics and safety of AI
Bias, fake videos and voice scams, privacy, copyright, responsibility and laws.
Open the lesson →26. The future of AI
What is already happening, how jobs are changing, skills that stay important and three possible paths.
Open the lesson →6 Final project and review test
A project in three options – without programming, in Python or with a device – and a review test with 20 questions and two practical tasks.
✎ Related pages
AI in learning programming
How to use AI assistants in learning, what is allowed in competitions and tests.
Open the page →Python
The language used most in artificial intelligence – needed for module 3.
Open the guide →Arduino and ESP32
Sensors and devices – the basis for module 4 (AI and the Internet of Things).
Open the guide →