A project-based course in three levels for students aged 15 and up. Students learn the core of pre-university computer science (hardware, networks, databases, machine learning, programming and algorithms) in Python, with a Raspberry Pi Pico on the desk to make every idea tangible.
Instructor: Narek Tigranyan, university lecturer, Computer Science teacher and Founder/CTO of UZLIN Technologies
This course teaches how computing systems work and how to solve problems with code. Instead of studying computers on paper and learning to program separately, students do both on one real device, the Raspberry Pi Pico 2 W. It has processor cores, memory, communication buses, a wireless radio and security hardware, so abstract topics become tangible from the first week.
The three levels cover the same areas at growing depth. Level 1 builds vocabulary and understanding, Level 2 applies it in code, SQL and algorithms, and Level 3 asks students to analyse, compare and evaluate. No experience is needed to start.
Computer Science teaches the concepts and the code; Robotics is the hands-on engineering. They share the Pico and reinforce each other: a robot built in Robotics can become this course’s final project. Each course can also be taken on its own.
| Level | Students mostly | Typical tasks |
|---|---|---|
| 1 Foundation | Recall and understand | Define, state, outline, label a diagram |
| 2 Intermediate | Apply ideas, write and trace code | Explain, trace, construct an algorithm, design a schema, write SQL |
| 3 Advanced | Analyse and evaluate | Compare, evaluate, justify, apply ideas to a new case study |
| Goal | By the end of the course, a student can… | Built in |
|---|---|---|
| G1 | Explain how computing systems work, using correct terminology. | All levels |
| G2 | Apply computational thinking to break down and analyse problems. | Levels 1 and 2 |
| G3 | Write, test and debug working programs in Python, including object-oriented ones. | Levels 2 and 3 |
| G4 | Design, evaluate and justify a solution, including its ethical impact. | Level 3, final project |
Each level covers the same areas at greater depth. It ends with a level project and an assessment, and the assessment result decides whether the student continues to the next level.
Students learn the vocabulary and core ideas of computing: what is inside a computer, how data is stored, how networks and databases are organised, and what machine learning is. They write their first programs.
Parts of the CPU; memory types (RAM, ROM, cache); secondary storage; the role of the operating system; cloud computing
Binary and hexadecimal; how text, images and sound are stored; units of storage
Network types (LAN, WAN, PAN), network devices, topologies, wired versus wireless
Tables, records, fields, primary and foreign keys
What machine learning is; supervised, unsupervised and reinforcement learning; ethics
Decomposition, abstraction, pattern recognition, flowcharts
Variables, data types, selection, loops, strings, one-dimensional arrays
Define, state, outline and label a diagram.
Students apply what they know: they trace and write algorithms, design databases and query them with SQL, explain how data crosses a network, and build their first machine learning models and classes.
The fetch–decode–execute cycle, pipelining, GPU versus CPU, lossy and lossless compression, Boolean logic, truth tables, logic circuits
Polling versus interrupts, multitasking, control systems with sensors and actuators
IP addressing, packet switching, TCP versus UDP, protocols and layers, firewalls, encryption basics
Entity–relationship diagrams, normalisation to third normal form, SQL: SELECT, JOIN, GROUP BY, INSERT and UPDATE
Linear regression, k-nearest neighbours, decision trees, clustering
Two-dimensional arrays, stacks and queues, functions and parameters, reading and writing files, linear and binary search, bubble and selection sort, tracing algorithms
Classes, objects, constructors, encapsulation, getters and setters, UML class diagrams
Explain, trace, construct an algorithm, design a database schema and write SQL.
Students analyse and evaluate: they compare algorithms and database models, judge security measures and model performance, design larger object-oriented programs, and apply everything to an unfamiliar case study.
Compilers versus interpreters, operating system scheduling algorithms, deeper memory management
Digital certificates, public and private key encryption, network segmentation, evaluating security measures
Nested queries and aggregates, transactions and ACID, NoSQL and data warehouses, choosing between database models
Data preprocessing, neural networks and CNNs, reinforcement learning, judging how well a model performs
Big O analysis, recursion, comparing algorithms
Inheritance, polymorphism, abstract classes, interfaces, design patterns
Linked lists, binary search trees and their traversals, hash tables, sets
A new real-world scenario each year, studied in advance, where students apply ideas from the whole course to a context they haven’t seen before
Analyse, compare, evaluate and justify, including the ethical impact of a solution.
Every student finishes with a complete computational solution to a real problem, chosen by the student and taken through the full development process.
| Stage | What the student does |
|---|---|
| Planning | Finds a real user and problem, and agrees success criteria with them |
| Design | Plans the data, algorithms and structure of the solution |
| Development | Builds the solution, using techniques from all three levels |
| Testing | Tests systematically against the success criteria |
| Evaluation | Judges the result with the user, and reviews its ethical impact: privacy, safety and consent |
Starter pathways mirror products UZLIN builds:
A small web app with a database that solves a real problem for a real user.
A Pico-based device, or a robot from the Robotics course, documented as a full solution.
A model trained on collected data and evaluated for accuracy and bias.
Sensors to a database to a dashboard, with a security review.
Progress is measured continuously, and every piece of evidence goes into the student’s portfolio. Each level ends with an assessment whose result decides whether the student continues to the next level.
| Component | What it shows |
|---|---|
| Level projects | A working program or device at the end of each level, demonstrated in class |
| Practical tests | Short checks of concepts and code, used to spot gaps early |
| Level assessment | At the end of each level; decides whether the student continues to the next level |
| Final project | A complete solution with documentation and an ethics review |
| Portfolio | All projects, code and reflections, ready to show schools and universities |
| Item | Detail |
|---|---|
| Software | Python 3, Thonny or VS Code, SQLite; free and cross-platform |
| Hardware | Raspberry Pi Pico 2 W with a basic sensor set, shared with the Robotics course |
| Course materials | Level notes, practice problems and project templates |
Lessons are inquiry-led and hands-on: a short explanation, then building and testing. Ethics runs through the whole course rather than sitting in one topic: privacy in networks, bias in machine learning, consent in the final project. Students credit every source they use, including code and AI assistants, and the final project must be their own work.