Python for High School - Grade 9

Python for High School - Grade 9 is Carpathica Academy's English-language edition of our flagship Liceu course, built directly from Romania's official Computer Science national curriculum for Grade 9 (Anexa nr. 8, specialised curriculum, theoretical track, real profile, mathematics-informatics specialisation, intensive Computer Science classes, approved under Ministerial Order OMEC no. 4370/2026).

The program covers, in full, all three content domains and all six general competences (CG1-CG6) of the official curriculum: conceptual data organisation (linear model - list, stack, queue), problem-solving strategies (program design, number processing, systematic sequence generation, sorting) and data storage and code organisation (subprograms, an introduction to object-oriented programming, text files, Tkinter graphical interfaces, the list class).

Unlike the official version, which splits teaching hours between Python and C++, our course is taught exclusively in Python - the language required today in industry, in research, at university admission and in the computing olympiads we prepare students for (Cybersecurity and Artificial Intelligence). Everything taught in C++ is covered just as rigorously in Python, and the time this frees up is reinvested in systematic debugging, testing with assert, version control with Git and GitHub, algorithm visualisation, responsible use of AI coding assistants, and one integrating capstone project: the Digital Classroom app.

The time reserve the official curriculum sets aside for remediation, consolidation and extension is built into every session through a short recap at the start, and concentrated further in two dedicated studio sessions.

The course is organised into 12 units, delivered in a single 2-hour guided session per week - 35 sessions in total, calculated precisely against the official 2026-2027 school-year calendar for Satu Mare county (10 September 2026 - 17 June 2027), with no sessions during school holidays or public holidays. Each session blends concept explanation with hands-on practice, so that the 4 weekly hours allocated by the official curriculum are covered in full, in an intensive format:

1. Fundamentals, active recap and orientation (4 sessions): setting up the working environment, your first program, creating a GitHub account and your first commit; variables, types, operators, reading and writing data, conditionals, loops - recapped at a brisk pace; systematically reading Python error messages.
2. Designing a program (4 sessions): analysis, design, implementation, testing and debugging; pseudocode, flowcharts and code; console, graphical and file interfaces; an intuitive introduction to algorithm efficiency.
3. Subprograms I (3 sessions): defining and calling subprograms, parameters, return values, local and global variables, predefined maths functions, testing subprograms with assert.
4. Number processing (3 sessions): operations on the digits of a number, divisors, the greatest common divisor (Euclid's algorithm), the Sieve of Eratosthenes, fast exponentiation, conversions between number bases - with explicit links to the number theory studied in mathematics.
5. Studio - free project and recap (1 session): a scientific calculator with custom functions, paired code review, and catch-up time for students who need it.
6. The linear conceptual model - the list (3 sessions): the characteristics of the stack, the queue, the direct-access and sequential-access list, illustrated through real situations.
7. Python's list class (3 sessions): every operator and predefined method, mutability and the difference between assignment and copying, applied on top of the stack and queue models from the previous unit.
8. Systematic sequence generation and sorting (4 sessions): sequences with given properties, recurrence relations (including the Fibonacci sequence), selection sort, frequency-list sort and bubble sort - visualised step by step.
9. Studio and the responsible use of artificial intelligence (1 session): catch-up and consolidation, plus exercises in critically using an AI coding assistant, verifying and explaining any suggestion it offers.
10. Text files and an introduction to object-oriented programming (3 sessions): opening, reading, writing and closing files; predefined classes and objects; persisting data for the Digital Classroom app.
11. Graphical interfaces with Tkinter (3 sessions): window, label, button, text box, frame, canvas, layout management; building the Digital Classroom interface.
12. Final project (3 sessions): fully integrating lists, files, subprograms, object-oriented elements and the graphical interface into the Digital Classroom app, a public presentation and self-assessment.

Every unit explicitly covers the corresponding general and specific competences from the official curriculum (CG1-CG6). The time reserve the curriculum sets aside for remediation, consolidation and extension is built into every session through a short recap at the start, and concentrated further in the two studio sessions (units 5 and 9).

By the end, students can identify, explain, apply, analyse and evaluate the conceptual and operational models of the official Grade 9 Computer Science curriculum, and can design, on their own, custom Python algorithms and programs to solve real problems.

Concretely, students can: read and explain any Python error message and debug a program systematically; design a program starting from a requirement, using pseudocode, flowcharts and testing with normal and edge cases; write and test subprograms with parameters, return values, and local and global variables; apply number-processing algorithms (greatest common divisor, Sieve of Eratosthenes, fast exponentiation, base conversions); use the stack, queue and frequency-list conceptual models and Python's list class with all of its operators and methods; systematically generate sequences of values and apply sorting algorithms; read and write text files; use basic object-oriented programming concepts; build graphical interfaces with Tkinter.

Beyond the official curriculum, students can: use Git and GitHub to version and publish their projects in a portfolio; write assert-based tests for their own code; critically use an AI coding assistant, verifying and explaining any suggestion it offers; build and present a complete application with a graphical interface, files and persistent data.

Throughout the year, students build, test and commit to Git more than 15 mini-projects: a time-unit converter, a grade classifier with a decision table, a scientific calculator with custom functions, a tool for checking prime numbers and computing the greatest common divisor, a queue simulator, a shopping-list editor using every method of the list class, a recurring-sequence generator, a sorting algorithm visualised step by step, and a grade register saved to a text file.

The final project is Digital Classroom, a complete desktop application built with Tkinter, which manages students, grades and attendance, saves data to text files, and uses lists, subprograms and basic object-oriented programming concepts. Students present the app publicly and publish the full source code in their personal GitHub portfolio.

Why only Python, when the official curriculum also includes C++?
Because Python is the language used today across industry, research, and most university introductory courses, and its simple syntax lets you focus on algorithmic thinking. Everything taught in C++ - from subprograms to number processing and sorting - is covered just as rigorously in Python, with no loss of content. More importantly, Python is the language required in the computing olympiads we prepare students for at Carpathica Academy, such as the Cybersecurity Olympiad (OSC) and the National Artificial Intelligence Olympiad (ONIA), where C++ offers no real advantage. All the competences and content of the official curriculum are covered in full - just through Python, not through both languages.

Does this course follow the official national curriculum?
Yes, in full. Every unit is explicitly mapped to the content domains and to the general and specific competences (CG1-CG6) from Anexa nr. 8 of OMEC no. 4370/2026, for Grade 9, specialised curriculum.

Do I need prior programming experience?
No. The first few weeks actively recap the fundamentals, so any Grade 9 student can start the course.

What happens with the content that goes beyond the official curriculum?
Git and GitHub, assert-based testing, systematic debugging and the responsible use of AI coding assistants are deliberate additions that prepare students for real programming practice, beyond the curriculum's minimum requirements.

What's the final project?
Digital Classroom, a desktop application with a Tkinter graphical interface that manages students, grades and attendance, and saves data to text files.

What are the confirmed dates for this group?
The group starts on Friday, 11 September 2026, and ends on Friday, 18 June 2027, with one guided 2-hour session per week, following the official school-year calendar for Satu Mare county, with no sessions during school holidays or public holidays.