Programming Basics (Python)

As part of the lesson, students are introduced to Python’s history of developing the programming language, its place in today’s tech ecosystem and its wide applicability across different industries. The theoretical presentation covers Python syntax fundamentus, interpreter operating mechanisms and basic computational principles that form the basis for developing algorithmic solutions. The practical part learns the configuration of the work environment and develops the first interactive app, integrating data input and output (input/print) principles to ensure user-system interaction.

By the end of the topic, students will have acquired the basic skills needed to work with the Python environment and will be able to independently implement simple software code lines.

This topic focuses on the program’s decision-making capabilities and logic building. In the theoretical part, students will learn the elements of Boolean algebra (AND, OR, NOT) and conditional constructions (if, Elif, else) needed to build logic circuits. The practical part will develop an app with decision-making logic, such as a simple password-checking system or a conversational bot that provides different answers depending on the user’s choices. By the end of the topic, students will have acquired theoretical knowledge of logical operators and algorithm branching principles in decision-making processes.

In this topic, we’ll look at the management structures you need to manage repetitive tasks effectively. In the theoretical part, we will analyze the syntax and application of the for and While cycles and the control of iterations. In the practical part, students will create programs that keep you running, such as forcing you to re-enter your password while it’s correct, or making games include cycles. At the end of the topic, students will understand the construction of cyclic algorithms and theoretical aspects of iteration management required for effective control of program flow.

In this lesson, we’ll learn about methods for organizing and manipulating information in the Python environment. The theoretical part will analyze the most relevant data structures: lists (lists), strings (tuples), and dictionaries (dictionaries), explaining their differences and application scenarios. In the practical part, students will develop code for a simple system, such as a to-do list or a phone book, where records can be added and deleted. At the end of the topic, students will theoretically be familiar with the organizational principles of different data structures in computer memory and will be able to argue for the choice of the most appropriate data type.

In this topic, we’ll look at the critical role of functions in programming, focusing on logically splitting code. In the theoretical part, we’ll explain the definition of functions, parameter transfer, return values, and the concepts of variable visibility areas (scope). In the practical part, students will refactor the code of previous classes by dividing it into logical blocks and separating specific activities into individual functions. At the end of the topic, students will understand the importance of code modularity, the variable area of vision (scope) theory, and the building blocks of functional programming.

This topic focuses on basic principles of object oriented programming (OOP) and code organization in modules. In the theoretical part, we will introduce classes, objects, characteristics and methods, as well as explain the import of external modules. In the practical part, students will define the first objects that model the real world, giving them characteristics and behaviors. At the end of the topic, students will theoretically understand the paradigm of object-oriented programming, being able to define and distinguish classes, objects, methods and their role in software architecture.

This lesson will include a written examination aimed at assessing students’ theoretical understanding of the basic Python programming principles learned in the first part of the course. The test will include questions about syntax, data types, control structures (cycles and conditions), function design and basic concepts of object oriented programming. Students will need to demonstrate the ability to read and analyze snippets of code, explain terminology, and choose the most appropriate solutions in theoretical situations without having to use a computer. Passing a successful test confirms that the student understands the logic behind software development and is willing to learn more complex topics.

This topic introduces students to professional development standards and collaboration tools. The theoretical part will look at PEP8 style guidelines, fault correction (Debugging) techniques and version control systems (Git) basics. In the practical part, students will learn how to create and manage Git repositories to ensure change tracking, collaboration, and secure preservation of project history. At the end of the topic, students will be able to write better quality code and manage versions of it.

This module integrates state-of-the-art artificial intelligence (AI) tools into the coding process to lift productivity. The theoretical part will showcase the Human loop (Human-in-the-loop) methodology and the role of AI assistants in explaining logic and generating standard code. In the practical part, students will use AI tools to correct errors and develop solutions, improving their productivity and learning speed. At the end of the topic, students will be able to critically evaluate and efficiently use AI-generated code.

This topic introduces the field of data analysis by introducing the Panda Library as a key tool for effective information processing within Python. In the theoretical part, let’s look at the basic principles of data structuring by explaining the structure of DataFrame and series objects, as well as the most common problems in raw data. In the practical part, students will load real datasets from Excel and CSV files using simple missing value processing and data filtering. At the end of the topic, students will be able to technically load external data sources and apply basic cleaning techniques to convert raw information into an analytical format.

This topic focuses on getting practical insights from organized data and presenting them visually. In the theoretical part, we’ll look at data collection methods and the capabilities of visualization libraries in creating professional graphics. The practical part will apply basic modelling methods, such as trend line analysis, to identify legal relationships and visually present found relationships. At the end of the topic, students will be able to use the data to draw conclusions and create visible schedules.

In this lesson, students will learn web data acquisition techniques to automate information from public sources. In the theoretical part, we’ll look at Web scraping techniques and connecting scripts to communication systems. The practice will develop scripts that collect data and send email alerts based on new

information. At the end of the topic, students will have a functional automated monitoring tool developed.

This lesson combines system connectivity with text analysis using API and NLP methods. In the theoretical part, we’ll look at interactions with application interfaces (APIs) for external data acquisition and NLP basics for text structure analysis. In the practical part, students will integrate API data and conduct sentiment analysis into text data. At the end of the topic, students will be able to connect different systems and perform basic level text content analysis.

In this topic, we’ll focus on improving file management skills to drive automation of typical office jobs. In the theoretical part, we’ll analyze the optimization of workflows and the use of scripts to generate documents. In the practical part, students will develop solutions to generate formatted Excel reports and automatically create PDF documents. By the end of the topic, students will have created automated workflows that replace manual and repetitive administrative work.

This topic provides an introduction to developing web solutions using the Streamlit tool. in the theoretical part, we’ll explain how to connect the user interface to the Python code logic that processes data in the background, while in the practical part, students will create a simple app, such as a calculator or questionnaire, that works in an internet browser, so at the end of the topic, students will be able to turn their Python script into a working webpage.