You will build a working understanding of how Python makes decisions, repeats actions, and organizes data. You will start with conditional statements — learning to use if, else, and elif to control what your program does based on specific conditions. From there, you will move into loops, using for and while to handle repetitive tasks and iterate through data efficiently. Once you are comfortable with control flow, lists are introduced as your first data structure: you will learn to create, modify, slice, and apply common list methods to manage ordered sequences of information. The module closes with a capstone lesson on how Python actually executes code — you will trace execution order line by line and learn to recognize and avoid common pitfalls. By the end of this module, you will be writing Python code that uses conditionals, loops, and lists together to solve practical programming problems.

You will develop the ability to write Python code that is reusable, organized, and built to scale. You will start with functions as the foundational building block — learning the syntax, writing functions with and without parameters, working with return values, using Python's built-in functions, and applying the DRY principle to eliminate unnecessary repetition in your code. You will then explore variable scope, understanding how variables behave differently inside and outside functions and what local and global scope mean in practice. With functions and scope firmly in place, the focus shifts to object-oriented programming — you will learn to define classes as blueprints for objects, add attributes and methods, and create instances of your own custom classes. The module closes by broadening your toolkit: you will work with built-in and external modules, learn how to import them, manage packages using pip, and create your own module from scratch. By the end of this module, you will be applying functions, classes, and modules together to write structured, maintainable Python programs.

You will build a solid, practical understanding of Python's core data structures and how to work with them. Starting with a reference cheat sheet, you will explore lists, dictionaries, tuples, and sets — learning the unique properties of each, how their ordering and mutability differ, and when to reach for one over another. You will go deeper into dictionaries, working through real-world applications and more advanced operations, before moving on to sets and how Python distinguishes between ordered and unordered collections. The module then shifts to algorithms — you will implement sorting and searching on lists, compare the efficiency of linear and binary search, and understand how algorithmic choice affects the speed of data retrieval. The module closes with a decision framework that brings everything together, giving you a structured way to evaluate which data structure best fits a given problem. By the end of this module, you will be able to choose, implement, and justify the right data structure for practical programming challenges.

You will develop the skills to read, handle, and resolve errors in Python programs with confidence. You will start by understanding Python exceptions — what they are, how to interpret them, and which ones you are most likely to encounter. From there, you will learn to handle exceptions gracefully using try-except blocks, working through real-world examples that show you how to prevent program crashes and manage errors cleanly. The focus then shifts to debugging: you will work with print debugging and interactive debuggers, stepping through code, inspecting variables, and pinpointing exactly where things go wrong. A toolkit of strategies used by experienced developers rounds out the debugging lessons before the module brings exception handling and debugging together in a final practical lesson. By the end of this module, you will be constructing try-except blocks, applying debugging techniques, and approaching code errors with a structured, methodical mindset.

You will learn two practices that are fundamental to writing code you can trust and maintain over time. You will start with unit testing using the pytest framework — understanding why testing matters for code quality, writing and running your own tests, working with fixtures, and keeping your test files well-organised. The module then moves to version control with Git and GitHub: you will set up Git, learn the relationship between Git and GitHub, track changes, and work through the core commands that let you manage your codebase with confidence. In the final lesson, you will bring your Python skills together in a capstone programming activity, applying what you have built across the course to solve a practical problem. A role play closes the module, giving you the opportunity to explain your project and development workflow out loud. By the end of this module, you will be writing and running unit tests with pytest and using Git to track and manage your code.