Course Content
Module 2 – Introduction to Python Programming
In this Introduction to Python module, learners explore Python’s clear, readable syntax and powerful features. Beginning with installation and a simple “Hello, World!” script, you will progress through variables, control flow and functions using step-by-step examples. By the end, you will be equipped to write your own Python programmes, automate routine tasks and tap into an extensive library ecosystem for real-world projects.
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Lesson 1: Introduction to Python & Setup
Lesson 2: Python Real-World Applications
Lesson 3: Getting Started with Python
Lesson 4: Installing Python Packages and Modules
Summary
Quiz: Introduction to Python and Setup
Lab Activity : Intro to Python
Module 3 – Variables, Data Types and Basic Operations
In the Variables, Data Types and Basic Operations in Python module, learners explore how to store and manage data using variables, master fundamental types such as integers, floats, strings and booleans, and perform arithmetic, comparison and logical operations step by step. Clear explanations, real world examples and hands on exercises guide you through writing and debugging code. By the end of this module, you will be ready to build dynamic Python programs and automate everyday tasks.
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Lesson 1: Python Variables
Lesson 2: Basic Arithmetic Operations
Lesson 3: Working with String
Summary
Quiz: Variables, Data Types and Basic Operations
Lab Activity : Variables, Data Types and Basic Operations
Module 4 – Control Flow – Conditions and Loops
Control flow structures determine the order in which your program’s code executes. With conditional statements, you can make decisions and execute certain code blocks only when specific conditions are met. Loops allow you to repeat actions efficiently without writing redundant code. In this module, we will explore fundamental control flow concepts in Python in a step-by-step manner, similar to Microsoft’s learning curriculum. By the end, you’ll understand how to use if, elif, and else statements (including nested conditions) for decision-making, how truthy and falsy values work in Boolean logic, how to construct for loops (using range() and iterating over collections), how to use while loops along with loop control statements (break and continue), and how to leverage list comprehensions and generator expressions for concise looping. Finally, we’ll apply these concepts in a practical exercise to build an interactive decision-making system. Each section below includes explanations, code examples, and mini-exercises to reinforce the concepts, all formatted for clarity and easy follow-along.
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Lesson 1: if, elif, else statements and nesting
Lesson 2: Truthiness, boolean logic, and chaining comparisons
Lesson 3: for loops with range() and iterating over collections
Lesson 4: while loops and loop control (break, continue)
Lesson 5: List comprehensions and generator expressions
Summary
Quiz: Control Flow – Conditions and Loops
Lab Activity : Building Calculator
Module 5 – Functions and Code Organisation
Imagine you need to clean up a messy data set or send a personalised email to each customer. Instead of writing the same steps over and over, you can create a function and call it whenever you need. In this lesson on Functions and Code Organisation, you will learn how to define functions, pass and return information, document your work and group related code into modules for easy reuse and maintenance.
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Lesson 1: Defining and calling functions
Lesson 2: Function Arguments: Positional, Keyword, Default, and Variable-Length
Lesson 3: Return values and early exits
Introduction to Python Programming (Copy 2)

Installing Python Packages and Modules

Ever found a brilliant Python tool that solves your problem perfectly but you had no idea how to install it? That is where installing Python modules comes into play. Whether you are just starting out or managing serious projects, knowing how to set up packages and tools is a core part of using Python effectively. In this guide, we will walk you through the basics, from virtual environments to pip, helping you get the most out of Python’s powerful package system.

Key Terms

Let us begin by understanding the tools and terms you will come across:

  • pip: This is Python’s go-to installer. From version 3.4 onwards, pip comes bundled with Python.

  • Virtual environment: Think of it as a separate workspace for your project so packages do not interfere with others. venv is Python’s built-in tool for this since version 3.3.

  • virtualenv: An earlier tool similar to venv, mainly for older Python versions before 3.4.

  • Python Package Index: This is an online collection of packages you can install using pip.

  • Python Packaging Authority: This group maintains packaging tools and documentation. You can find their work on GitHub.

  • distutils: An older build tool that laid the foundation for current packaging systems. Although it is being phased out, you may still encounter it.

Basic Usage

You will use the command line to install packages. Here is how to get started:

python -m pip install SomePackage

To install a specific version, use:

python -m pip install SomePackage==1.0.4

For a minimum version, use quotes to avoid shell issues:

python -m pip install "SomePackage>=1.0.4"

If the module is already installed, running the command again does nothing unless you explicitly ask for an upgrade:

python -m pip install --upgrade SomePackage

Want more on pip’s capabilities? Check out the Python Packaging User Guide.

For working in virtual environments, use the venv module. Create the environment, activate it, then install packages as shown above.

How Do I …?

Here are quick answers to common questions.

… install pip for Python versions before 3.4?

Earlier versions do not bundle pip, so you will need to set it up manually. Follow the guidance in the requirements section of the Python Packaging User Guide.

… install packages for just myself?

Use the –user option:

python -m pip install --user SomePackage

On Windows, use the py launcher:

py -3.4 -m pip install SomePackage

Common Installation Issues

Installing Python into the System on Linux

Linux distributions often include Python. Installing packages into this system version requires root access and may conflict with your system tools. To avoid trouble, use a virtual environment or install packages just for your user.

Pip Not Installed

If pip was not installed with Python, you can add it with:

python -m ensurepip --default-pip

Additional help for installing pip is available in the packaging guide.

Installing Binary Extensions

Python used to rely on source-based installs, meaning users had to compile extensions manually. Now, many packages offer pre-built “wheel” files, making installs quicker and simpler. Wheels especially help Windows and macOS users. For scientific software and other compiled packages, this trend is making things more accessible.

For more on binary extensions, see the Binary Extensions Guide.

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