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Introduction to Python Programming (Cohort 3)

Categories Programming, Python
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What I will learn?

  • Set up Python and your development environment, then master core coding skills—variables, data types, functions, conditions, loops and organising reusable code.
  • Automate everyday jobs by working with files and folders, using popular libraries and driving web tasks with PyAutoGUI and Selenium.
  • Build smarter workflows to process Excel and PDF documents, send automated emails and alerts, and schedule your scripts to run on their own.
  • Bring it all together in a mini-project to create a complete automation tool, learn error-handling and debugging, and map out your career-growth path.

Course Curriculum

Module 1 – Getting Started with Python
introduced the fundamentals of Python, giving beginners a clear understanding of how the language works and how to start writing simple programs. Python was highlighted as a beginner-friendly language with simple syntax, making it easy to read and write code.

  • Lesson 1: Introduction to Python & Setup
  • Lesson 2: Python Real-World Applications
  • Lesson 3: Introduction to Python – Syntax
  • Summary
  • Quiz: Getting Started with Python
  • Lab Activity : Getting Started with Python

Module 2 – 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.

Built-in Functions in Python
This is for revision and for getting you up to speed for the next day

Day 1 Summary

Module 3 – 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.

Day 2 Summary

Module 4 – 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.

Day 3 Summary

Module 5 – Automating a Daily Task with Conditionals & Loops

Day 4 Summary

Module 6 – Working with Files and Folders
In this lesson, we will learn how to manipulate files and directories using Python. We’ll explore common file operations using the os module, and see how the pathlib module provides an object-oriented way to handle file paths. We’ll also use the glob module for pattern-based file searches and learn file I/O operations for text, CSV, and binary files. Additionally, we’ll introduce the calendar and time modules to work with dates and timestamps. Finally, an interactive lab will tie everything together by automating a folder backup and cleanup task. Follow the step-by-step sections below for each subtopic, try out the code examples, and explore the guided lab at the end.

Module 7 – Error Handling and Debugging Techniques
In this lesson, we will learn how to handle errors in Python programs and how to debug code effectively. Errors are inevitable, but knowing how to manage them ensures our programs don't crash unexpectedly. We will cover the difference between syntax errors and exceptions, how to use try, except, else, and finally blocks to catch and handle exceptions, and how to raise your own exceptions (including creating custom exception classes). We’ll also explore debugging strategies: using simple print statements or the logging module to trace your program’s execution, and using Python’s interactive debugger pdb to step through code. By following best practices for error handling and debugging, you can write resilient, maintainable code. Throughout this lesson, try the examples and exercises to practice these techniques.

Mini Project: Build your own Automation Tool
The project incorporates two common automation tasks – Contact Management and Student Tasks Tracking

Resources

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Free
Free access this course
  • Level
    Beginner
  • Total Enrolled
    26
  • Duration
    24 hours
  • Last Updated
    November 13, 2025
  • Certificate
    Certificate of completion

A course by

Technisaur Admin
A
AA
F
Fatima
Python Trainer
sfawan

Material Includes

  • Downloadable code samples

Requirements

  • Basic computer skills and familiarity with file navigation
  • A computer running Windows, macOS or Linux with an internet connection
  • Python installed from python.org
  • Choice of code editor or IDE such as VS Code, Jupyter Notebook or PyCharm
  • Willingness to learn by doing and follow step-by-step labs

Tags

Data Types & Control Flow Email Automation Error Handling & Debugging PDF & Excel Automation Python CLI tools Python file handling Python programming Scheduling & Task Automation

Target Audience

  • Complete beginners with no prior programming experience
  • Professionals who want to automate repetitive tasks
  • Students studying IT or data-focused disciplines
  • Anyone interested in learning Python for web, data or process automation

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