Adrian Dane

Welcome to the Free Python 30‑by‑30 Course

Time is often the hardest resource to find when learning a new skill. The idea behind this course is simple: if you set aside thirty minutes each day for thirty days, you can build a working knowledge of Python. Consistent practice and small victories accumulate. Each day has a focused lesson with reading, examples and suggested practice. As you read and type along, you will begin to think in Python. You will see how simple ideas combine to form programs, and you will gain the confidence to explore further.

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Why Learn Python? 🐍

Python is not a new language. Guido van Rossum began working on it in the late 1980s as a successor to the ABC language, and he released version 0.9.0 in early 1991. He wanted a simple, readable language that would let hobbyists and professionals explore ideas without the fuss of compilation and boilerplate. The name was inspired by the comedy series Monty Python’s Flying Circus.

From the start, its syntax used indentation and whitespace to mark blocks, which makes code resemble structured prose. Python 1.0 appeared in 1994 with features such as lambda expressions, map and filter, and basic support for object‑oriented programming. Python 2.0 followed in 2000 with list comprehensions, garbage collection, Unicode support and other improvements. In 2008, Python 3.0 was released; this major revision introduced cleaner syntax, better input/output handling and a more consistent standard library, paving the way for sustainable growth.

Since those early releases the language has grown in popularity and capability. It remains one of the most widely taught introductory languages and frequently appears near the top of industry popularity surveys. Python’s design encourages readability and modularity. It supports multiple programming paradigms, including procedural, object‑oriented and functional approaches. Its dynamic typing and late binding make it well suited to rapid prototyping. A large standard library and a vibrant ecosystem of third‑party packages allow you to solve problems without reinventing common tools. You can write a small utility to rename files on your laptop or build a large‑scale web application—Python scales across domains.

The uses of Python span many industries. People use it to build websites and back‑end services, automate data processing and system administration, analyse data, develop machine‑learning models and test software. Scientists, social scientists, educators and journalists rely on Python to compute statistics, visualise information and share reproducible workflows. Companies such as Netflix use it to power recommendation engines, and researchers use it with packages like TensorFlow and PyTorch to train deep neural networks. Because it is approachable and free, non‑programmers can pick up Python to automate everyday tasks, from updating spreadsheets to organising photos.

What You'll Learn & Build

By the end of this course you will know how to set up Python, work with built‑in types, control flow and functions, structure programs with modules and classes, read and write files, handle common data formats, write command‑line tools and incorporate basic testing and debugging. In the final module you will examine a real script used on Whatchan.co.uk to gather football match listings and present them as a daily table. You will see how Python powers the scraping logic and HTML generation behind that site and learn how to adapt and refactor it. This gentle, progressive journey will give you a solid foundation and a sense of what Python can do.