Python Introduction

What Is Python?

Python is a widely used, general-purpose programming language known for being easy to read and quick to learn. It was created by Guido van Rossum and first released in 1991, and over the past three decades it has grown into one of the most popular languages in the world — powering everything from personal scripts to the backend of major websites.

Python is commonly used for:

• Web development (server-side)
• Software development
• Data analysis and mathematics
• Automating repetitive tasks (system scripting)
• Artificial intelligence and machine learning

What Can Python Do?

• Build the server-side logic behind web applications
• Connect to databases, and read, write, or modify files
• Handle large datasets and perform advanced mathematical operations
• Automate workflows alongside other software
• Support both rapid prototyping and full production-ready systems
• Power machine learning models and AI-driven applications

Why Choose Python?

• Cross-platform — runs the same way on Windows, macOS, Linux, and even small devices like the Raspberry Pi.
• Readable syntax — code reads almost like plain English, which makes it approachable for beginners.
• Concise — many tasks take fewer lines of code in Python than in other languages.
• Interpreted — code runs line-by-line without a separate compile step, so you can test ideas instantly.
• Flexible — supports procedural, object-oriented, and functional programming styles, so you can pick the approach that fits your project.

Good to Know

• The current major version is Python 3, and that’s what this series will use throughout.
• You can write Python in a simple text editor, but many developers prefer an Integrated Development Environment (IDE) like PyCharm, Thonny, or VS Code — especially once a project grows beyond a single file.

Python’s Syntax vs. Other Languages

Python was designed with readability as a priority, drawing some inspiration from both natural language and mathematical notation:

• Line endings: Python uses a new line to end a statement, instead of a semicolon or parenthesis.
• Code blocks: Python uses indentation (whitespace) to define scope — for loops, functions, and classes — rather than curly braces { }. This means consistent indentation isn’t just a style choice in Python; it’s part of the language’s structure.

How Python Helps With AI

Python has become the default language for artificial intelligence and machine learning work, for a few practical reasons:

• A mature ecosystem — libraries like NumPy and pandas handle the heavy numerical and data work, while frameworks like TensorFlow, PyTorch, and scikit-learn provide ready-made tools for building and training models, so developers rarely start from scratch.
• Fast experimentation — because Python is interpreted and quick to write, researchers can test an idea, see the result, and adjust it almost immediately — a big advantage when developing and tuning AI models.
• Strong data-handling tools — AI depends on large volumes of data, and Python’s libraries make it straightforward to clean, transform, and analyze datasets before they ever reach a model.
• A large community — because so many AI practitioners already use Python, there’s a constant stream of tutorials, pretrained models, and open-source projects to build on rather than reinvent.
• Readable code — AI projects are often collaborative and long-running; Python’s clear syntax makes it easier for teams to understand and maintain complex model code over time.

This is one of the main reasons Python is worth learning even outside traditional software development — it’s the language most AI tools and tutorials assume you already know.

What’s Next

In the next part of this series, we’ll set up Python on your computer and write your very first program.