Python for AI - Crash course

This crash course provides a complete and practical introduction to Python with a focus on the skills required for AI, automation, and data-driven applications. You begin by learning the essentials of Python syntax: variables, expressions, numerical operations, and string manipulation while working inside a Jupyter Notebook environment. This includes creating and running code cells, organizing notebooks, and writing your first executable Python programs.

You then progress into Python’s core data structures—lists, tuples, dictionaries, and sets—understanding how to store, access, transform, and manage collections of data using indexing, slicing, sorting, and set logic. These structures are the backbone of effective programming and are heavily used in AI and data science tasks.

The course then builds deeper programming skills through conditions, branching, loops, and functions. You will learn to design reusable logic, handle errors through exception handling, and grasp the basics of object-oriented programming by creating your own classes and objects. These concepts provide the thinking patterns necessary for writing clean, scalable code.

Next, you will work extensively with real-world data. You will practice reading and writing files (text, CSV, JSON) and learn to use Pandas for tabular data analysis and NumPy for numerical computations. These libraries form the foundation of modern machine learning workflows.

Finally, you will explore data collection methods through REST APIs and web scraping using the requests library and BeautifulSoup. By the end of the course, you will be able to extract, clean, and prepare data—an essential skill in building AI solutions.