Python is the working language of AI and data science. Almost every tool you'll use later, from notebooks to machine learning libraries, is written for it, so fluency here pays off in every module that follows.
You'll start with core Python: variables, data types, loops, functions, and the structures you'll use daily. Then the module moves to the two libraries that sit at the centre of the ecosystem: NumPy for fast numerical work on arrays, putting the vectors and matrices from the last module into code, and pandas for loading, filtering, grouping, and reshaping tabular data.
With these skills you'll be ready for the next module, Version Control & Notebooks, which covers how to track your work with Git and run analysis in Jupyter.
A fast overview of what Python is, how its syntax reads, and why it became the default language for data work.
A hands-on first pass through variables, data types, conditionals, loops, and functions, enough to start writing real scripts.
Loading data into DataFrames, filtering and sorting rows, grouping, and working through a realistic analysis end to end.