The training starts by briefly describing Python’s position in the landscape of programming languages. The trainees start by installing the Anaconda manager and learn how to create a new Python environment for their project. They will also learn how to install Python packages which is necessary for the rest of the training. At this point in the lesson, everybody is guaranteed to have a working installation of Python and Anaconda, so we are ready for the second part: programming in Python.
The second part of the training introduces the Python programming language. It alternates short explanations and short exercises that cover basic data types, how to work with lists and dicts, functions, classes, objects, and list comprehensions. It ends with longer exercises in which the trainee can practice and digest what they’ve just learned.
Finally, the training goes in depth on list comprehensions; list comprehensions are useful in data science because they transform collections of data. They are suitable for an introductory class because they use simple expressions and their expressive power allows a ramp up to more advanced exercises.