Introduction to Python for Data Science

Python is the primary language of data science. This module builds the programming fundamentals you will use in every subsequent module — not as a general programming survey, but with a focus on the patterns that appear most often in data work.

By the end of this module, you will be able to write functions that transform data, use strings to clean and parse text, organize information in lists and dictionaries, and work with the objects and methods provided by data science libraries.

Lessons

  1. Intro to Python — Variables, data types, arithmetic, comparison operators, and basic input/output. Your first runnable Python program.
  2. Functions — Defining and calling functions, parameters and return values, and writing reusable, readable code.
  3. Strings — String operations, slicing, formatting, and the methods most useful for working with text data.
  4. Conditional Logic — if/elif/else statements and boolean expressions for branching logic.
  5. Lists — Creating, indexing, slicing, and iterating over lists; list comprehensions for data transformation.
  6. Dictionaries — Key-value storage, iteration over items, and using dictionaries to represent structured records.
  7. Objects — What objects are, how to call methods, and how Python's object model applies to the libraries you'll use throughout the course.
  8. Module Assessment — A coding assessment that tests your ability to write Python functions and work with core data structures.