Introduction to Data Science
This module sets the foundation for everything that follows. Before writing a line of data analysis code, you need to understand what data science is, how practitioners work, and how to set up the tools and workflows that make that work possible.
The module introduces the data science workflow — from raw data to insight — and establishes the professional habits (version control, reproducible notebooks, and AI collaboration) that will serve you throughout this course and in practice.
Lessons
- Intro to Data Science — What data science is, the roles within the field, and an overview of the end-to-end data science workflow.
- Intro to Google Colab and Jupyter Notebooks — The notebook environment used throughout this course: cells, markdown, code execution, and working with files in Colab.
- Setting Up GitHub — Version control for data scientists: creating a GitHub account, initializing a repository, and committing your notebooks.
- Pair Programming with AI — How to use AI coding assistants effectively: prompting strategies, reviewing AI output, and when to trust versus question suggestions.
- Module Assessment — A hands-on notebook assessment covering the tools and concepts introduced in this module.