Python Intro (Fall 2025 / RSM338)
Python is a high-level programming language known for its readability and versatility. It has a rich ecosystem of data science libraries, making it an excellent choice for data analysis tasks, from basic descriptive statistics to complex predictive modeling. This workshop introduces you the basics of Python programming and data analysis.
What To Prepare
In this workshop, we use Google Colab as our coding environment, so all you need is a Google Account. Google Colab is a hosted Jupyter Notebook service that requires no setup to use and provides free access to computing resources.
Session 1. Programming Basics
- Slides
- Notebook:
- Readings & exercises: Section Basics in the Python Intro Crash Course.
- Prepare for the next session: Section Data Analysis in the Python Intro Crash Course.
Session 2. Data Analysis Basics
- Notebook:
- Readings & exercises: Section Data Analysis in the Python Intro Crash Course.
Resources
- Learning
- Programming with Python by Software Carpentry
- Python Intro by Google
- Python for Beginners by Microsoft
- Python for Data Analysis, 3E by Wes McKinney (creator of pandas library)
- Python Data Science Handbook by Jake VanderPlas
- Numpy Quick Start
- 10 Minutes to Pandas
- Python Style Guide
- Free Cloud Computing (other than Google Colab)
- UofT JupyterHub (choose Jupyter or JupterLab for Python)
- Anaconda Cloud (choose the free tier)
Back to MDAL Computing Page