Provided by: WiDS Datathon Team
This tutorial is aimed to introduce basic data science skills and concepts to datathon participants with little to no background in statistics or computer science. In these Jupyter Notebook tutorials, you will learn to use the Python programming language to explore fundamental statistical concepts and become familiar with various data values, structures and manipulation techniques.
If you do not already have Anaconda installed on your computer, it is highly recommended that you first follow the "Anaconda Installation Guide" to download and install Anaconda to access your Jupyter Notebooks. This will allow you to download and work interactively through your own copy of the tutorial notebooks, and it will set you up with an environment to tackle your datathon challenge should this be the data science platform you choose to use.
| Notebook | Summary |
|---|---|
| Anaconda Installation Guide | Instructions for Anaconda installation & accessing tutorial notebooks on Jupyter |
| 01_Intro_to_Jupyter | Introduction to Jupyter Notebooks & Python |
| 02_Intro_to_DataStructures | Python packages, data structures & basic statistics |
| 03_More_DataStructures | Dictionaries, Matrices & Pandas data manipulation |
- Jupyter Notebook modules from the UC Berkeley Data Science Modules Program licensed under CC BY-NC 4.0
- ESPM-163ac: Lab1-Introduction to Jupyter Notebook by Alleana Clark
- Data 8X Public Materials for 2022 by Sean Morris
- LEGALST-123: Anaconda Installation Guide by Keiko Kamei
- Composing Programs by John DeNero based on the textbook Structure and Interpretation of Computer Programs by Harold Abelson and Gerald Jay Sussman, licensed under CC BY-SA 3.0