© Colin Conrad 2020 This is a public repository of my teaching materials from the 2020 iteration of INFO 6270: Introduction to Data Science at Dalhousie University. This course is designed to bring students with no programming experience up to the point of having basic data science capabilities using Python technologies. In this repository you will find supporting lab materials and exercises for 10 labs, all of which are in a Jupyter Notebook format. I have not provided the answers to the exercises (for various reasons) but these are avaliable upon request. It is also important to note that though these exercises are provided under the MIT License, the various supporting datasets are not and will need to be downloaded from the respective websites. The references to the datasets are given at the bottom of the lab documents.
Credit must also be given to Al Sweigart for creating supporting material for the early labs. You can purchase his book at https://automatetheboringstuff.com/
Lessons:
- Lab 1 - Hello Python world!
- Lab 2 - A function for data validation
- Lab 3 - Basic data cleaning and analysis
- Lab 4 - How to work with open data
- Lab 5 - How to ethically scrape the web
- Lab 6 - Create and manage a digital bookstore collection
- Lab 7 - Identify Halifax's Twitter influencers
- Lab 8 - Making big(ger) data eas(ier) with data frames
- Lab 9 - Analyze iPhone app downloads
- Lab 10 - Discover associations between e-commerce purchases