Welcome to the repository for the lecture materials from the "Introduction to Data Science" course I taught at Carleton College, MN during the Spring of 2024. This course was designed to equip students with foundational skills and knowledge in data science, focusing on practical applications and theoretical underpinnings.
The course was structured around a series of lectures, practical lab sessions, and assignments that introduced students to various aspects of data science. Topics covered included data manipulation, statistical modeling, machine learning, and data visualization.
All lectures and materials were developed within the R ecosystem, utilizing the state-of-the-art Quarto platform to create dynamic, reproducible lecture notes and assignments. Quarto is an open-source scientific and technical publishing system built on Pandoc, which allows seamless integration of R code into high-quality documents. This approach ensured that all demonstrations and analyses were interactive and easily accessible, providing students with hands-on experience using real-world datasets.
This content is distributed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0), which allows others to remix, tweak, and build upon the work non-commercially, as long as they credit the creator and license their new creations under the identical terms. For more details on this license, visit Creative Commons License.
Please feel free to use and adapt the material for your own classes or personal study. I encourage you to contribute back improvements or extensions to this repository, enhancing the learning experience for future users.