CMPSC-301-00: Data Analytics
Academic Bulletin Description
An introduction to computational and analytical methods for finding patterns in large data sets. Using statistical procedures that they design and implement in programming environments, students extract knowledge from financial, political, scientific, and other data sources, exploring the issues of power and privilege that emerge from their discoveries. Students also learn to contrast their own perspectives with the ones identified by their analyses, reflecting on the ethical consequences of using the power that originates from computationally derived knowledge. During a weekly laboratory session students employ state-of-the-art statistical software to complete projects, reporting on their findings through both written documents and oral presentations.
In order to acquire the proper skills in technical writing, critical reading, and the presentation and evaluation of technical material, it is essential for students to have hands-on experience in a laboratory. Therefore, it is mandatory for all students to attend the laboratory sessions. If you will not be able to attend a laboratory, then please see the one of the course instructor at least one week in advance in order to explain your situation. Students who miss more than two unexcused laboratories will have their final grade in the course reduced by one letter grade. Students who miss more than four unexcused laboratories will automatically fail the course.
Discord class server:
- Tuesdays and Thursdays at 11:10 AM – 12:25 PM (EST)
- 24 August 2021 – 15 December 2021 Where: Alden 101
- Tuesdays at 3:00 PM - 4:50 PM Where: Alden 101
Planning your time
Wickham, Hadley, and Garrett Grolemund. R for Data Science: Import, Tidy, Transform, Visualize, and Model Data., O’Reilly Media, Inc., 2016. Book Website
Julia Silge And David Robinson. Text Mining With R: A Tidy Approach., O’Reilly Media, Inc., 2019. Book Website
Other Useful Textbooks:
BUGS in Writing: A Guide to Debugging Your Prose (Second Edition). Lyn Dupr'e. Addison-Wesley Professional. ISBN-10: 020137921X and ISBN-13: 978-0201379211, 704 pages, 1998. References to the textbook are abbreviated as “BIW”.
Writing for Computer Science (Second Edition). Justin Zobel. Springer ISBN-10: 1852338024 and ISBN-13:978-1852338022, 270 pages, 2004. References to the textbook are abbreviated as “WFCS”.
Use the ssh or http link (below) to get the classDocs repository containing all class materials.
- Web based access: https://github.com/Allegheny-Computer-Science-301-F2021/classDocs.git
Your grades will be added to your personlized repository for your assignments. Please accept this “assignment” and then check this repository after your grades have been posted.