Data Analytics (CS 301)
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.
Lecture, Discussion, Presentations, and Group Work:
28 Aug. 2018 - 18 Dec. 2018: Lecture Tuesday, Thursday 9:30AM - 10:45AM, Alden Hall, Room 101
28 Aug. 2018 - 18 Dec. 2018: Lab Friday 2:30PM - 4:20PM, Alden Hall, Room 101
Mondays: 1:30 pm -- 3:30 pm (10 minute time slots)
Tuesdays: 11:00 am -- 12:00pm and 2:30pm -- 4:30pm (10 minute time slots)
Thursdays: 11:00 am -- 12:00pm (10 minute time slots)
Schedule an appointment with me using the Google calendar
Tentative Chapter Schedule:
Other Useful Textbooks:
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.