Data Science Team Companion Course (CSCI 4802/5802)

When: Tuesdays 5-6:15pm
Where: ECCR 245 (Spring 2020)
Professor: Rafael Frongillo
Captain/grader: Carter Tillquist

Team website: codata.colorado.edu
Communication: slack
Assignments: moodle

Prerequisites: linear algebra or permission of instructor

Course Description

Gives students hands-on experience applying data science techniques and machine learning algorithms to real-world problems. Students will work in small teams on on projects of their choosing, which could include competitions sponsored by local companies and organizations. Project teams are responsible for attending, submitting progress reports, and giving short presentations when appropriate.

Motivation

Data science is one of the fastest-growing sectors of our economy, and there is a great demand for data scientists with practical experience applying statistical techniques and machine learning algorithms to real data. While several courses in the CS curriculum develop these techniques, in the areas of machine learning, statistical modeling, network science, numerical analysis, and data science more broadly, and while these courses often include a hands-on project, no course specifically focuses on putting this myriad of tools to work on real data and developing intuition for when to apply certain techniques over others. The present course will fill in this gap, allowing students to work in teams both small and large to solve real-world prediction challenges, gaining valuable experience whether entering the workforce or remaining in academia.

Topics

To accompany the prediction challenges and other activities hosted by the team, we will have short presentations on topics relevant to the current competition or data science more broadly. A non-exhaustive list of topics is as follows.

Assessment

The general requirement for the course is to participate in the competitions and other activities of the team. As the specifics of these competitions and activities will change from semester to semester, the course is formally structured as follows. You will submit three written reports to Moodle detailing what you have done. These reports should be structured as follows:

Midterm reports

Final report

For more information about the team, please visit the team website.