MinneMUDAC 2023

Student Data Science Challenge

Main Event at Target Field in Minneapolis on Saturday, March 25, 2023

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MinneAnalytics is proud to present the fifth edition of this analytics event inviting teams of graduate and undergraduate students to explore real-world data while enhancing and showcasing their skills. Join us for this unique collaboration between students, their academic advisors, and professionals from the community.

The Challenge

We have identified a challenge for this year’s event, which will be released in mid-February. It will be applicable to many industries and reflective of the real world challenges students will encounter in their careers – and challenging. Past challenges have focused on a range of industries, including sports, agriculture, and healthcare. While datasets may be provided, teams are encouraged to use publicly available sources. More will be required of Graduate Division teams to complete the challenge.

How It Works

Team registration begins in January. The data and challenge question will be released in February. Student teams have several weeks to analyze data before presenting their findings to judges from the analytics community at the main event at Target Field on March 25. Teams with the highest scores move on to the finals. Cash prizes are awarded to top teams in each division. This year’s data and challenge question are to be announced. The data will be released approximately one month before the day of the challenge.

Benefits to Students

MinneMUDAC provides an experiential opportunity with far-reaching benefits to student growth. Many participants cite the competition as a concrete example to share later on while interviewing for a job. A recent article in TechCrunch on hiring analytics talent states that “using case studies rather than a skills checklist effectively uncovers elements of quality in the hiring process.” Students from dozens of colleges and universities across the country have participated in past MinneMUDAC events. Check out this recap of our 2019 challenge during which 71 student teams analyzed agriculture data to predict trends in soybean prices.

Competition Guidelines

Who is invited?

MinneMUDAC is open to:

  • Students: Undergraduate and graduate students welcome. Please note that you must enter the team name and name/email of a faculty or staff advisor to register. See team guidelines below.
  • Faculty/Staff Advisors: Each team requires a faculty or staff advisor to provide guidance throughout the challenge. One advisor may advise up to three student teams. Advisors assisting more than one team must register for each team.
  • Judges/Mentors: Share your experience with the next generation of analytics professionals. Industry professionals who would like to judge and provide mentorship may register by selecting the “Judge/Mentor” ticket option.
Team Guidelines

Student teams must meet the following guidelines:

  • Each team requires a faculty or staff advisor to register as well as provide support throughout the competition.
  • Teams are limited to five students and one faculty or staff advisor.
  • Colleges and universities outside of Minnesota are encouraged to participate.
  • MinneAnalytics is able to provide Friday night accommodations for teams traveling two hours or more; however, the number of rooms available is limited. The team faculty advisor must request accommodations during initial registration.
  • More than one team from the same college or university may participate. Individual students may only join one team.
  • There is a limit to three teams from the same college department.
  • Blended teams of students with different majors and skill-sets are encouraged.
Competition Divisions

Each student team competes in one of four divisions:

  • Open Division: For accomplished career professionals that are adding a second advanced degree or enhancing their skill set, or elite teams that want to compete against the best. Note: No cash prizes are awarded to teams participating in the Open Division.
  • Graduate Division: For teams with advanced data management, data programming, and statistical/analytic skills to support predictive modeling, including at least one graduate student. Any team with one or more Graduate students will automatically be in the Graduate division.
  • Undergraduate Division: For undergraduate teams with advanced data management, data programming, and statistical/analytic skills to support predictive modeling.
  • Novice Division: For students early in their studies who have limited experience and have novice to intermediate data management, data programming and statistical/analytic skills. Any team with Freshmen and Sophomores will be in the Novice division. Any team whose school’s data science program is less than two years old will be in the Novice division.

Division level is chosen by the team’s faculty or staff advisor during registration.

High school level teams may participate in the Novice Division. Contact dan@minneanalytics.org if your high school team is interested.

Presentation & Judging

Student teams will present their findings on March 25. During the first round (9 am-noon), teams have five minutes to present their model to a series of judging teams. Judges will also have the opportunity to ask questions of each team. Student teams should expect to pitch 4-6 times with each interaction lasting 7-12 minutes. After breaking for lunch, the finalists will present to all the judges.

Award Categories

Analytic Acumen: Awarded to the team in each division with the most technically appropriate and accomplished team presentation.

Serendipitous Discovery: Awarded to the team in each division providing the most interesting, if unrelated, findings or insights.

Overall Prediction: Awarded to the teams in each division (excluding Novice Division) with the most accurate prediction.

Challenge & Data

This year’s competition challenge is to be announced.

Volunteer as a Judge/Mentor

Participation from professionals from the analytics community is key to the success of the MinneMUDAC competition. Judges/Mentors are grouped into small teams of 3 or 4 (ideally with at business professional, a technologist, and an academic to create a blended mentoring teams). If you are a business professional that’s been pitched a presentation before, a technologist that understands computer science and/or math/stats, or an academic that regularly engages students, then you are qualified to be on a judging team. Register on the registration page by selecting the Judge/Mentor option.

Note: competition guidelines, details, and timeline are still being finalized and are subject to change.