MinneMUDAC 2023: Student Data Science Challenge
Inviting teams of graduate and undergraduate students to explore real-world data while enhancing and showcasing their skills
This experiential learning opportunity invites 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 analytics professionals from the community.
Student teams have several weeks to analyze data before presenting their findings to judges from the analytics community at the main event on March 25. Teams with the highest scores move on to the finals round. Cash prizes are awarded to top teams in each division.
Stay tuned – this year's challenge and data will be announced in mid-February.
Presenting Your Findings
Student teams will present their findings on Saturday, 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.
Want to participate? Put together your team following the guidelines below! We recommend the faculty or staff advisor register for the entire team if possible.
Who is invited?
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. For more information, see the "Judges/Mentors" section below.
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.
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.
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.
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.
Presented by MinneAnalytics and Midwest Undergraduate Data Analytics Competition (MUDAC). For more information, visit the event website: minneanalytics.org/minnemudac2023/
PLEASE NOTE: MinneAnalytics requires a Driver's license or government-issued photo ID for entrance at all events.