*Entry is FREE and open to U of T students for the competition & for the workshops*

Sponsored by the BIGDataAIHUB at the Institute for Management & Innovation (IMI) at the University of Toronto Mississauga, in collaboration with Scotiabank, STEMFellowship and ICUBE.

*Please see below for important dates, including registration deadline & competition launch date*

The combination of Big Data and Artificial Intelligence is reshaping the way we think, work, and live. New career opportunities are emerging and traditional ones are being transformed or eliminated. As Graduate students at one of the top universities in the world it is important to stay on top of current and emerging trends, to pursue continual personal development, and to have some fun in the process. This event is designed to achieve all three. Sponsored by the BIGDataAIHUB at the University of Toronto Mississauga (UTM), this competition is being held in collaboration with Scotiabank, STEMFellowship and ICUBE.

The 2022 IMI Big Data & Artificial Intelligence Case Competition is a multi-faceted competition that is open to graduate students and undergrads with big data/AI experience from any academic discipline, in any year of their academic career at the University of Toronto. Some level of prior experience in working with big data / artificial intelligence is required.

In addition to the competition itself there will be 6-8 two-hour workshops. Attendance at these is optional. They will address specific big data, artificial intelligence and machine learning techniques that competitors may wish to consider employing. Registered competitors will automatically have access to these workshops, but other U of T students with an interest who choose not to compete can also have access to these workshops by registering for a non-competitor ticket.

The event is designed as a developmental opportunity for students. If selected to compete, they will gain additional hands-on exposure to big data and artificial intelligence as well as an opportunity to practice their formal presentation skills in a safe, fun and collegial, yet competitive, environment.

REGISTRATION AND COMPETITION DETAILS

Important information about the competition is as follows. Please ensure you read this thoroughly.

NOTE: the specific “use case” for the competition and the big data sets should be available to competitors by the initial (virtual) Kick-Off Event the morning of Saturday, November 27th. The competition will conclude with the live final round (i.e. virtual via Zoom) on March 26, 2022 (please refer to the schedule of key dates for more details).

There are TWO STREAMS (tickets).

1. COMPETITORS – The competition will be geared toward graduate students from all three U of T campuses and to undergraduate students that have advanced programing and AI skills. Competitors will need to sign the non-disclosure acknowledgement form.
2. THOSE WHO WANT TO LEARN ABOUT BIG DATA AND AI – registration for the Workshops will be open to anyone that wants to attend and observe them. There is no requirement for these registrants to be graduate students or undergraduate students that have advanced programing and AI skills.

Competition Timeline:

1. Online registrations will be accepted until 5:00 pm on Friday, November 26th. Early registration is strongly encouraged.
2. Virtual Kick-Off Meeting – This information session is expected to take place via Zoom from 10:00 am – 1:00 pm on Saturday, November 27th (Details to follow). All registered competitors are expected to attend the full Kick-Off Session.
3. Optional Workshops – A series of optional big data and artificial intelligence educational workshops will be scheduled in December, January, and February for registered entrants wishing to participate. Participation is encouraged but not required.
4. All teams are to submit their approach, findings and recommendations via ten-minute voice over PowerPoint video presentations (i.e. Zoom, or QuickTime videos) by 5:00 pm on Monday, February 28, 2022.
5. Team voice over PowerPoint submissions will be adjudicated by a panel of judges during the next two-week period. Five semi-finalists will be selected.
6. As a condition of remaining in the competition, all semi-finalist teams selected will be required to document their approach, findings and recommendations in a written paper of up to ten pages in length, plus attachments. Some of these finalist team papers may be selected for subsequent publication. Finalist teams are to submit their written papers by 5:00 pm on Monday, March 21, 2022.
7. The final round of presentations will be undertaking via synchronous (i.e. live) Zoom presentations on Saturday, March 26, 2022. Finalists will present for up to 15 minutes and a 20-minute question and answer period will follow. The written submissions will be taken into consideration in the selection of the first, second and third place winners.

Competition Eligibility:

1. To be eligible for this competition, students must be able to demonstrate that they are enrolled at the University of Toronto throughout the entire competition period. As part of the registration process, competitors are required to complete a short information questionnaire.
2. It is anticipated that there will be four participants per team, however teams with a minimum of two members are invited to register as well.
3. Any teams initially registering fewer than four team members could potentially find that the competition organizers might add additional members to their team in order to top-up the number closer to four members per team depending upon the total number of registrants and availability of U of T computing resources. This is also designed to foster cross-disciplinary teams.
4. Individual registrations (i.e. rather than in pre-arranged teams) are also welcome, however these individuals will be assigned to teams.
5. PLEASE NOTE: Each team must have at least one or two members with a strong background in data analysis and / or computer science, and possessing strong programming skills (e.g. python).
6. Diversity is encouraged. The comingling of students from different academic disciplines on each team is actively encouraged, but not a requirement.