×

Data Fest

DataFest is back at Loyola University Chicago!

Loyola University Chicago will be hosting DataFest April 5-7, 2024.  

Sign up for DataFest at Loyola here 

DataFest Schedule

Where: Cuneo Hall 109

Friday, April 5, 2024

5pm: Registration starts; Pizza

6pm: Data revealed

11:30pm: Room closes

Saturday, April 6, 2024

8am: Room opens

12pm: Lunch

5pm: DataFeast

11:30pm: Room closes

Sunday, April 7, 2024

8am: Room opens

11am: Presentations begin

12pm: Lunch

1pm: Winners announced; awards given out

What Is ASA DataFest?

American Statistical Association DataFest Website

DataFest is a data "hackathon" for students, founded at UCLA in 2011 to motivate a data-analysis class project, that makes data analysis more fun and meaningful while incentivizing good scientific practice and presentation. Now sponsored by the American Statistical Association, ASA DataFest is run through several host institutions across the country, including right here at Loyola University Chicago!

ASA DataFest @ Loyola Chicago is hosted by the Loyola Department of Mathematics and Statistics, the Loyola Department of Computer Science, and the Loyola Data Science Program.  

  • Analyze

ASA DataFest will introduce you to what is likely the richest, most complex dataset you’ve seen so far in your college career. The dataset is provided by a real-life organization and is chosen to provide many avenues of discovery. Students at any stage of their data-science education will find something of interest and will have the opportunity to make an original finding. Students from any major are welcome.

  • Network

Mingle with data science professionals who visit DataFest to offer their advice and answer your questions. You’ll also get to meet students from other colleges and universities.

  • Experience

Past participants of an ASA DataFest have gone to job interviews and are able to describe how they can overcome technical challenges, explain how they work under time pressure, and can talk about their thoughts on solving real-life data-problems.

 

 

DataFest is back at Loyola University Chicago!

Loyola University Chicago will be hosting DataFest April 5-7, 2024.  

Sign up for DataFest at Loyola here 

DataFest Schedule

Where: Cuneo Hall 109

Friday, April 5, 2024

5pm: Registration starts; Pizza

6pm: Data revealed

11:30pm: Room closes

Saturday, April 6, 2024

8am: Room opens

12pm: Lunch

5pm: DataFeast

11:30pm: Room closes

Sunday, April 7, 2024

8am: Room opens

11am: Presentations begin

12pm: Lunch

1pm: Winners announced; awards given out

What Is ASA DataFest?

American Statistical Association DataFest Website

DataFest is a data "hackathon" for students, founded at UCLA in 2011 to motivate a data-analysis class project, that makes data analysis more fun and meaningful while incentivizing good scientific practice and presentation. Now sponsored by the American Statistical Association, ASA DataFest is run through several host institutions across the country, including right here at Loyola University Chicago!

ASA DataFest @ Loyola Chicago is hosted by the Loyola Department of Mathematics and Statistics, the Loyola Department of Computer Science, and the Loyola Data Science Program.  

  • Analyze

ASA DataFest will introduce you to what is likely the richest, most complex dataset you’ve seen so far in your college career. The dataset is provided by a real-life organization and is chosen to provide many avenues of discovery. Students at any stage of their data-science education will find something of interest and will have the opportunity to make an original finding. Students from any major are welcome.

  • Network

Mingle with data science professionals who visit DataFest to offer their advice and answer your questions. You’ll also get to meet students from other colleges and universities.

  • Experience

Past participants of an ASA DataFest have gone to job interviews and are able to describe how they can overcome technical challenges, explain how they work under time pressure, and can talk about their thoughts on solving real-life data-problems.