Global Student Excellence in Data and AI Showcased
With the recent launch of SAS Viya Workbench for Learners, students showcased their skills in data analysis, preparation, and presentation during this year's prestigious competition. The SAS Curiosity Cup brings together bright minds from around the world to explore innovative applications of data science and artificial intelligence.
Exploring Innovative Solutions
This year, participants engaged in fascinating projects. They tackled important questions such as whether machine learning can predict diseases like breast cancer and Alzheimer’s. Another impactful inquiry was how social platforms, like Facebook, can reduce feelings of isolation among older adults. These topics, presented in the SAS Curiosity Cup, demonstrate the potential of data science in addressing real-world challenges.
A Platform for Future Data Scientists
Thanks to the introduction of SAS Viya Workbench for Learners, participants in the competition had access to a cutting-edge computing environment designed for building programming skills and developing AI models. This powerful tool enabled students to quickly undertake multiple projects across various programming languages.
Positive Impact on Participants
Jürgen Kaselowsky, Director of Global Academic Programs at SAS, shared insights on the competition, highlighting the growth in participation and global representation. He stated, "The opportunities to utilize data and AI for meaningful challenges have never been greater. Our growth in participation reflects this demand. The introduction of SAS Viya Workbench for Learners further empowered teams by allowing flexibility between SAS and open-source tools."
Wide Participation in the Competition
A remarkable 112 teams, comprising 360 students and 25 industry consultants from 29 countries, entered the competition. These talented individuals selected publicly available datasets, posed their own analytical questions, and produced detailed papers alongside engaging video presentations that showcased their findings and analyses. Expert judges evaluated submissions based on data preparation, analysis, and presentation skills.
Celebrating Winners of the Competition
The winners of the SAS Curiosity Cup represent outstanding achievements in their respective categories:
- Data Preparation: Team Data Aces from the University of Santo Tomas – "Predictive Model Trends: Predicting Early Detection of Alzheimer's Disease"
- Data Analysis: Team Machine Learning Dynamite from Anglia Ruskin University – "Development of Breast Cancer Detection Tool"
- Data Presentation: Team DataMind from the University of Padua – "Social Media Use Among Italian Older Adults: A Weighted Analysis of Facebook Survey Data"
Team DataMind expressed their gratitude, stating, "Being part of the Curiosity Cup was an enriching experience, enhancing both personal and professional growth. It taught us teamwork, priority management, and how to seek mentorship, which are invaluable skills for our future careers."
Moving Forward: Inspiring Future Generations
Looking ahead, the SAS Academic Programs and SAS Viya Workbench for Learners continue to foster curiosity and empower the next generation of data scientists. As we anticipate the 2026 competition, excitement builds for emerging innovations and collaborations in the field.
Frequently Asked Questions
What is the SAS Curiosity Cup?
The SAS Curiosity Cup is a global data science competition that recognizes student excellence in data analysis, preparation, and presentation.
Who participated in this year's competition?
This year, 112 teams made up of 360 students and 25 industry consultants from 29 countries participated.
What tools did participants use?
Competitors utilized SAS Viya Workbench for Learners, which supports various programming languages and AI model development.
What were the categories for awards?
Awards were presented in categories for data preparation, data analysis, and data presentation.
How can students learn more about SAS programs?
SAS offers various academic programs and resources designed to support students in data science and analytics.
