Regional Data Science Hackathon 2026

About the Hackathon
The DSHP Regional Hackathon is part of the Hack4dev programme, which aims to strengthen data science capacity through collaborative, practice-based learning.
Over four days, participants will work in multidisciplinary teams to solve a real-world machine-learning challenge using real datasets, supported by experienced trainers and mentors.
Participants will gain practical experience in:
- Data preparation
- Machine-learning model development
- Model evaluation
- Teamwork and collaboration
- Presenting technical solutions
Who Can Apply?
Applications are open to university students and young professionals who:
- Are currently enrolled at a university, undergraduate or postgraduate.
- Have an interest in data science, artificial intelligence, machine learning or related disciplines.
- Have basic programming experience; Python is advantageous but not mandatory.
- Are enthusiastic about learning and teamwork.
- Can attend the full four-day hackathon.
- Can commute to and from the venue each day.
- Understand that travel and accommodation costs will not be covered.
- Are willing to complete the pre-hackathon preparation activities.
Programme
| Date | Activity |
|---|---|
| 26 October 2026 | Welcome, introductions, challenge briefing and other formalities — half day |
| 27 October 2026 | Teams work on the challenge |
| 28 October 2026 | Teams work on the challenge |
| 29 October 2026 | Final team presentations, judging and closing |
Awards & Recognition
Outstanding teams will be recognized for innovation, technical excellence, teamwork and problem-solving. Additional prizes or awards may be presented by the host institution or programme partners.
How to Apply
Applications are submitted through the Google Form: Application Form – Regional Data Science Hackathon 2026
The poster also has the QR code for the application form.
scan for the application form
Successful applicants are to be notified by 4th October 2026 and will receive information about the programme, preparation materials and logistical arrangements.
