We are excited to announce a 2-day Data Science Hackathon that will take place on 21 - 22 April 2024, after the AfAS conference. This hackathon will offer participants the chance to experience the entire pipeline of machine learning, from conception to application. To support their work, we will utilise the advanced South African ilifu data-intensive research cloud facility.
We extend a warm invitation to undergraduate and postgraduate students, as well as young professionals, who are interested in machine learning. This hackathon will not only provide an excellent platform for participants to showcase their skills but also enable them to network with peers from the African community. The event will be centered around teamwork, peer learning, and fun as the participants solve data challenges using machine learning.
During the hackathon, participants will have access to tutorials and receive guidance from mentors. They will form teams of five and commence their work on the data challenge by employing machine learning techniques. Following the hacking period, teams will prepare a presentation showcasing their results on the task and present it to a panel of expert judges.
Transport and accommodation will be provided for all selected participants who are from African countries.
• Registration is open until – 15 January 2024
• Attendance confirmation by – 31 January 2024
• Event 21 – 22 April 2024
The hackathon is suitable for undergraduate and postgraduate students, as well as young professionals residing in Africa who have Python experience and a keen interest in data science and machine learning.
Please Note: Selected applicants must submit a recommendation letter from their supervisor/manager indicating their Python skills.
Participate in this event to utilise your data science skills, contribute to research in multi-wavelength astronomy, and foster connections within the African community. In addition, participants will be able to attend the informative AfAS conference scheduled to take place on 15 - 20 April 2024.