Applications open for Deep Learning Indaba – Africa

The Deep Learning Indaba exists to strengthen African machine learning. Their flagship programme is the annual gathering of the African Al community. It consists of a week-long event of teaching, practical sessions and debate on the principles and practice of modern Artificial Intelligence. Participants are selected from across the African continent, and elsewhere, and are exposed to the world’s leaders in the area of Al, to build networks for future research and innovation, and are given the opportunity to showcase their own work.

This is a popular event which is multiple times oversubscribed, and they hope this application guide will provide you with guidelines and key points to assist you in putting your best foot forward.

Traits of a Typical Indaba Attendee

• Active in the community
  • Involved in building capabilities in your local community and/or involved societal projects in Africa.
• Inspiring
  • You have overcome the challenges life throws at you. Your journey uplifts other people.
• Enthusiastic
  • You show intense enjoyment and interest in Al and the ML community.
• Experienced
  • You are a domain expert in your field and/or you are actively involved in ML. research & application, with knowledge to participate in discussions.
• Motivated
  • You have a clear idea of how the Indaba will benefit your career and visions.
• Entrepreneur Visionary
  • You see solutions to unique African problems using Al.
• Open to learning
  • You show a keen interest to learn and grow with the community.
• You!
  • Indaba candidates presents a mix of these traits and they welcome your uniqueness.

Eligibility Criteria

• This conference is open to students, early career researchers, industry professionals, and those involved in NGOs, government, or academia. If you are enthusiastic, motivated, eager to learn and help, and have some experience with machine learning or work at the intersection of machine learning with the humanities, then this conference is for you.

For more information, visit Deep Learning Indaba.