Deep Learning Indaba𝕏
South Africa

07 - 11 Jul, 2025

Stellenbosch University

A Deep Learning Indaba𝕏 is a locally-organised “Indaba” or conference that helps ensure that knowledge and capacity in machine learning are spread more widely across the African continent.

Registration info

Academia
🔭
Early Bird Ticket: R2000

Closed!

Opening again soon. Tickets released in multiple waves on a first come, first serve basis

Open until: Friday 13 Jun 2025 at 23:00:00 +0200

Industry
🛠
Early Bird Ticket: R3700

Closed!

Opening again soon. Tickets released in multiple waves on a first come, first serve basis

Open until: Friday 13 Jun 2025 at 23:00:00 +0200

Studying
🎓
Free!

Apply to attend for free

Deadline: Fri 23 May 2025 at 22:00:00 (+0200)

Acceptance: 6th June (approx.)

Present a talk
🎤

Submit abstract

Deadline: Fri 23 May 2025 at 22:00:00 (+0200)

Acceptance: 1st June (approx.)

Machine learning and artificial intelligence conference

Duration

Jul 07, 2025 - Jul 11, 2025

The conference will be a multi-day event featuring…

400+
attendees

connect with other researchers and practitioners

50+
speakers

attend a showcase of cutting-edge research and applied AI

4+
tutorials

receive a practical introduction to machine learning for beginners

50+
posters

share your work and get feedback from experts

2+
hackathon problems

get your hands dirty and learn from the best

News

Meet the Indaba𝕏 2025 organising committee

Yes, we’re back with deep learning, one layer at a time, to building Africa’s AI future

2025-04-21 read more

Meet the Indaba𝕏 2024 organising committee

We’re serious about growing machine learning in South Africa, no joke!

2024-04-01 read more

Join the committee for Indaba𝕏 2024: It’s coming home!

Indaba𝕏 2024: It’s coming home We are looking for the next generation of ML community leaders in South Africa!

2024-01-22 read more

What people say about the Indaba𝕏

The incredible diversity of experiences and backgrounds of people in the AI and ML field. Everyone has a unique story.

The IndabaX is an amazing event that changed my perspective on how ML can be used in Africa. I am so glad I attended and I would recommend it to anyone.

My key take aways from the conference were in the academia side; I really enjoyed being in the Company of the people I have had around me. They were very intelligent group of People, ranging from the event organizers to the lectures whom shared their years of acquired experience with passion to my fellow students whom were also so accommodating and intelligent. The positive mindset I have acquired from the IndabaX conference was just what I needed to align my personal life with the research project I am currently working on; to know that there are similar minded people out there whom are also working on solving real life problems using science really reenergized me. I thank you kindly for the opportunity.

I enjoyed meeting different people, who are doing very different from what i do and seeing things from their perspective. The keynote were wildly helpful and interesting, so was the panel discussion. I realized that there is no one straight path in AI and ML and that a lot of us can take very different routes and sort of end up at the same place which is interesting.

I am an intermediate in research and reinforcement learning with interest in working in industry. Therefore, the whole conference was my key take away in a way. I attended all reinforcement learning related talks, from the foundations to the applied ML and industry. It was interesting how RL was first introduced before moving on to how it is applied. That was thoughtful and accommodating.

I think the conference did very well when it came to diversity and inclusion, this is highly attributed to the fact that it did not only focus on the technical side of things but included people from different background and cultures with different life experiences. How they came together towards working on solving real life problems really shows the success of this event.

In terms of people, I think there’s an even proportion amongst all genders and race. Including applied ML and industry was truly outstanding because not everyone wants to be in research and academia. The talks were so diverse that most industry were included.