Submit applications to host IndabaX events in your country, anywhere across Africa by 10 May 2022. The process is simple and we hope to support as many as we can. To apply, simply fill in this form!
About the IndabaX program
The IndabaX programme started in 2018 as an experiment in strengthening our machine learning community beyond the annual Deep Learning Indaba, to allow more people to contribute to the conversation on artificial intelligence and machine learning. We join hands across our beautiful continent. The initiative continues in 2022, and it is YOUR initiative!
A Deep Learning IndabaX is a locally-organised Indaba (i.e gathering) that helps ensure that knowledge and capacity in machine learning is spread more widely.
The first edition, in 2018, included 13 IndabaX events that were run locally in different countries across Africa. In 2021, the IndabaX grew to include 24 countries, 4 of which hosted the event for the first time! The events range from roughly 50 attendees per event, up to some of the larger ones which exceeded 300, allowing our community to grow to several thousand attendees!
If you attended one of the previous editions of the Deep Learning Indaba, and think your local community would benefit from such an event, we encourage you to organise an IndabaX at your institution. We leave the details of what exactly happens at an IndabaX to those who take on the role of organising one. The event can be organized at any time of the year.
Proposing an IndabaX
An IndabaX is a local gathering that helps develop knowledge and capacity in machine learning and artificial intelligence in individual countries across Africa. The IndabaX is one of the major programmes of the Deep Learning Indaba.
We encourage you to organise an IndabaX in your country. We leave the details of what exactly happens at an IndabaX to those who take on the role of organising one. The event can be organized at any time of the year.
Due to the spread of COVID19 and the uncertainty and threat it still creates, we encourage Hybrid events by default. If the regulations in your country allow for fully fledged in-person meetings, then you consider an in-person event as well.
The Deep Learning Indaba will support as many of these meetings as it can. Our support can include anything from: use of Baobab, our dedicated portal for event and attendee management, financial grants to support your event, help in planning and speaker invitations, publicity through the website, or in any other ways that local organisers think would be useful. An IndabaX can be small or big. Be as creative as possible.
Your IndabaX could be:
- A one to three-day meeting to stream leading online lectures, group learning around a specific set of topics, code teaching, research-replication sessions, or poster sessions;
- A structured series of tutorial lectures by invited speakers from the country, continent, or abroad on a focussed topic;
- A one-day workshop that brings people together to discuss their latest research with short talks and a panel discussion, bringing together groups across your university;
- A hackathon around a specific dataset or important challenge.
- Or a mixture of the above and other formats you think would work.
To make this possible, we ask interested groups to complete one of our online forms describing your meeting. We host monthly IndabaX catch up meetings, and if you have questions or need help, please join the next meeting.
What’s in the Proposal
The proposal is short, but does have a few different components that you need to answer. Long answers are not needed. The application form asks for responses to the following:
Your reasons for wanting to organise an IndabaX.
- Help us understand why you think it’s important to organise a local IndabaX where you are, and what outcomes you hope to achieve.
- If you organised an IndabaX in 2018, 2019, 2020 or 2021, tell us how things have changed, what you have learnt, and how you will improve.
- If you are in a country where an IndabaX was organised in 2018, 2019, 2020 or 2021 and you would like to be involved this year, please reach out to us through the online form to tell us about your motivation and what you hope to achieve. We are community builders and work together! We therefore encourage you to also reach out to the core contact in your country or region to coordinate with them, so that you can join forces and organize one impactful event per country.
COVID19 Planning
- Describe what measure you will put in place to keep everyone safe and prevent the spread of COVID19. For this reason we encourage virtual events as the safest path.
- If you can host in-person components of your meeting, describe how you think this will work, and what backup plans you have if regulations change.
- Include a description that you have confirmation from people in charge of the meeting space that you can host your event, and include their details.
Your plans to ensure diversity and inclusion in participants and speakers.
- Be mindful of the need for greater diversity in organisers, speakers and participants; one of the Indaba’s core principles.
- In particular, comment on the ways that you will increase the participation of women. We encourage every IndabaX to work towards having at least 35% female participation.
- You will be asked to adopt the Indaba’s code of conduct for your event, and take the responsibility that all participants work together to create a safe and inclusive learning and networking community.
A description of your IndabaX, and the format it will take.
- What type of IndabaX will you organise and what will your day(s) look like?
- Include a tentative schedule, and any confirmed and potential speakers.
- Expected number of attendees. An IndabaX does not need to be big, it can be 10 people or 100 people. Anything that helps strengthen your local machine learning community.
- If you are in a region with other universities and centres, we encourage you to work with each other–create a critical mass in your region–and submit a joint proposal. We are more likely to fund these events.
- How will you reach out to people and make them aware of your event. Try to be as inclusive as possible. Find interested first year undergraduates, and senior professors, and from different institutions. Try reaching out to local businesses and startups. Spark the spirit of the Indaba in them all.
- We ask that your event make explicit time to discuss how knowledge and capacity in machine learning can be spread more widely. After the event, we request that you send a summary of this discussion to the Deep Learning Indaba organisers to help us better plan future IndabaX events.
Details of your organising team.
- Any types of teams can apply, although we recommend multiple organisers.
Support needed.
- Describe the support that you think you will need.
- Send a proposal even if you don’t need funding so we can include you in the list of IndabaXs across the continent.
- If your proposal includes financial support, include a proposed budget.
- Funding can be requested for any need, e.g., budget to support coffee breaks or meals, to fund travel, cloud computing, meeting space, etc.
- Apply for amounts that support the scope and scale of your IndabaX.
- If a budget is needed, we aim to support different meetings with around US$ 2,000. Preference will be given to groups that collaborate and co-locate their meetings.
- You are encouraged to seek additional sponsors for your meeting. This is part of ecosystem building. Include details of any support that you will receive from local institutions (your research group, department or university) or outside funding. We encourage everyone to seek additional support, where possible, since this means we can support more IndabaX’s at other locations.
- You can apply from anywhere in the continent.
- Your IndabaX must be held at a local university. This means that we encourage you to have the support of a university lecturer or faculty member who will help to receive and spend the funds. This is preferred since it greatly simplifies the process of international funds transfer between countries (through registered organisations, such as universities). Nevertheless, we are also open to other suggestions to work around potential obstacles (e.g. pay some service suppliers directly rather than going through a university cost center).
All successful groups must send us a report of their workshop, a summary of their conversation on ways to strengthen African machine learning, some pictures and Invoice & Reciepts showing how the funds were spent, after their meeting. This will be included in our annual IndabaX report and helps us secure funding for future IndabaX events.
Key Dates
Send us your proposals by 10 May 2022. Successful local IndabaX organisers will be notified by 20 May 2022, and will receive funding as soon as possible thereafter. Send your proposal through the online form and any questions and queries to indabax@deeplearningindaba.com.
Key Dates for #IndabaX2022
IndabaX proposals due: 10 May
IndabaX notifications: 20 May
What is IndabaX?
The IndabaX programme started in 2018 as an experiment in strengthening our machine learning community beyond the annual Deep Learning Indaba, to allow more people to contribute to the conversation on artificial intelligence and machine learning. We join hands across our beautiful continent. The initiative continues in 2022, and it is YOUR initiative!
In 2018, we supported 13 IndabaX events that were run locally in different countries across Africa. In 2019, the IndabaX grew to include 27 countries. In 2021, we supported 23 IndabaX Events!. The events range from roughly 50 attendees per event, up to some of the larger ones which exceed 300, allowing our community to grow to several thousand attendees.
How to IndabaX?
To organise a successful IndabaX event, we have put together a document: “The Handy How to IndabaX” outlining the necessary steps and activities that will act as a guide during the organisation of your IndabaX event.
If you have any questions, feel free to reach out to the IndabaX Central Steering Committee.
Feel free to Join the Indaba Community slack for general updates.