{"id":340,"date":"2026-02-19T12:40:57","date_gmt":"2026-02-19T12:40:57","guid":{"rendered":"https:\/\/deeplearningindaba.com\/2026\/?page_id=340"},"modified":"2026-04-17T19:07:10","modified_gmt":"2026-04-17T19:07:10","slug":"tutorials-skill-sessions","status":"publish","type":"page","link":"https:\/\/deeplearningindaba.com\/2026\/tutorials-skill-sessions\/","title":{"rendered":"Tutorials & Skills sessions"},"content":{"rendered":"
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Tutorial & Skill Sessions<\/h1>
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Open Call for Tutorial & Skill Sessions<\/h1><\/div><\/div>\n<\/div>\n<\/div>\n\n
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Submit Your Proposals for Indaba 2026<\/h1><\/div><\/div>\n\n
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The Deep Learning Indaba (DLI) is the annual gathering of Africa\u2019s Machine Learning and AI community, dedicated to strengthening and celebrating African AI. In 2026, the Deep Learning Indaba will be held in Nigeria in August (exact dates to be announced later). The event will include keynotes, tutorials, workshops, panels, and other interactive sessions. The theme for this year's Indaba is: <\/span>Sovereign Intelligence: Africa\u2019s Path in a Frontier AI World.<\/i><\/b><\/p>\n<\/div><\/div>\n<\/div>\n<\/div>\n<\/div>\n\n

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We are excited to announce our first-ever open call for Tutorials and Skill Sessions and invite you to submit your proposals, <\/span>especially<\/span><\/i> for topics that support the theme.<\/span><\/p>\n<\/div><\/div>\n<\/div>\n<\/div>\n\n

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Tutorials<\/h4>

They are a 2-hour entirely in-person sessions intended to introduce a specific topic to the audience in a lecture-style format. Please see the past Intro to Transformers or Intro to Machine Learning tutorials for inspiration. We encourage topics around (but not limited to) Graph Neural Networks, Climate Modelling, Agentic AI etc. Maximum of 3 speakers per Tutorial.\u00a0<\/p>\n<\/div><\/div><\/div><\/div>\n<\/div>\n\n

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Skill Sessions<\/h4>

They are 1-hour entirely in-person sessions aimed at providing participants with broad, reusable competencies that are essential for long-term professional success. Sessions should be hands-on demonstrations (\"how-to\") and include resources for participants to reproduce the skills later.\u00a0 For example, you could propose a session on how to ship production-level code or how to read and write research papers. Maximum of 1 speaker per Skill Session.<\/p>\n<\/div><\/div><\/div><\/div>\n<\/div>\n<\/div>\n\n

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Both s<\/span>essions <\/span>are expected to be accessible to undergraduate participants working in different areas of Machine Learning, i.e., a good part of the session should be spent on covering necessary background material. We encourage submitters to think about how their session could be helpful in the community after the meeting, for example, providing links to code, slides, and exercises. There is no cap on the number of proposals submitted per person - feel free to fill out this form multiple time.<\/span><\/h3>\n