Source: Deep Learning on Medium
Data science Nigeria was founded Olubayo (Bayo) in 2016 and the organization is driven by a vision to build an AI-first society where Artificial Intelligence is effectively deployed to solve local problems, particularly the sustainable millennial goals. He believes that AI will provide a springboard for Africa’s development by enhancing how we live, work and play.
He believes that Nigeria’s population of 200million with median age of about 18 years is a huge strategic advantage that can position Nigeria as one of the top 10 AI Knowledge centres in the world, especially the opportunity to raise 1 million AI talents in 10 years with globally relevant skills that can drive increased employability, FOREX inflow, AI-enabled start-ups and enhancement of the general quality of life through solution-oriented AI applications in Health, Agriculture, Financial Inclusion, Smart City etc.
Data science Nigeria offers free programs for its participants and these include the following (i) 100 Days of Machine Learning, which is prerequisite for participating in the annual bootcamp. (ii) Bootcamp is the residential bootcamp and hackathon of the those who emerged from the 100 days learning machine learning practitioners in the academic community and the industry. (iii) Inter-Campus ML Competition is an avenue for raising a generation of data scientists and Artificial Intelligence experts from all Nigerian Universities and Polytechnics.
Deep Learning Indaba was founded by Vukosi Marivate in 2017. Deep Learning Indaba is an organisation whose mission is to Strengthen Machine Learning and Artificial Intelligence in Africa. We work towards the goal of Africans being only observers and receivers of the ongoing advances in AI, but active shapers and owners of these technological advances.
Much of the wider discourse at present is permeated with conversations around the 4th industrial revolution, the need for policies and interventions around changes to jobs and workplaces, the impacts of increasing automation in societies, of high-levels of global investment in AI and machine learning, and visions of AI-first organisations. What underlies these conversation is the ongoing and rapid advances being made in artificial intelligence. It is essential for Africans to become not just observers of the ongoing advances in AI, but active shapers and owners of these technological advances. It is for this reason that the Indaba was conceived. And for this reason it plays a unique and important role within our continent.
The Deep Learning Indaba aims to address two principal aims: African participation and contribution to the advances in artificial intelligence and machine learning, and diversity in these fields of science. The implications of these overarching goals is the spreading of technical knowledge at the state-of-the art in the field; the opportunities for new research connections to be made and and silos in the research community to be broken; the fostering of a better understanding of the variety of career paths in the field, especially those that are in abundance locally; and through new friendships, perspectives and backgrounds, taking the steps to realising a more representative, inclusive and multicultural machine learning community.
We execute our mission through three principal programmes: the annual Deep Learning Indaba, the IndabaX, and the Kambule and Maathai awards. These programmes aim to build a sustainable pan-African community of AI expertise, create local leadership in AI in every country across the continent, and recognise excellence in research and application of AI technologies, respectively.
The Deep Learning Indaba the annual gathering of the African AI community. It consists of a week-long event of teaching, practical session 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 AI, build networks for future research and innovation, and are given the opportunity to showcase their own work. Participants range from all levels, including undergraduate students, research students, lecturers and academic, industry professionals, startups, and policy developers.
The IndabaX builds local leadership in individual countries across our continent. We ask groups to run their own one-day Indaba and build the community of researchers and developers in their community. We support these IndabaX’s through small grants and organisational guidance.
The Kambule Doctoral Dissertation Award recognises excellence in research and and writing by a doctoral candidate at an African higher education institution. The Maathai Impact Award recognises excellence in the application of machine learning to problems facing Africa and her people.
African Masters of Machine Intelligence (AMMI) was founded by Moutapha Cisse in 2018 thanks to the sponsorship of Facebook and Google and the exceptional support of the global AI community. The goal of AMMI is to bring the best of AI education in Africa and contribute to building a healthy ecosystem of AI practitioners committed to making a positive impact on our societies.
Our first cohort comprises 30 students from 10 countries. During the past months, it has been exciting seeing them develop strong relationships and grow their technical abilities through group projects, and interactions with world-class lecturers. They now mentor students from their former institutions and are mentored by senior researchers in the field. In July 2019, they will graduate from AMMI and will become mentors for the students of the class of 2020.
AMMI is a novel fully funded one-year intensive graduate program that provides brilliant young Africans with state-of-the-art training in machine learning and its applications. The AMMI program will prepare well rounded machine intelligence researchers who respond to both present and future needs of Africa and the world. Visit the website of AMMI
AI Hack Tunisia was founded by Karim Beguir in 2019. The AI Hack Tunisia doubles as hackathon: the first part will be an individual Machine Learning Challenge, and the second part will be a group (or as we like to say, startup) competition focused on a specific technology (that will be announced a few days before the event).