Building Africa’s data science talent pool

4Jun - by aiuniverse - 0 - In Data Science

Source: businessdailyafrica.com

A Marketing Trends report by IBM in 2017 estimated that we generate 2.5 quintillion bytes of data daily. This has since gone up by several factors, taking into account the steady growth in digitisation and more users and devices coming online. Businesses, governments, and institutions are swimming in oceans of data, with a need to have it carry a commercial or another such positive benefit. As a result, the demand for science, technology, engineering, and mathematics (STEM) talent is skyrocketing.

Predictably, data scientists and artificial intelligence engineers are emerging as the most sought after roles in STEM globally. Across Europe, the US, and Africa 13 million STEM jobs will need to be filled by 2025. Aging populations and shrinking labour forces in the western world should have us looking more keenly at this opportunity. Sub Saharan Africa is the youngest global region with a median age of 19.1 and the world’s fastest-growing population.

However, the continent is not yet producing the requisite quality and numbers of skilled workers to take advantage of this. New talent development approaches are urgently needed if Africa is to turn its abundant youth dividend into a productive resource.

The current intervention mix is predominantly short term boot camp style programmes that do not quite provide the needed depth for astute learning for technical subjects. Globally there are interesting edtech startups like Lambda School but there are some obvious dampers to their models if you are based out of an emerging market context.

This was not lost on Mark Karake, a Kenyan technology entrepreneur who relocated back to Kenya from Silicon Valley to establish Impact Africa Network, a non-profit startup studio that has launched Jenga School, a STEM education startup that offers a rigorous 12-month data science and AI course. With a focus on quality, all instructors are PhD holders in the field and they work with industry mentors who are themselves data science professionals with a curriculum that is a unique combination of academic thoroughness and practical skills. They have also tapped the world’s foremost mind in the field, Jeff Dean, head of AI research at Google to its advisory board.

Imparting solid teaching to a new generation of computer scientists, data scientists, and machine learning practitioners will ready us, not just to address the continent’s most pressing challenges but to also have exportable talent that we can ‘share’ with the world.

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