Data Science Education in Africa
Data science is relatively new and is an interdisciplinary field which is a blend of statistics, computer science, mathematics, engineering and subject matter knowledge. In fact, any and all subjects qualify. Its proponents believe it will transform every aspect of society. Many of the disruptive, game-changing innovations that are grounded in data science are intended to improve people’s quality of life as well as the efficiency of processes and services. Examples include autonomous vehicles; precision medicine and precision agriculture; smart cities and financial technology.
Over the past decade, virtually every university in Europe and North America has responded to the challenges and opportunities of data science by establishing new institutes, departments and degree programs in the field. Academic institutions in Africa have only recently begun to catch up. Some are creating structures, networks and training programs to stimulate research and capacity development in the subject. Examples include HURU schools' Data Science online Picodegree, the African Center of Excellence in Data Science in Rwanda, the AI & Data Science Research Group at Makerere University in Uganda, Data Science Africa, and the Deep Learning Indaba. But with a time lag of at least half a decade, the question is whether Africa is bound to be trailing behind.
Less than 10% of people younger than 25 have access to higher education in Sub-Saharan Africa. It is not that the continent’s youth are uninterested in a higher education degree. Many are simply unable to afford full-time on-campus studies. So, if students can’t come to the university, the university must come to the students. The internet and a myriad of innovative distance learning platforms make this possible. Only 40% of Africa’s population has access to the internet. That’s compared to 61% for the rest of the world. But the internet penetration rate is increasing faster on the continent than anywhere else. Bite-size online content can be taken as standalone modules or cumulated into a certified degree. Either way, online distance education formats can be offered at a lower cost. They are also more scalable than traditional classroom teaching. With the acceleration and demand for data science HURU School attempts to fill this demand.
In this way, Africa’s youth has the chance to earn a degree while maintaining informal or formal employment. This makes it a financially viable proposition. They can also stay physically connected to their social networks of families and friends. This is important in preventing internal brain drains and exacerbating socio-economic disparities within and between African countries.
Data science lends itself particularly well to being taught through online learning programs. This is because thriving in a virtual classroom requires the same creative, solution-oriented mindset that characterizes the best data scientists. And much of the program’s content—like managing and analyzing data, writing code and deploying software solutions—happens from behind a laptop which is connected to the Cloud anyway.
It is human nature to focus on immediate, locally perceived problems before venturing into fixing more remote ones. So people and organizations from elsewhere in the world may not always identify and try to tackle the African continent’s problems. These issues include improving access and equity in health care; improving road safety and bolstering food security. Data science, led by Africa-based scientists, could play a key role in addressing all of these needs. That’s not to say collaborations with overseas partners should be discarded. These bring complementary expertise; avoid reinventing the wheel, and make it possible to make larger investments and ultimately have a bigger impact. But local academics should take the lead in developing data-driven solutions to local challenges. They understand the social, cultural and political contexts. They are connected to the government departments, non-profit organizations and businesses that can put theoretical models into practice.
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