Friday 20 March 2020: With social distancing in place and serious concerns about the spread of coronavirus, Zindi will demonstrate the power of their online platform to crowd-solve challenges in health, education, environmental conservation, and business through the UmojaHack Africa competition which takes place on Saturday, 21 March 2020.
Zindi will host the first-ever virtual inter-university artificial intelligence (AI) hackathon for students across Africa. Over 70 universities from 17 African countries, with an estimated 2500 students, have registered to participate in the hackathon taking place on Zindi’s online platform.
Sponsors of the event include Microsoft, African Bank, Google Research, Liquid Telecom, Alliance4ai, Instadeep, and the Field Institute.
African Bank’s Executive of Credit and Data Science, Vere Millican says African Bank is delighted to be involved with the first-ever Zindi Inter-University Umoja Hackathon. “African Bank has a total of 77 data science professionals, 20 of which are currently attending the Explore Data Science Academy. We are committed to upskilling and employing brilliant data scientists and welcome opportunities like this to develop and find young talent.”
The top-performing team in each of three challenges will be awarded prize money of $1000 USD, $600 USD, and $400 USD respectively. Teams placing 2nd and 3rd in each category will be awarded learning opportunities from one of the sponsors of the event. The associated university will receive $7500 (1st category), $5000 (2nd category), and $2500 (3rd category). “We are excited to put in funds as prize money to reward and recognise Africa’s best young data scientists,” says Millican.
These teams of data scientists will be working to find the best solution for three real world challenges:
- Hotspot Fire Prediction Challenge
Teams are challenged to figure out the dynamics of where and when fires occur in the Democratic Republic of Congo, a country dealing with the health and environmental impacts of slash and burn agriculture. They must also predict how these dynamics will play out in the future, under different climatic conditions. The challenge is to build a model capable of predicting the burned area in different locations.
- SAEON Marine Invertebrate Classification Challenge
Teams are challenged to develop an automated image classification solution for photographs of marine invertebrate taken by researchers in South Africa. The solutions will reduce the resources needed to manually process photos and allow researchers to identify changes in marine life faster and more efficiently, to better monitor and understanding climate change impacts.
- Xente Purchase Prediction Challenge
Teams are challenged to create a machine learning model to predict purchase behaviour of customers on the Xente app, based on their purchase history. Xente is a Ugandan e-commerce start-up that makes it easy for consumers to make payments, get loans, and shop using simply a mobile phone. The resulting models and solutions will enable target marketing and create a better customers experience.
Millican says African Bank is particularly interested in the Xente Purchase Prediction Challenge. “It resonates so well with African Bank as data analysis sits at the heart of our value proposition for customers. As an organisation we are committed to using data much more intelligently to inform our decision making processes and add value to our customers through the propositions we offer them. We are excited to see what these brilliant young minds come up with.”
The machine learning solutions developed during UmojaHack Africa and the skills developed by the participants promise large-scale improvements to people’s lives, and it is no surprise that some top brands have got in on the action and partnered with Zindi to sponsor this exciting venture.