Strengthening the AI and ML skills and communities in Malawi
AI, machine learning, and data science inherently embrace a multidisciplinary approach, holding great potential for addressing challenges in domains such as education, healthcare, climate change mitigation, coping with extreme events, and disaster risk reduction.
This initiative brings together academics, professionals, and policy makers to share ideas, research findings, technology tools, scientific methodologies, and perspectives on AI, ML and data science in Malawi, Africa and internationally.
Since 2019 we have organised the Deep Learning Indaba Malawi events.
How can AI and Data Science be leveraged?
High quality dataset are crucial for analysis and modelling. Both language and culture are hard to model by machines, hence these datasets need to capture multiple perspectives. When it comes to language and culture there is a lot of scope for developing creative datasets. Several members of IndabaX Malawi have been involved in developing datasets for machine translation. If this is something you are passionate about, get in touch.
This is an area in which AI can excel. Predicting events such as floods, landslides, earthquakes is complicated due to the influences of many factors, providing early warnings. Early warning systems are crucial in limiting human casualties and material loss.
Machine Learning is said to play a major role in transforming healthcare. The combination of big health datasets and the ability of ML to analyse large volumes of clinical and medical data, ML has the potential to uncover hidden patterns and trends that can be crucial for early diagnosis, disease prediction, and personalized treatment development.
There are multiple use case for AI/ML in education. Our first competition we hosted was utilising ML to analyse usage and engagement on an online learning platform. Recently, we see the use of Large Language Models (LLMs) in education and all the questions, opportunities and challenges that this may raise.
Send any queries to indabax@poly.ac.mw or to ataylor@poly.ac.mw