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Building Africa’s Data Science and AI Capacity

Building Africa’s Data Science and AI Capacity: Lessons from Training, Collaboration, and Community Engagement ABOUT THE TALK: Africa is at the dawn of a data-driven era. From health and agriculture to business and education, the continent is witnessing an explosion of data that holds enormous potential for innovation, economic growth, and social transformation. Already, applications such as AI-powered tools for predicting disease outbreaks, diagnosing crop diseases, and improving maternal health outcomes are demonstrating the real-world value of data science and artificial intelligence. Yet, unlocking this potential requires one crucial ingredient: a new generation of skilled data scientists equipped to turn raw data into actionable solutions. This talk explores the evolving landscape of data science and AI training in Africa, focusing on the interplay between formal education and informal, community-led ecosystems. It argues that success will depend on hybrid pathways of learning, strong communities of practice, and purpose-driven innovation that responds to Africa’s unique contexts. Ultimately, the vision is not only to catch up with the global data revolution but to shape it with solutions rooted in Africa’s realities and aspirations. ABOUT THE SPEAKER: Dr. Verrah Otiende is an Assistant Professor of Statistics and Data Science at United States International University–Africa (USIU-Africa). She works at the intersection of computational statistics, artificial intelligence, and global health, with a focus on advancing equitable, data-driven solutions to Africa’s pressing challenges. Currently an Eric and Wendy Schmidt AI in Sciences African Faculty Fellow based at the University of Michigan’s MIDAS, she is developing AI tools to help vulnerable communities in Kenya adapt to extreme urban heat driven by climate change. Her research combines machine learning, Bayesian modeling, and agent-based simulations to map heat risk, predict health impacts, and inform interventions such as early warning systems, shaded areas, and cooling stations. Her broader expertise spans computational global health, including modeling Rift Valley Fever in Uganda, COVID-19 in Kenya, and harmonizing cohort health data across Africa. Beyond research, she co-designed the TI Analytics Accelerator Program (USIU-Africa & Michigan State University, funded by AAP), convenes the USIU-Africa Data Science Summit, and leads outreach initiatives like EmpowerHer MathGirl.