Data Science Africa Announces 2026 Summer School for Emerging Researchers

Data Science Africa (DSA) has announced the launch of its 2026 Summer School, a three-day intensive programme aimed at strengthening data science capabilities among students and early-career researchers. The annual initiative is designed to provide participants with a strong blend of theoretical understanding and hands-on experience in contemporary data science, with a focus on challenges and opportunities relevant to both African and global contexts.

The Summer School places strong emphasis on applied learning, combining core concepts with practical exercises and project-based activities. Through this approach, participants will gain exposure to real-world data problems while developing critical analytical and problem-solving skills essential for research, industry, and policy-oriented roles in data science.

The curriculum for the 2026 edition covers a wide range of foundational and advanced topics. Participants will receive training in Python programming for data analysis, data storytelling, and visualisation techniques that help communicate insights effectively. The programme also introduces machine learning fundamentals, including supervised, unsupervised, and reinforcement learning methods, along with sessions on ethics and responsible artificial intelligence to address fairness, accountability, and transparency in AI systems.

Advanced modules include agentic AI and multi-agent systems, multimodal AI and large language models, explainable AI, and model interpretability. Special focus will also be given to deploying AI in resource-constrained environments and developing natural language processing solutions for African languages, reflecting the programme’s commitment to inclusive and context-aware innovation. Participants will apply their learning through hands-on projects using real-world datasets.

The Summer School is open to undergraduate and postgraduate students, researchers, and working professionals who engage with large-scale or specialised datasets. Applicants are expected to have a strong academic foundation in mathematics, statistics, computer science, engineering, or related disciplines. The programme aims to enhance both technical expertise and critical thinking skills among attendees.

Interested candidates must complete an online registration process, which includes a short beginner-level quiz. Applicants are required to download a registration package, complete the prescribed exercises, and upload the finished file through the official portal. Careful adherence to instructions is essential for successful submission.

The application window opens on 26 January 2026 and closes on 15 March 2026, with acceptance notifications scheduled for 31 March 2026. Due to limited seats, early applications are encouraged.