Project based learning as an approach for teaching and learning has a strong history in engineering education where alongside core technical content, students learn transversal skills like collaboration, critical thinking and applied problem solving. This paper explores the motivation, design and implementation of a group-project based learning module within a masters level data science programme as a dissertation unit, emphasising real-world problem-solving as the core learning approach.

The unit focuses on industry-led challenges, where student teams engage in data-driven projects focusing on authentic problems from sectors such as healthcare, finance, and sustainability. Didactic content as well as principles followed to design the unit in order to promote student success and satisfaction are described alongside practices used to ensure inclusivity and skills development.

The motivation to add this unit on the masters in data science programme as an alternative to the traditional individual research project, is to increase student satisfaction and employability, but this does not come without its issues. Challenges around choice, cohort size, staff workload and student satisfaction are explored with some proposed solutions. Data from a short survey conducted over current students is presented which shows the students views regarding some of theses challenges.

This work contributes to the discourse on innovative pedagogical approaches in data science education, providing insights for educators aiming to design experiential, inquiry-driven curriculum for students.

Keywords: PBL, Project Based Learning, Group Work, Data Science, Curriculum design.