The "Magpie: Services at a Glance" project, developed as part of an MSc in Computing (Advanced Software Development | Data Science) program, provided students with an extensive learning experience encompassing software engineering, data science, machine learning, DevOps, and user-centered design. Magpie is a geographic information system (GIS) designed to provide an intuitive, high-level overview of public amenities in urban areas. The system aggregates, processes, and visualizes location-based data to support urban planners, event organizers, and other stakeholders in making informed decisions about city infrastructure. By integrating machine learning, geospatial analysis, and interactive mapping, Magpie offers a comprehensive, automated solution for identifying and analyzing public resources such as parking spaces, bike-sharing stations, public toilets, and other essential amenities.

One of the primary learning outcomes of the project was the enhancement of students' ability to solve real-world technical problems. The development of Magpie required students to design a system capable of aggregating, analyzing, and visualizing public amenities data for urban planners. This necessitated an in-depth understanding of system architecture, backend and frontend development, and geospatial data processing. The Magpie project also mirrored real-world software development challenges, requiring students to work in interdisciplinary teams.

They developed proficiency in:
- Task Delegation and Team Dynamics: Assigning roles based on expertise, fostering a collaborative work environment.
- Risk Management and Problem-Solving: Identifying technical and organizational challenges early, and implementing contingency plans to mitigate risks.
- Effective Communication: Documenting progress, presenting findings, and synthesizing feedback from stakeholders.

These skills prepared students for careers where teamwork and communication are as vital as technical acumen.

The Magpie project was a transformative learning experience, equipping students with a comprehensive skill set for software and data science careers. The integration of advanced technologies, human-centered design, and collaborative problem-solving not only prepared them for technical roles but also fostered innovation and critical thinking. Future iterations of this project could focus on expanding machine learning capabilities, integrating real-time data feeds, and refining UX based on broader user feedback. The project’s success demonstrates the value of experiential learning in computing education, emphasizing the need for academia to embrace industry-relevant, problem-solving approaches. By undertaking this complex, interdisciplinary project, students not only honed their technical expertise but also cultivated the adaptability and resilience essential for success in a rapidly evolving digital world.

Keywords: e-learning, Geographic Information Systems, Teamwork.