Learning goals

After the completion of the course, students:

• have improved scientific skills in conceptualizing complex location-related problems in the society related to sustainability.

• can identify how the sustainability problems can be studied with geospatial data and computational approaches.

• have technical, hands-on competencies to identify, use, assess, process, and enrich geospatial data to study sustainability related topics.

• have competencies to identify, use and assess spatial data science methodologies in their analysis, and can apply them in practice to a range of sustainability related topics with Python programming language.

• can plan and manage team work over several weeks with their own sub goals, milestones and deliverables, and recognize the roles and responsibilities of members in a project team, linked with the team deliverables.

• can conduct reproducible and open science using computational notebooks and programming.

• can present their work to others, and peer-evaluate other students work.