This course is designed to provide mentee(s) with practical skills in Geographic Information Systems (GIS) using open-source Python tools. Participants will explore core GIS concepts and techniques, focusing on the application of Python libraries to manage and analyze spatial data. A key component of the course will be learning how to scale up GIS processing by implementing these tools in high-performance computing (HPC) systems. This approach will enhance the capability to handle larger datasets and more complex analyses, making GIS more accessible and integrative with their existing projects. By the end of this course, attendee(s) will have gained proficiency in applying Python to real-world geospatial challenges and scaling their solutions on HPC platforms, enhancing both their analytical capabilities and their ability to contribute to diverse cyberinfrastructure endeavors.
- Basic Understanding of GIS and Python: Familiarity with GIS concepts and some programming experience, preferably in Python.
- Interest in HPC Applications: A keen interest in learning about high-performance computing as it applies to GIS.
- Proactive Learner: Enthusiasm for learning and applying new tools and techniques in GIS.
- Project Involvement: Currently involved in or planning a project that could benefit from enhanced GIS capabilities.
- Collaborative Spirit: Openness to feedback and collaboration within a mentorship framework.