CE-ITCS-5000 - Current Issues in Spatial Data Science Problem-Solving

Course Description

If you are pursuing the Mastery Certificate in Spatial Data Science Applications, this required capstone course will help you synthesize the skills you’ve learned throughout the core and elective courses you’ve taken into work that demonstrates your abilities. This course is required to complete the mastery certificate.

Is This Course for You?

This course is designed for data science professionals currently working in geospatial analysis, data analysis, data science, or other types of computerized data who have already completed the three core courses in the Spatial Data Science Applications Mastery Certificate. This capstone course is required for those pursuing both the GIS development (GIS-D) and GIS analyst (GIS-A) pathways. Once you’ve completed this course, you will earn your mastery certificate and be ready to advance your career in geospatial, data science, and other industries involving geospatial data and professional industry certifications.

What You’ll Learn

In this course, you’ll learn how to apply the spatial data science skills learned in prior coursework to your specific interests and career goals. You’ll be given the opportunity to either develop a spatial data science project of your own with guidance from your instructor or receive a topic from your instructor related to current issues in spatial data science problem-solving. There is a focus in this course on teaching you how to think critically when conducting real-world spatial data science projects. Your project topic could relate to climate change, natural hazards/disasters, environmental monitoring, health care, and infectious disease spread. Throughout your project, you’ll gain skills related to how to define a spatial problem, generate research questions related to the problem, identify specific and relevant spatial data science methodologies to answer research questions, conduct a spatial data science analysis using the methodologies, and present final results in visual formats.

How You’ll Learn

This six-week course is fully online with required synchronous sessions. You can learn more about when these sessions will take place by clicking the “+” icon next to the available course run dates. Throughout this course, there will be established milestones that you should be meeting while working on your final capstone project that will be laid out by your instructor. You’ll use your existing Python or R programming skills and may need to conduct independent research on how to use the programming language of your choice in ways not covered in previous courses as needed for the completion of your project.

Your capstone project will serve as a final addition to the professional portfolio developed throughout the courses in the Spatial Data Science Applications Mastery Certificate program. In this final project report, you’ll include a clear problem statement, goals to address the problems, visual artifacts such as maps and data graphics that communicate results, and clear articulation and justification of methods learned from previous courses to achieve the goals that unequivocally demonstrate skills learned. This report must be written by you and cannot be AI generated as an understanding of the technical report writing is a key part of this project. The source code files in whatever format you choose will be in GitHub, and these files can either be written manually, based on existing code, and based on AI generated code, and must include extensive documentation (comments) reviewed by the instructor for clarity. In order for your project to be successful, it must demonstrate that you can complete an entire spatial data science project from start to finish with professional caliber results that allow the project to be shared with others through open-source formats or commercialization.

Skills You Walk Away With

By the end of this course, you will be able to:

• Define a spatial data science problem with clear parameters for analysis.
• Identify research questions related to a spatial data science problem.
• Articulate relevant spatial data science methodologies for a spatial data science problem-solving exercise.
• Utilize Python or R programming skills to implement spatial data science methodologies.
• Utilize geographic visualization skills to present problem-solving results.
• Formulate project artifacts (project specifications, source code, written results, graphics, and diagrams) into a professional work portfolio.

Notes

Applies Towards the Following Certificates

• Spatial Data Science Applications : GIS-Analyst Elective Track, GIS-Development Elective Track