CE-ITCS-3003 - Geospatial Generative AI

Course Description

Generative AI is a powerful tool, but it’s only as powerful as the prompts you engineer while using it. Using generative AI for writing code in spatial data science applications is no exception, and in this course you’ll dive into how to use AI effectively to get the results you want, whether that’s creating code you can use as a starting point, using it to debug code you’ve written, and more.

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 looking to advance their skills. This is one of the elective choices for the Spatial Data Science Applications Mastery Certificate and is recommended for students in both the GIS analyst (GIS-A) and GIS development (GIS-D) tracks who wish to utilize generative AI to increase productivity in spatial data science code generation tasks. Previous knowledge of Python or other coding language in the context of geospatial data is required as well as the background necessary to be able to critically analyze and manipulate code produced by a generative AI system. If you don’t have these skills already, we recommend you take the Core Skills in Geospatial Technology and Spatial Python Programming course, and if you’re planning to pursue the mastery certificate, we recommend that you take the three core courses in this program before taking this elective.

What You’ll Learn

In this course, you’ll learn how to engineer prompts to utilize generative AI for interaction with large language models with the goal to create Python and other code files relevant to spatial data science applications. You’ll cover topics including how to develop precise AI prompts for generating code to achieve specific spatial data science tasks for visualization and data analysis, how to generate AI prompts for debugging code produced by generative AI, and understanding limitations and opportunities with generative AI for spatial data science applications. For the professional portfolio you’ll build throughout the courses in the Spatial Data Science Applications Mastery Certificate program to demonstrate how you can use your skills in real-world applications, you’ll develop a case study that examines a real-world spatial data science project or scenario where you’ll need to apply the generative AI techniques acquired in this course. Overall, this course will focus on how you can use generative AI to increase productivity when generating spatial data science code.

How You’ll Learn

This 12-week course is fully online with required synchronous sessions throughout the course. To learn more about the timing of these required sessions, click the “+” icon next to the available course start dates. Throughout this course, you’ll engage in activities including AI prompt-building exercises, code analysis exercises, debugging exercises, and more to get hands-on practice with the concepts you’re learning about. For your project that will be part of your professional portfolio, you’ll develop a case study of when you will need to use generative AI in real-world spatial data science projects, which will include documenting your process and reflecting on the limitations and opportunities you encountered when utilizing generative AI for spatial data science applications.

Skills You Walk Away With

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

• Develop precise prompts that allow for generative AI to create Python code or other code that can achieve spatial data science tasks with visualization and data analysis.
• Analyze code outputs, identifying and troubleshooting problems with AI-generated code.
• Develop prompts to guide the AI in fixing problems with AI-generated code.
• Explain the ethical considerations of using generative AI in spatial data science applications.

Notes

Applies Towards the Following Certificates

• Spatial Data Science Applications : GIS-Development Elective Track