CE-ITCS-2001 - Operation of Commercial and Open Python Spatial Data Science Libraries

Course Description

Spatial data science libraries are collections of pre-existing code that you can utilize as a starting point and customize for your own uses to streamline coding for spatial data science applications. In this course, you’ll use the skills you built in Core Skills in Geospatial Technology and Spatial Python Programming or through equivalent training and learn how those skills translate to Python spatial data science libraries.

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 the second core course for the Spatial Data Science Applications Mastery Certificate and is part of both the GIS-A and GIS-D tracks. If you’re pursuing the mastery certificate we strongly recommend you take this course after the first core course, Core Skills in Geospatial Technology and Spatial Python Programming, and before the third core course, Geographic Visualization with Python.

What You’ll Learn

In this course, you’ll build on the foundational skills you acquired in the Core Skills in Geospatial Technology and Spatial Python Programming course by learning how those skills translate to commercial and open-source Python spatial data science libraries, including ArcPy, ArcGIS API for Python, and GeoPandas. You’ll work towards creating Python source code files in GitHub that demonstrate your ability to utilize ArcPy for geographic data analysis, data conversion, data management, and map automation tasks. In addition, you’ll create Jupyter Notebook source code files in GitHub that will demonstrate your ability to write ArcGIS API for Python code that can perform tasks such as displaying a web map, searching for an address and geocoding, GeoEnrichment, and Smart Mapping. You’ll also create Jupyter Notebook source code files in GitHub that demonstrate you can write GeoPandas code that can perform tasks with the GeoDataFrame such as reading and writing geospatial files, basic geometry options (measure, boundary, centroid), and basic map plotting. These source code file projects will include documentation (comments) from your instructor and can be added to your professional portfolio to show the skills you’ve gained through this course.

How You’ll Learn

This 12-week course is fully online but includes required synchronous online sessions. You can view the times of these sessions by clicking the “+” icon next to the available course dates. Throughout this course, you’ll learn through hands-on practice of the techniques you’re learning about. This includes utilizing Python computer programming exercises with the ArcPy, ArcGIS API for Python, and GeoPandas spatial data science libraries to conduct spatial data science problem-solving assignments. You’ll receive instructor feedback to help improve clarity, especially on the Python and Jupyter Notebook source code files you will create as an addition to your professional portfolio. You will also be creating code statements without the use of generation AI in order to form a foundation of coding knowledge you can use to troubleshoot problems in code generated using generative AI.

Skills You Walk Away With

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

• Apply geospatial technology to geospatial dataset preparation for use with Python spatial data science libraries.
• Operate Python spatial data science development environments.
• Create Python code statements that utilize commercial and open source Python spatial data science libraries.
• Modify existing or AI-generated code statements that utilize commercial and open-source Python spatial data science libraries.

Applies Towards the Following Certificates

• Spatial Data Science Applications : Core Courses