CE-ITCS-3000 - Commercial Python for Spatial Statistics and Machine Learning

Course Description

Being able to analyze the spatial data you collect is vital to using your data to its fullest potential. In this course, you’ll use spatial data science libraries for spatial analysis and gain skills in different analytical methods with an emphasis on working with larger volumes of geospatial data.

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 course is one of the five elective options for the Spatial Data Science Applications Mastery Certificate and is part of the GIS Analyst (GIS-A) track, which is designed for professionals who already have prior experience and skills pertaining to geospatial data and databases, using geospatial technology, conducting spatial analysis, and creating geographic visualizations. If you’re pursuing the mastery certificate we strongly recommend you take this course after finishing all three core courses.

What You’ll Learn

In this course, you’ll learn how to utilize commercial spatial data science libraries ArcPy and ArcGIS API for Python for spatial analysis. Topics you’ll cover include advanced ArcPy scripting and creating ArcGIS Pro geoprocessing tools from code, spatial statistics, and machine learning. You’ll also practice writing new code as well as modifying existing code in commercial spaces to conduct spatial analysis using spatial statistics and machine learning core concepts. By the end of this course, you’ll create Python source code files in GitHub based on an existing or AI-generated Python script that you will make modifications and provide extensive documentation (comments) about changes made to demonstrate your ability to write or utilize existing ArcPy code 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 you will write, based on existing code, or based on code written through generative AI with extensive documentation (comments) that demonstrates your ability to write or modify ArcGIS API for Python code that can perform tasks such as spatial analysis using prediction, suitability, patterns, and clustering.

How You’ll Learn

This 12-week course is fully online with weekly synchronous 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 about utilizing commercial spatial data science libraries for spatial analysis through hands-on practice with spatial statistics, coding exercises, and more. You’ll get experience using analytical methods with a focus on working with larger volumes of geospatial data to provide insight.

Skills You Walk Away With

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

• Create and revise Python code generated from geoprocessing tools.
• Write Python code that can use ArcPy and ArcGIS API for Python.
• Identify and modify existing ArcPy and ArcGIS API for Python Code that can be incorporated into a spatial data science workflow.
• Compute spatial statistics and implement machine learning concepts.
• Implement Python code that can conduct spatial analysis using prediction, suitability, patterns, and clustering in a commercial library.
• Illustrate how various Esri commercial technologies integrate into spatial data science workflows.

Course Outline

Being able to analyze the spatial data you collect is vital to using your data to its fullest potential. In this course, you’ll use spatial data science libraries for spatial analysis and gain skills in different analytical methods with an emphasis on working with larger volumes of geospatial data.

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 course is one of the five elective options for the Spatial Data Science Applications Mastery Certificate and is part of the GIS Analyst (GIS-A) track, which is designed for professionals who already have prior experience and skills pertaining to geospatial data and databases, using geospatial technology, conducting spatial analysis, and creating geographic visualizations. You can learn more about which track is best for your career trajectory and goals here [link to mastery certificate page]. If you’re pursuing the mastery certificate we strongly recommend you take this course after finishing all three core courses.

What You’ll Learn

In this course, you’ll learn how to utilize commercial spatial data science libraries ArcPy and ArcGIS API for Python for spatial analysis. Topics you’ll cover include advanced ArcPy scripting and creating ArcGIS Pro geoprocessing tools from code, spatial statistics, and machine learning. You’ll also practice writing new code as well as modifying existing code in commercial spaces to conduct spatial analysis using spatial statistics and machine learning core concepts. By the end of this course, you’ll create Python source code files in GitHub based on an existing or AI-generated Python script that you will make modifications and provide extensive documentation (comments) about changes made to demonstrate your ability to write or utilize existing ArcPy code 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 you will write, based on existing code, or based on code written through generative AI with extensive documentation (comments) that demonstrates your ability to write or modify ArcGIS API for Python code that can perform tasks such as spatial analysis using prediction, suitability, patterns, and clustering.

How You’ll Learn

This 12-week course is fully online with weekly synchronous 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 about utilizing commercial spatial data science libraries for spatial analysis through hands-on practice with spatial statistics, coding exercises, and more. You’ll get experience using analytical methods with a focus on working with larger volumes of geospatial data to provide insight.

Skills You Walk Away With

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

• Create and revise Python code generated from geoprocessing tools.
• Write Python code that can use ArcPy and ArcGIS API for Python.
• Identify and modify existing ArcPy and ArcGIS API for Python Code that can be incorporated into a spatial data science workflow.
• Compute spatial statistics and implement machine learning concepts.
• Implement Python code that can conduct spatial analysis using prediction, suitability, patterns, and clustering in a commercial library.
• Illustrate how various Esri commercial technologies integrate into spatial data science workflows.

Notes

Applies Towards the Following Certificates

• Spatial Data Science Applications : GIS-Analyst Elective Track