Overview
Spatial data science utilizes geographic information to analyze how environmental factors relate to specific issues, such as climate change or resource allocation. By analyzing spatial relationships and patterns, you will understand the “where" and "why" behind phenomena. This guide provides e-learning resources on the latest tools and techniques for spatial data science utilizing ArcGIS technology.
This guide is for educators who want to use authoritative Esri web-based learning resources as part of college or university courses. Listed items are available as of October 19, 2026, through Esri Academy. This guide is expected to be updated annually. The information provided in this guide is subject to change without notice. New listings are shown in orange.
All items listed are web courses unless otherwise noted. For full descriptions, use the links provided. The complete Esri Academy catalog can be found at esri.com/training/catalog. Please email GIStraining@esri.com or call (800) 447-9778, ext. 5757 with questions about courses.
A learning plan is a set of learning content with a suggested order. You can create your own plan or copy and edit one that you find. You can assign your plan to students or colleagues and track their progress. See the Esri Academy FAQ page (Filter: Learning Plans) for more information.
You and your students may be eligible for unlimited access to the entire collection of self-paced e-Learning (web courses, training seminars, and more) if your institution has a qualifying product with a current maintenance subscription. To determine whether this applies to you, contact your Esri software license administrator, check online, or email educationinfo@esri.com.
Technology
Spatial data science
The following resources introduce spatial data concepts and skills for spatial data science workflows.
- Spatial Data Science: The New Frontier in Analytics: Explores the application of spatial data science to find patterns and improve predictive modeling. Shows how to integrate popular open data science packages into analyses. (MOOC, 6 weeks; September 23–November 4, 2026.)
- Introduction to AI in ArcGIS: Introduces geospatial AI capabilities in ArcGIS, Esri’s trusted AI approach, implementation use cases, and best practices for adopting AI responsibly. (1 hr., 5 mins.)
Related Learning Plans
ArcGIS foundation
The following web courses cover skills and concepts about GIS and ArcGIS Pro that data science students may find helpful.
- GIS Basics: Presents fundamental components and capabilities of GIS and how ArcGIS can help organizations address business needs. (2 hrs., 35 mins.)
- ArcGIS Pro Basics: Introduces tools to integrate, visualize, analyze, and share data. (50 mins.)
- Introduction to Spatial Data: Introduces foundational concepts of spatial data, including the two models that are used to map spatial data: vector features and rasters. (1 hr., 30 mins.)
- Basics of Geographic Coordinate Systems: Teaches fundamental concepts of coordinate systems used to locate features on the earth. (1 hr., 15 mins.)
- Getting Started with Spatial Analysis: Introduces the six categories of spatial analysis that can help you answer geographic questions. (1 hr., 10 mins.)
- Getting Started with Geoprocessing: Presents key concepts and geoprocessing techniques used for analysis, including setting the geoprocessing environment. (1 hr., 30 mins.)
- Maintaining Attribute Data Integrity Using ArcGIS Pro: Provides foundational concepts and workflows for maintaining spatial data integrity in ArcGIS Pro. Covers data accuracy, consistency, quality control, and topology-based editing tools. (3 hrs., 5 mins.)
- Maintaining Spatial Data Integrity Using ArcGIS Pro: Introduces workflows for verifying and correcting attribute and geometry errors in ArcGIS Pro. Explains how to address common data inconsistencies to support accurate, reliable spatial datasets. (3 hrs.)
- Symbolizing Map Layers: Teaches basic principles of map symbology. (1 hr., 45 mins.)
Esri Tutorial
ArcGIS and Python scripting foundation
The following resources introduce ArcGIS Python libraries, ArcGIS Notebooks, and context necessary to begin Python scripting with geospatial data. (Get an overview of ArcGIS Python Libraries.)
- ArcGIS Notebooks Basics: Introduces ArcGIS Notebooks in ArcGIS Pro. Presents the interface and functionality for creating Python notebooks to perform spatial data analysis. (1 hr.)
- Data Science Workflows Using ArcGIS Notebooks: Introduces the process for performing data engineering tasks using ArcGIS Notebooks in ArcGIS Pro. (2 hrs.)
- Python for Everyone: Introduces basic Python concepts and the Python scripting environment in ArcGIS. (3 hrs., 30 mins.)
- Python Tips and Tricks for ArcGIS:Provides Python tips and shortcuts as presenters go through the decision process to choose an effective scripting approach, as well as build and debug scripts. (Training seminar: Live on June 13, 2024. One-hour recording available thereafter.)
- Python 101 for ArcGIS: Introduces foundational programming concepts and Python language structures and teaches how to add logic to lines of code to automate ArcGIS mapping, analysis, and data management workflows. (Training seminar, 1 hr.)
Related Learning Plan
Esri Tutorial
Scripting with ArcGIS and Python
The following courses teach students how to create Python scripts for common spatial data workflows. The descriptions indicate which solution is used: ArcGIS Pro/ArcPy, ArcGIS API for Python, or both.
- Scripting for Geoprocessing Workflows: Teaches how to create Python scripts using desktop GIS and ArcPy. Teaches a common scripting workflow and how to set geoprocessing environments, access data for automation, choose a cursor, get parameter values, and create a tool. (3 hrs., 30 mins.)
- Creating Python Scripts for Raster Analysis: Uses the Python window in ArcGIS Pro and the ArcPy raster object class to solve a spatial problem. (1 hr.)
- Updating Real-Time Data Using ArcGIS Python Libraries: Explores basic and advanced Python topics to create two feed routines: one that automatically updates feature classes and one that automatically updates feature services. Uses both ArcPy and the ArcGIS API for Python. (ArcGIS Lab, 1 hr., 55 mins.)
- Performing Analysis Using ArcGIS API for Python: Introduces analysis capabilities available in the ArcGIS API for Python and demonstrates the process for integrating them into apps. (1 hr., 35 mins.)
- Visualizing Data Using ArcGIS API for Python: Introduces key visualization methods and customization options for creating maps and charts with the ArcGIS API for Python. (3 hrs., 10 mins.)
Related Learning Plans
R-ArcGIS Bridge
ArcGIS provides a set of statistical cluster analysis tools that allow you to specify each parameter in your analysis. The following courses present concepts and skills needed to use the various tools. (Get an overview of R-ArcGIS Bridge.)
- Introduction to the R-ArcGIS Bridge: Introduces how to integrate R functionality with ArcGIS and its capabilities, such as the ability to access and work with ArcGIS location services in an R environment and to create ArcGIS Pro script tools that use R code. (1 hr., 55 mins.)
Esri Tutorial
Capabilities
Pattern detection
ArcGIS provides a set of statistical cluster analysis tools that allow you to analyze where clusters exist. The following courses present concepts and skills needed to use these tools. More courses are listed in the Higher Ed Guide to Esri E-Learning for Geospatial AI.
Related Learning Plan
Esri Tutorial
Space-time analytics
The following offerings teach methods to extend statistical cluster analysis to find patterns across both space and time.
Related Learning Plan
Esri Tutorials
Predictive analytics and machine learning
These offerings introduce interpolation, regression, classification, and modeling while showing how machine learning supports spatial prediction, pattern discovery, environmental analysis, imagery workflows, and decision-making.
- Geostatistical Interpolation: Introduction: Explains key geostatistical interpolation concepts. Shows how to use ArcGIS Pro to evaluate associated data assumptions. (1 hr., 40 mins.)
- Geostatistical Interpolation: Using Empirical Bayesian Kriging and EBK Regression Prediction: Explains how ArcGIS Pro automates the most difficult aspects of building a valid kriging model. Shows how to perform exploratory spatial data analysis. Teaches how to create prediction surfaces and cross-validate the results. (3 hrs., 45 mins.)
- Geostatistical Interpolation: Reaggregating Data Using Areal Interpolation: Teaches the two main use cases of areal interpolation, which applies kriging theory to data averaged or aggregated within polygons: downscaling a source polygon dataset and using the prediction surface to fill in missing polygon data. (3 hrs., 45 mins.)
- Geostatistical Interpolation: Creating a 3D Prediction Surface: Teaches how to interpolate 3D point datasets using Empirical Bayesian kriging 3D (EBK 3D). (3 hrs., 20 mins.)
- Regression Analysis: Building a Regression Model Using ArcGIS Pro: Teaches how to perform an exploratory data analysis and create a generalized linear regression model to predict monthly temperature at weather stations. (ArcGIS Lab, 1 hr., 40 mins.)
- Regression Analysis: Performing Random Forest Regression Using ArcGIS Pro: Teaches how to train a regression model, then create a new model using the most important independent variables. Uses statistical downscaling to predict monthly temperature. (ArcGIS Lab, 1 hr., 25 mins.)
- Introduction to Regression Analysis: Introduces fundamental regression analysis concepts and provides an overview of common regression techniques that can be performed in ArcGIS Pro. (1 hr., 15 mins.)
- Spatial Interpolation Using ArcGIS Pro: Provides a summary of the different spatial interpolation methods available with the Geostatistical Analyst extension in ArcGIS Pro and teaches how to choose the right methods to create a prediction surface. (Training seminar, 1 hr.)
- Forest-Based Classification and Regression Analysis Using ArcGIS Pro: Teaches how to build, evaluate, interpret, and apply forest-based regression models in ArcGIS Pro to predict unknown values and model complex relationships. (1 hr., 50 mins.)
- Deep Learning Using ArcGIS Pro: Shows how pretrained deep learning models from ArcGIS Living Atlas can support GIS analysis and decision-making. (2 hrs., 15 mins.)
- Deep Learning Using ArcGIS Online: Teaches how to apply pretrained deep learning models in ArcGIS Online to support analysis and operational decision-making. (1 hr., 40 mins.)
- Introduction to AI in ArcGIS: Introduces geospatial AI capabilities in ArcGIS, Esri’s trusted AI approach, implementation use cases, and best practices for adopting AI responsibly. (1 hr., 5 mins.)
- Spatial Data Science: The New Frontier in Analytics: Explores the application of spatial data science to find patterns and improve predictive modeling. Shows how to integrate popular open data science packages into analyses. (MOOC, 6 weeks; September 23–November 4, 2026.)
- Introduction to Image Classification: Introduces techniques for creating thematic classified rasters in ArcGIS. A prerequisite or bridge course for students moving from spatial analysis into machine learning and deep learning imagery workflows. (1 hr., 15 mins.)
- Performing Supervised Pixel-Based Image Classification: Introduces the supervised pixel-based image classification technique for creating thematic classified rasters. (1 hr., 20 mins.)
- Performing Unsupervised Pixel-Based Image Classification: Teaches how to identify computer-created pixel clusters to create thematic classified rasters in ArcGIS. (55 mins.)
- Performing Supervised Object-Based Image Classification: Introduces how to classify images based on user-identified objects or segments, paired with machine learning. (1 hr., 15 mins.)
Related Learning Plan
Esri Tutorials
Suitability modeling
These offerings teach spatial tools and methods that can be used to solve suitability problems, such as finding the best location, allocating resources effectively, or minimizing costs. You might also be interested in the Spatial Statistics Resources page from the Esri Spatial Statistics team.
Related Learning Plan
Esri Tutorials
Multidimensional data
These offerings teach voxels, a data type used to visualize multidimensional data, with applications in atmospheric, oceanic, and geological sciences.
Esri Tutorials
Final Thoughts for educators
You can view lists of new training, training pending retirement, and retired training on the New and Retired Training page. You will receive a message when retirements are announced. (Click to view alerts button while signed in to Training.)
If you plan to assign a MOOC to a group of students or to an entire class, please review the following resources:
To request a transfer of training history from an institutional account to another account, students should contact Esri Customer Service at service@esri.com or (888) 377-4575.
* Note: MOOC dates for 2027 have not been finalized as of the publishing of this guide. Please visit www.esri.com/training/mooc for the latest MOOC offerings and dates.
Spatial Data Science guide URL
The published guide can be accessed with the following link:
https://trainingassets.esri.com/assets/downloads/Higher_Ed_Guide_Esri_Spatial_Data_Science.pdf
