Deep Learning in ArcGIS Pro for Geospatial Analysis

Geospatial data is growing exponentially, and traditional analysis methods can no longer keep up with the volume of high-resolution imagery. Harnessing the power of artificial intelligence within your geographic information system (GIS) is the key to unlocking deeper spatial insights. This course guides you through the process of applying deep learning models directly within ArcGIS Pro. You will transition from understanding core machine learning definitions to executing sophisticated object detection and pixel classification workflows on real-world remote sensing data, all through clear written explanations and step-by-step walk-throughs. What you'll learn: - Understand the foundational concepts of machine learning, neural networks, and deep learning in a GIS context - Configure the ArcGIS Pro environment with necessary deep learning frameworks and libraries - Prepare and label geospatial training data for object detection and image classification tasks - Deploy pretrained models from the ArcGIS Living Atlas to accelerate your analysis workflows - Run convolutional neural networks to automatically detect features and classify land cover in satellite imagery - Evaluate model performance and refine parameters to optimize your geospatial analysis results The curriculum begins with essential terminology and setup procedures before moving into hands-on data preparation, model execution, and practical post-processing techniques. You will read detailed workflow explanations, study configuration examples, and learn how to interpret model outputs within ArcGIS Pro. This course is designed for GIS analysts, geographers, environmental scientists, and remote sensing beginners who want to integrate artificial intelligence into their spatial workflows. No prior programming or deep learning experience is required. Start your journey into geospatial artificial intelligence and elevate your spatial analysis skills today.