About Event

This course is designed to equip faculty members, researchers, and professionals with an opportunity to enhance their knowledge and skills in the field of Machine Learning and Deep Learning in QGIS and ArcGIS as applied for geospatial analysis, namely Geographic Information Systems (GIS) and Remote Sensing. This course is designed to take users who use QGIS & ArcGIS for basic geospatial data/GIS/Remote Sensing analysis to perform more advanced geospatial analysis tasks including object-based image analysis using a variety of different data and applying Deep Learning & Machine Learning state of the art algorithms. In the course, participants will be able to apply such Machine Learning algorithms as Random Forest, Support Vector Machines, Decision Trees, Convolutional Neural Networks (and others) for Remote Sensing and geospatial tasks. By the end of the course, participants will feel confident and completely understand the Machine and Deep Learning applications in Remote Sensing & GIS technology and how to use Machine and Deep Learning algorithms for various Remote Sensing & GIS tasks, such as land use and land cover mapping (classifications) and object-based image analysis (segmentation, object detection) and regression modeling in QGIS and ArcGIS software. This course will also prepare users for using GIS with open source and free tools (QGIS) and a market-leading software (ArcGIS)