GEOG 527

Credit: 4 hours.

The field of Artificial Intelligence (AI) has made significant progress in recent years, and a number of AI algorithms have even surpassed human ability at tasks such as computer vision, natural language processing and machine translation. The intersection of AI and geospatial analysis is creating massive and unprecedented opportunities for knowledge discovery and innovative applications. A growing number of Geospatial AI and machine learning applications have emerged in a diverse set of disciplines such as geography and geographic information science, agriculture, business, economics, sustainable development, and urban planning. In this course, students will learn a variety of Geospatial AI and Machine Learning (ML) algorithms (e.g., decision trees, and support vector machine) and tools that allow us to investigate and identify patterns, clusters, classes, and anomalies based on various types of geospatial data. The course will include extensive hands-on interactions with geospatial data and applications based on cutting-edge AI and ML techniques.

4 graduate hours. No professional credit. Prerequisite: GEOG 407 or equivalent.