Focus on artificial intelligence (AI) and machine learning (ML) methods and their applications on geospatial problems. Explore python programming and GIS data preparation for machine learning models, ML foundations, regression, clustering, decision tree and random forest, neural network, embedding, and location representation learning. Three lecture hours and one laboratory hour a week for one semester. Geography 327G and 356T (Topic: Intro to Geospatial AI) may not both be counted. Offered on the letter-grade basis only. Prerequisite: Upper division standing.