Predicting Extreme Climate Behavior with Machine Learning

Throughout Predicting Extreme Climate Behavior with Machine Learning, you'll explore both theoretical concepts and practical applications or machine learning and data analysis. You'll begin by analyzing unsupervised learning algorithms, mastering techniques like clustering and dimensionality reduction, and applying them to real-world climate datasets. You'll also explore supervised learning, gaining hands-on experience with algorithms such as Logistic Regression, Decision Trees, and Neural Networks. This course can be taken for academic credit as part of CU Boulder's Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder's departments of Applied Mathematics, Computer Science, Information Science, and others.

The degree offers targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Data Science: https://www.coursera.org/degrees/master-of-science-data-science-boulder