The Department is pleased that we are offering CEE 415 this spring.  It is open and available for registration.  More information is below.

Course Description: This course aims to provide students with an overview of machine learning basic concepts and common tools; introduce machine learning for civil engineering applications; expose students to basic technical elements of machine learning; and equip students with basic capabilities for common machine learning tasks (including regression, supervised and unsupervised learning, decision trees) and their applications in civil engineering. The course will be taught using Python programming language, and students will work on several projects to apply the concepts learned in class.

Pre-requisites:
• MATH308 (Matrix Algebra), MATH124-126 (Calc/Analytic Geom), and IND E 315 (Probability and Statistics for Engineers) or STAT390
• Prior programming experience (we will use Python for this class)

Learning Objectives: By the end of this class, students will:
·   Describe basic machine learning concepts and common tools;
·   Implement and evaluate these tools and concepts using Python;
·   Analyze and discuss the outputs of Python-based machine learning implementation;
·   Generate professional-quality documents and presentations in a team setting that describe the student’s process of moving through each of the elements listed above.

If you have questions about the class, please contact instructor Grace Jia: gracejia@uw.edu