Optimization Concepts for Data Science and Artificial Intelligence
There is a new version of this course. Please see Optimization Concepts for Data Science and Artificial Intelligence.
This course focuses on linear, nonlinear, and mixed integer linear optimization concepts in SAS Viya. Students learn how to formulate optimization problems and how to make their formulations efficient by using index sets and arrays. The demonstrations in the course include examples of diet formulation and portfolio optimization. Learn the OPTMODEL procedure and open source tools to formulate and solve optimization problems.Learn how to
Who should attendThose who want to develop the optimization foundation necessary to work as a data scientist, especially those with a strong background in applied mathematics
Before enrolling in this course, you should be comfortable with data manipulation using basic SAS tools. You can gain this course-specific knowledge in data manipulation by completing the SAS Programming 1: Essentials course. Some knowledge of linear programming concepts and matrix algebra is helpful but is not required.
This course addresses SAS Optimization software.
Introduction to Mathematical Optimization