Optimization Concepts for Data Science
This course focuses on linear, nonlinear, and efficiency optimization concepts. You 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 data envelopment analysis and portfolio optimization. The OPTMODEL procedure is used to solve optimization problems that reinforce concepts introduced in the course.
The e-learning format of this course includes Virtual Lab time to practice.Learn how to
Who should attendThose who want to develop the advanced knowledge and skills necessary to work as a data scientist, especially those with a strong background in applied mathematics
Before enrolling in the data science certification program, you should have completed all coursework for the SAS Certified Big Data Professional program or passed the Big Data Certification exams. Before attending this course:
You can gain this course-specific knowledge and skill by completing the SAS Programming 1: Essentials course.
This course addresses SAS/OR software.
Introduction to Mathematical Optimization