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. Participants 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. The OPTMODEL procedure is used to solve optimization problems that reinforce concepts introduced in the course.
Lernen Sie, wie Sie / Learn how to
- Identify and formulate appropriate approaches to solving various linear, mixed-integer linear, and nonlinear optimization problems.
- Create optimization models commonly used in industry.
- Solve optimization problems using the OPTMODEL procedure in SAS.
Zielgruppe / Who should attend
Those who want to develop the optimization foundation necessary to work as a data scientist, especially those with a strong background in applied mathematics
Verfügbare Schulungsformen / Formats available | Dauer (kann variieren, Details s. Terminliste) | | |
Präsenzkurs: |
1.0 Tag | | |
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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.
In diesem Kurs wird mit folgenden Software Modulen gearbeitet: SAS Optimization Software
