Optimization Concepts for Data Science and Artificial Intelligence
3h 22m + Hands-On Practice
Available in:
Optimization Concepts for Data Science and Artificial Intelligence
ORVY : ORVY41
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
- 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.
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
Prerequisites
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.
SAS Products Covered
SAS Optimization
Course Outline
Introduction to Mathematical Optimization
- Introduction.
- A simple example.
- The OPTMODEL procedure.
- Introduction to linear programming.
- Formulating and solving linear programming problems using the OPTMODEL procedure.
- Using index sets and arrays in the OPTMODEL procedure.
- Dual values and reduced costs in the simplex method (self-study).
- Reading and writing data in the OPTMODEL procedure.
- Introduction to nonlinear programming.
- Solving nonlinear programming problems using the PROC OPTMODEL.
- Introduction to integer and mixed-integer linear programming.
- Solving integer and mixed-integer linear programming problems using the OPTMODEL procedure.
- SAS Viya and open source integration.
- SAS Viya Python APIs.
Live Class Schedule
Duration: 14 hours
Step into our live classes and experience a dynamic learning environment where you can ask questions, share ideas, and connect with your instructor and classmates. With on-demand lab hours, you can explore the material at your own pace. Our globally acclaimed instructors will motivate you to think bigger, so you can take what you've learned and achieve your biggest goals.
Live Class Schedule
SOLD SEPARATELY
Private Training
Get training tailored specifically for your team, led by expert SAS instructors. Choose from virtual sessions, or training at your location (or ours). Perfect for teams seeking a customized curriculum and plenty of interaction with a SAS specialist. We'll schedule it at a time that works for you.
Mentoring Services
Take your training to the next level with personalized mentoring. While private training offers structured coursework, mentoring provides hands-on, real-time support from a subject matter expert. As you work with your own data, you'll receive expert guidance to help you uncover insights, unlock the full potential of your data, and make faster progress. Perfect for those looking to apply what they’ve learned and see quicker results.
This course helps prepare you to earn the following SAS Credentials:
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