Optimization Concepts for Data Science
OPCON : OPCN51
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.
The e-learning format of this course includes Virtual Lab time to practice.
Learn How To
- Identify and formulate appropriate approaches to solving various linear and nonlinear optimization problems.
- Create optimization models commonly used in industry.
- Formulate and solve a data envelopment analysis.
- Solve optimization problems using the OPTMODEL procedure in SAS.
Who Should Attend
Those 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
Prerequisites
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 should complete an undergraduate course in operations research that includes linear programming, have recent experience using linear programming, or be comfortable with matrix algebra.
- You should be able to execute SAS programs and create SAS data sets.
SAS Products Covered
SAS/OR
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).
- Applied data envelopment analysis.
- Reading SAS data sets (self-study).
- Introduction to nonlinear programming.
- Solving nonlinear programming problems using the OPTMODEL procedure.
Live Class Schedule
Duration: 7 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.
This course isn't publicly scheduled, but private training and mentoring may be available. Contact us to explore options.
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.