Optimization Concepts For Data Science And Artificial Intelligence

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What you will learn

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.

Shareable Certificate Earn a Cerfiticate upon completion
On Demand, Live Online, Face to Face Start instantly and learn at your own schedule
Flexible Schedule Set and maintain flexible deadlines
Intermediate For those with working experience or likely to have completed foundation level training
English Subtitles: English

This course consists of 4 lessons

Introduction to Mathematical Optimization: Introduction - A simple example - The OPTMODEL procedure.

Linear Programming: 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 (self-study) - Reading SAS data sets (self-study).

Nonlinear Programming: Introduction to nonlinear programming - Solving nonlinear programming problems using the OPTMODEL procedure.

Integer and Mixed-Integer Linear Programming: Introduction to integer and mixed-integer linear programming - Solving integer and mixed-integer linear programming problems using PROC OPTMODEL.

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