Optimization Basics

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This course introduces students to optimization techniques. The course exposes students to basic concepts about the implementation of numerical optimization techniques, assuming that the student does or does not have any kind of idea on these topics. The approach used for teaching this optimization course is based on students having a basic understanding of optimization problem formulations, the important aspects of various optimization algorithms, also about the knowledge of how to use programming to solve optimization problems. The lectures in this course cover Graphical Approaches for Optimization Problems, Notations and Classification of Optimization, Unconstrained Optimization, and Constrained Optimization. Various algorithms such as Golden Section, Gradient Descent, Newton's Methods, Augmented Lagrangian, and Sequential Quadratic Programming (SQP).





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Course Instructor 

Rahul Rai

Dean's Distinguished Professor at Clemson University 
I am Dr. Rahul Rai. I am a Dean's Distinguished Professor in Automotive Engineering and Computer Science and Associate Director, Artificial Intelligence Research Institute in Science and Engineering (AIRISE) at Clemson University. I also have industrial research center experiences at United Technology Research Center and Palo Alto Research Center. I am the Founder and CEO of AI Brilliance, a company focused on empowering people to learn about data science, machine learning, and AI concepts.
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