Convex Optimization

edX MOOC / Non-credit Free
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Convex Optimization

About this course

This course concentrates on recognizing and solving convex optimization problems that arise in applications. The syllabus includes: convex sets, functions, and optimization problems; basics of convex analysis; least-squares, linear and quadratic programs, semidefinite programming, minimax, extremal volume, and other problems; optimality conditions, duality theory, theorems of alternative, and applications; interior-point methods; applications to signal processing, statistics and machine learning, control and mechanical engineering, digital and analog circuit design, and finance.

What you'll learn

  • understanding convex sets and functions
  • formulating and solving least-squares and quadratic programming problems
  • applying interior-point methods
  • utilizing duality theory in optimization

Course objectives

  • recognize and classify convex optimization problems
  • solve practical optimization challenges in diverse fields
  • analyze optimality conditions and their implications

Skills you'll gain

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