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Stanford EE364A: Convex Optimization


  • Offered by: Stanford
  • Prerequisites: Python, Calculus, Linear Algebra, Probability Theory, Numerical Analysis
  • Programming Languages: Python
  • Difficulty: 🌟🌟🌟🌟🌟
  • Class Hour: 150 hours

Professor Stephen Boyd is a great expert in the field of convex optimization and his textbook Convex Optimization has been adopted by many prestigious universities. His team has also developed a programming framework for solving common convex optimization problems in Python, Julia, and other popular programming languages, and its homework assignments also use this programming framework to solve real-life convex optimization problems.

In practice, you will deeply understand that for the same problem, a small change in the modeling process can make a world of difference in the difficulty of solving the equation. It is an art to make the equations you formulate "convex".

Course Resources

Personal Resources

All the resources and assignments used by @PKUFlyingPig in this course are maintained in PKUFlyingPic/Standford_CVX101 - GitHub