This course provides a comprehensive introduction to computational methods used for solving optimization problems, with a focus on the role of vector calculus in these methods. Students will explore various optimization techniques, including both unconstrained and constrained optimization, and learn how to implement these methods computationally. The course integrates key concepts from vector calculus, such as gradients, divergence, and the Hessian matrix, to provide a deeper understanding of optimization problems. Practical programming assignments will allow students to gain hands-on experience in applying optimization techniques using software tools such as PYTHON / MATLAB.
