Convex Optimization is a subfield of Optimization that focuses on minimizing convex functions over convex sets. Its problems are inherently well-behaved, guaranteeing that any local optimum is also a global optimum, making them tractable and efficient to solve. This powerful framework underpins many modern applications, from Machine Learning to engineering design.