Discrete optimization courses can help you learn linear programming, integer programming, and combinatorial optimization techniques. You can build skills in problem formulation, algorithm design, and solution analysis. Many courses introduce tools such as MATLAB, Python libraries like PuLP and SciPy, and optimization software like CPLEX, showing how these skills are applied to logistics, resource allocation, and scheduling challenges.