Introduction to Mathematical Programming and Optimization

Mathematical programming provides the analytical framework needed to solve complex decision-making, resource allocation, and optimization challenges. This structured text-based course introduces foundational concepts in mathematical modeling and practical optimization techniques. What you'll learn: Understand core terminology including decision variables, objective functions, and constraints; Formulate real-world optimization problems into precise mathematical models; Master linear programming principles and duality theory; Explore integer programming fundamentals for discrete decision models; Apply modern computational tools using Python optimization libraries like SciPy and PuLP. The course starts with essential mathematical concepts and definitions before progressing through clear written explanations and code-based problem formulations. Designed for beginners in data science, computer science, and business analytics, this guide requires no prior background in mathematical programming. Start reading today to build your skills in mathematical optimization.