Linear Programming and Application of Derivatives for Applied Mathematics

Unlock the power of mathematical optimization and calculus to solve practical, real-world problems. This course demystifies linear programming and the application of derivatives, translating complex formulas into clear, logical steps. You will learn how to analyze rates of change, find optimal values, and model business constraints mathematically to make data-driven decisions. Through structured written lessons, you will transition from basic algebraic concepts to formulating and solving optimization models. You will read through step-by-step mathematical proofs, explore practical business scenarios, and study how these mathematical principles form the foundation of modern data science algorithms. What you'll learn: - Understand the core terminology of optimization, objective functions, and constraints - Formulate and solve linear programming problems using the graphical method - Apply derivatives to find rates of change, increasing and decreasing functions, and tangent lines - Determine local and absolute maxima and minima to solve real-world optimization problems - Translate word problems in business and economics into solvable mathematical equations - Practice formulating models with multiple constraints to find optimal cost and revenue points This course begins with foundational definitions of variables, constraints, and rates of change before moving into step-by-step problem-solving methodologies. You will study complete mathematical breakdowns and walk through structured exercises that reinforce your theoretical understanding. This course is designed for beginners, students, and aspiring data analysts who want a solid grounding in applied mathematics. No advanced calculus background is required to begin. Start reading today to build a strong mathematical foundation for analytical decision-making.