Linear Programming and Derivatives for Applied Mathematics

Mathematical optimization and calculus are at the heart of modern decision-making, data analysis, and engineering. Understanding how to model constraints and determine rates of change is crucial for solving practical problems in business, economics, and science. This course helps you build a strong mathematical foundation, taking you from core definitions to practical application. You will learn to translate complex real-world scenarios into structured mathematical models and solve them systematically through written explanations and guided practice. What you'll learn: Understand core concepts of linear programming, including objective functions, constraints, and feasible regions; Solve optimization problems using graphical methods and systematic algebraic approaches; Apply derivatives to find rates of change, tangent lines, and normal lines; Master the first and second derivative tests to determine local maxima and minima; Analyze real-world business and economic scenarios to optimize profit, cost, and resource allocation. The course starts with essential mathematical terminology and foundational theory before guiding you through step-by-step problem-solving methodologies and practical exercises. This course is designed for beginners, students preparing for foundational mathematics exams, and anyone looking to refresh their optimization skills; no advanced prerequisites are required. Start reading to master the practical power of derivatives and linear programming today.