Foundations of Business Decision Modeling

Do you have access to business data but struggle to recommend the absolute best course of action? This course will teach you how to move beyond simple analysis and start building models that identify optimal outcomes. This text-based course is your practical introduction to the world of prescriptive analytics. You will learn to structure complex business challenges as mathematical models, defining clear objectives and constraints. By the end, you'll be equipped to use powerful techniques like linear programming and simulation to make data-driven strategic decisions with confidence. What you'll learn: - Understand the core principles of decision modeling, including objective functions and constraints. - Formulate and solve linear programming problems to optimize resource allocation. - Apply Monte Carlo simulation to model uncertainty and evaluate risk in your decisions. - Build basic optimization models using spreadsheet solvers for practical problem-solving. - Perform sensitivity analysis to test your assumptions and strengthen your recommendations. - Translate real-world business challenges from finance and logistics into structured, solvable models. The course begins with foundational concepts of modeling before guiding you through written exercises in optimization and simulation. You'll progress from simple examples to more complex business scenarios, building your skills systematically. This course is designed for aspiring business analysts, managers, and students. No prior experience in programming or advanced mathematics is required to get started. Enroll now to begin making smarter, data-backed business decisions.