Foundations of Prescriptive Analytics and Decision Optimization

In today's data-driven landscape, knowing what might happen is no longer enough; the real competitive advantage lies in knowing exactly what action to take. Prescriptive analytics represents the pinnacle of business intelligence, allowing organizations to find optimal solutions to complex resource, scheduling, and logistics challenges. This text-only course provides a clear, structured path to mastering the fundamentals of decision science and mathematical modeling. Through clear written explanations and practical scenarios, you will transition from understanding basic data concepts to formulating sophisticated optimization models. You will learn how to identify decision variables, construct objective functions, and map real-world constraints into mathematical equations that drive efficient outcomes. What you'll learn: - Understand the core terminology, definitions, and frameworks of prescriptive analytics. - Formulate linear programming models to solve resource allocation and production problems. - Define decision variables, objective functions, and constraints for diverse business scenarios. - Analyze sensitivity reports to evaluate how changes in constraints impact the optimal solution. - Explore modern approaches to optimization under uncertainty and risk management. - Practice structuring narrative business problems into clean, solvable mathematical models. Your learning journey begins with essential definitions and foundational concepts before moving step-by-step into formulation techniques. You will work through realistic business cases, learning how to analyze and interpret model outputs to make confident, data-backed recommendations. This course is designed for beginners, business professionals, and aspiring analysts who want to improve their strategic decision-making. No advanced mathematical background or programming experience is required. Equip yourself with the skills to solve complex business problems and drive optimal results.