This course explores Prescriptive Analytics, focusing on optimization methods to make data-driven decisions. Through practical examples, learners understand how to apply linear optimization principles to real-world scenarios. They learn to convert problem scenarios into mathematical models, identifying decision variables, objective functions, and constraints. Utilizing tools like Excel Solver and spreadsheets, participants formulate and solve optimization problems to achieve optimal business outcomes.

In a data-driven environment, companies seek the "best" course of action based on available data. For instance, manufacturers may need to determine production quantities based on demand estimates and raw material availability. Prescriptive Analytics offers solutions to such questions, enabling data-based decision-making. Optimization, a key method in Prescriptive Analytics, helps in prescribing optimal decisions.

By the course's conclusion, learners will have gained essential skills in applying linear optimization techniques to solve decision-making problems effectively. They will be equipped to analyze problem scenarios, construct mathematical models, and leverage optimization methods to derive optimal solutions, enhancing their ability to make informed decisions in various business contexts