In this data-driven world, companies are often interested in knowing what is the "best" course of action, given the data. For example, manufacturers need to decide how many units of a product to produce given the estimated demand and raw material availability? Should they make all the products in-house or buy some from a third-party to meet the demand? Prescriptive Analytics is the branch of analytics that can provide answers to these questions. It is used for prescribing data-based decisions. The most important method in the prescriptive analytics toolbox is optimization. This course will introduce students to the basic principles of linear optimization for decision-making. Using practical examples, this course teaches how to convert a problem scenario into a mathematical model that can be solved to get the best business outcome. We will learn to identify decision variables, objective function, and constraints of a problem, and use them to formulate and solve an optimization problem using Excel solver and spreadsheet.
Familiarity with Excel
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- 4 stars17.39%
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OPTIMIZATION FOR DECISION MAKING からの人気レビュー
Very insightful course. Love the detail explaination for solving simple LP problems.
Good teaching style with step by step guidance. Thanks for the connecting high school math (that I learned many years ago) to real life context. I look forward to the next course.
There are a lot of examples to work through and learn from which I find helps make the material easier to learn.
It was an interesting refreshed for the most part and went very quickly. Could have used just a little more info on using Excel Solver. Thanks for the class!
Analytics for Decision Making専門講座について