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.
이 강좌에 대하여
Familiarity with Excel
귀하가 습득할 기술
- 5 stars79.16%
- 4 stars16.66%
- 1 star4.16%
OPTIMIZATION FOR DECISION MAKING의 최상위 리뷰
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!
Very insightful course. Love the detail explaination for solving simple LP problems.
Analytics for Decision Making 특화 과정 정보
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