Optimization for Decision Making

This course is part of Analytics for Decision Making Specialization

Instructor: Soumya Sen

Skills you'll gain

  •   Process Optimization
  •   Resource Allocation
  •   Linear Algebra
  •   Data Modeling
  •   Solution Design
  •   Business Intelligence
  •   Operations Research
  •   Business Mathematics
  •   Business Modeling
  •   Decision Making
  •   Graphing
  •   Microsoft Excel
  •   Analytics
  •   Data-Driven Decision-Making
  •   Mathematical Modeling
  •   Business Analytics
  • There are 4 modules in this course

    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.

    Module 2: Solving Linear Programs

    Module 3: Alternative Specifications & Special Cases in Linear Optimization

    Module 4: Modeling & Solving Linear Problems in Excel

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