In this course you will learn how to create models for decision making. We will start with cluster analysis, a technique for data reduction that is very useful in market segmentation. You will then learn the basics of Monte Carlo simulation that will help you model the uncertainty that is prevalent in many business decisions. A key element of decision making is to identify the best course of action. Since businesses problems often have too many alternative solutions, you will learn how optimization can help you identify the best option. What is really exciting about this course is that you won’t need to know a computer language or advanced statistics to learn about these predictive and prescriptive analytic models. The Analytic Solver Platform and basic knowledge of Excel is all you’ll need. Learners participating in assignments will be able to get free access to the Analytic Solver Platform.
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Business Analytics for Decision Making
This course is part of Advanced Business Analytics Specialization
Instructor: Manuel Laguna
86,856 already enrolled
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(1,805 reviews)
What you'll learn
Describe the significance of optimization in identifying optimal solutions for complex business problems
Implement optimization techniques to identify the best possible course of action among multiple alternatives
Judge the appropriateness of optimization techniques in finding optimal solutions for practical business challenges
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There are 4 modules in this course
What's included
7 videos1 reading2 assignments1 discussion prompt
What's included
7 videos2 assignments1 discussion prompt
At the end of this module students should be able to: 1. Develop a spreadsheet model for an optimization problem 2. Use Excel to solve optimization models 3. Interpret solutions and conduct what-if analysis
What's included
7 videos2 assignments1 discussion prompt
At the end of this module students should be able to: 1. Given a business situation, apply an appropriate technique to identify the best solution alternatives 2. Formulate and solve models for business problems that requires yes/no decisions and logical constraints 3. Create models that mix techniques and tools such as simulation and optimizationAnalyze and interpret results to make informed decisions
What's included
6 videos2 assignments1 discussion prompt
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