Business Analytics for Decision Making

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Business Analytics for Decision Making

This course is part of Advanced Business Analytics Specialization

Instructor: Manuel Laguna

96,495 already enrolled

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4 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

No prior experience required

9 hours to complete

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

No prior experience required

9 hours to complete

Flexible schedule

Learn at your own pace

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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Assessments

8 assignments

Taught in English

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Build your subject-matter expertise

This course is part of the Advanced Business Analytics Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

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Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 4 modules in this course

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.

What's included

7 videos2 readings2 assignments1 discussion prompt

7 videosTotal 53 minutes

Introduction to the Course3 minutes
0. What is Cluster Analysis8 minutes
1. Data Reduction and Unsupervised Learning8 minutes
2. Preparing Data and Measuring Dissimilarities9 minutes
3. Hierarchical and k-Means Clustering7 minutes
4. Cluster Analysis with Excel8 minutes
5. Cluster Analysis with XLMiner10 minutes

2 readingsTotal 11 minutes

Course Updates and Accessibility Support1 minute
Register for Analytic Solver Platform for Education (ASPE)10 minutes

2 assignmentsTotal 60 minutes

Week 1 Quiz30 minutes
Week 1 Application Assignment - Clustering30 minutes

1 discussion promptTotal 20 minutes

Week 1 Discussion: Cluster Analysis in Nilsen Analytics Tools20 minutes

What's included

7 videos2 assignments1 discussion prompt

7 videosTotal 52 minutes

0. Risk Analysis and Monte Carlo Simulation8 minutes
1. Adding Uncertainty to a Spreadsheet Model9 minutes
2. Defining Output Variables and Analyzing the Results8 minutes
3. Using Historical Data to Model Uncertainty8 minutes
4. Models with Correlated Uncertain Variables6 minutes
5. Creating and Interpreting Charts8 minutes
6. Using Average Values versus Simulation5 minutes

2 assignmentsTotal 60 minutes

Week 2 Quiz30 minutes
Week 2 Application Assignment - Monte Carlo Simulation30 minutes

1 discussion promptTotal 10 minutes

Week 2 Discussion: How Betterment Holdings Inc. Used Monte Carlo Simulation10 minutes

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

7 videosTotal 54 minutes

0. Optimization and Decision Making6 minutes
1. Formulating an Optimization Problem8 minutes
2. Developing a Spreadsheet Model8 minutes
3. Adding Optimization to a Spreadsheet Model6 minutes
4. What-if Analysis and the Sensitivity Report9 minutes
5. Evaluating Scenarios and Visualizing Results to Gain Practical Insights9 minutes
6. Digital Marketing Application of Optimization8 minutes

2 assignmentsTotal 75 minutes

Week 3 Quiz30 minutes
Week 3 Application Assignment - Linear Optimization45 minutes

1 discussion promptTotal 10 minutes

Week 3 Discussion: How Amazon Uses Optimization for Its Supply Chain10 minutes

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

6 videosTotal 39 minutes

0. Advanced Models for Better Decisions4 minutes
1. Business Problems with Yes/No Decisions6 minutes
2. Formulation and Solution of Binary Optimization Problems8 minutes
3. Metaheuristic Optimization8 minutes
4. Chance Constraints and Value At Risk7 minutes
5. Simulation Optimization6 minutes

2 assignmentsTotal 75 minutes

Week 4 Quiz30 minutes
Week 4 Application Assignment - Simulation Optimization45 minutes

1 discussion promptTotal 10 minutes

Week 4 Discussion: How Uber Optimized Its Dispatch System10 minutes

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Instructor

Manuel Laguna

University of Colorado Boulder

4 Courses152,325 learners

Offered by

University of Colorado Boulder

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