This course is part of the Analytics for Decision Making Specialization

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stars
33 ratings

Soumya Sen

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Offered By

Analytics for Decision Making SpecializationUniversity of Minnesota

About this Course

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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.

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Coursera Labs

Includes hands on learning projects.

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Course 2 of 4 in the

Analytics for Decision Making Specialization

Beginner Level

Familiarity with Excel

Approx. 13 hours to complete

English

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Skills you will gain

Analytics
Linear Programming (LP)
Mathematical Optimization

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Course 2 of 4 in the

Analytics for Decision Making Specialization

Beginner Level

Familiarity with Excel

Approx. 13 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructor

Instructor rating

5/5 (11 Ratings)

Soumya Sen

Associate Professor

Carlson School of Management, Information and Decision Sciences

24,295 Learners

3 Courses

Offered by

University of Minnesota

The University of Minnesota is among the largest public research universities in the country, offering undergraduate, graduate, and professional students a multitude of opportunities for study and research. Located at the heart of one of the nation’s most vibrant, diverse metropolitan communities, students on the campuses in Minneapolis and St. Paul benefit from extensive partnerships with world-renowned health centers, international corporations, government agencies, and arts, nonprofit, and public service organizations.

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Syllabus - What you will learn from this course

Week1

Week 1

4 hours to complete

Module 1: Introduction to Linear Programming

4 hours to complete

11 videos (Total 91 min), 1 reading, 2 quizzes

11 videos

"Analytics for Decision Making" Specialization Overview8m"Optimization for Decision Making" Course Overview11mMeet Your Instructor: Soumya Sen8mModule 1 Overview: An Introduction to Linear Programming1mModeling Approaches to Decision Making9mApplications of Optimization – Part 110mApplications of Optimization – Part 27mHow to Setup a Linear Optimization Problem12mOak Barrel Brewery: An Example Linear Program Problem10mLuxury Sofas Problem: A Practice Exercise3mSolution to the Luxury Sofas Practice Problem6m

1 reading

Read this article on Optimization in Prescriptive Analytics10m

2 practice exercises

Module 1 Practice Exercise1hModule 1 Graded Exercise1h

Week2

Week 2

3 hours to complete

Module 2: Solving Linear Programs

3 hours to complete

8 videos (Total 61 min)

8 videos

Module 2 Overview2mSolving Linear Optimization Problems - Part 1a10mSolving Linear Optimization Problems - Part 1b7mSolving Linear Optimization Problems - Part 29mSolving Linear Optimization Problems - Part 34mExample Problem: How Many Items of Two Products Should a Manufacturer Produce? (Part 1)7mExample Problem: How to Plot the Feasible Region of the Problem (Part 2)8mExample Problem: Finding the Optimal Solution for the Problem (Part 3)10m

2 practice exercises

Module 2 Practice Exercise: A Retail Butcher Shop1hModule 2 Graded Exercise: Giapetto's Woodcarving Company1h

Week3

Week 3

3 hours to complete

Module 3: Alternative Specifications & Special Cases in Linear Optimization

3 hours to complete

7 videos (Total 49 min)

7 videos

Module 3 Overview: Alternative Specifications and Shadow Prices46sImpact of Changes to Model Parameters - Part 111mImpact of Changes to Model Parameters - Part 210mWhat to Do When There are Multiple Optimal Solutions8mRedundant Constraints5mUnbounded Solutions7mInfeasible Solution4m

2 practice exercises

Module 3 Practice Exercise: An Automobile Manufacturer1hModule 3 Graded Exercise: Dorian Auto Manufacturer1h

Week4

Week 4

4 hours to complete

Module 4: Modeling & Solving Linear Problems in Excel

4 hours to complete

13 videos (Total 75 min), 2 readings, 2 quizzes

13 videos

Module 4 Overview: Modeling & Solving Linear Problems in Excel1mIntroduction to Spreadsheet Solvers4mSteps in Implementing an LP Model in Excel6mOrganizing LP model data in Excel8mOptimal Solution with Excel Solver - Example 18mOptimal Solution with Excel Solver - Example 27mOptimal Solution with Excel Solver - Example 2 Solution4mCase Exercise: "Make vs. Buy" Decision (A Computer Gaming Company)4mMake vs. Buy Decision: LP Formulation9mMake vs. Buy Decision: Excel Solution Part 1 (Set Up the Problem)11mMake vs. Buy Decision: Excel Solution Part 2 (Using Excel Solver)4mCongratulations on Finishing the "Optimization for Decision Making" Course2mCarlson School of Management: Master of Science Program in Business Analytics (MSBA)2m

2 readings

Carlson School of Management: MSBA Program Website10mManagement Information Systems (MIS) Research Center10m

2 practice exercises

Module 4 Practice Exercise: Calmetal, a Manufacturing Firm Example1hModule 4 Graded Exercise: A Medical Device Example1h

Reviews

4.8

7 reviews

5 stars
84.84%
4 stars
12.12%
1 star
3.03%

TOP REVIEWS FROM OPTIMIZATION FOR DECISION MAKING

by NRSep 17, 2021

Very insightful course. Love the detail explaination for solving simple LP problems.

by JHMay 31, 2021

There are a lot of examples to work through and learn from which I find helps make the material easier to learn.

by CWApr 16, 2021

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!

by CLMay 15, 2021

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.

View all reviews

About the Analytics for Decision Making Specialization

The field of analytics is typically built on four pillars: Descriptive Analytics, Predictive Analytics, Causal Analytics, and Prescriptive Analytics. Descriptive analytics (e.g., visualization, BI) deal with the exploration of data for patterns, predictive analytics (e.g., data mining, time-series forecasting) identifies what can happen next, causal modeling establishes causation, and prescriptive analytics help with formulating decisions. This specialization focuses on the Prescriptive Analytics (the final pillar). This specialization will review basic predictive modeling techniques that can be used to estimate values of relevant parameters, and then use optimization and simulation techniques to formulate decisions based on these parameter values and situational constraints. The specialization will teach how to model and solve decision-making problems using predictive models, linear optimization, and simulation methods.

Frequently Asked Questions

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The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

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Optimization for Decision Making

About this Course

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