This course is part of the Analytics for Decision Making Specialization

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40 ratings

Soumya Sen

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Offered By

Analytics for Decision Making SpecializationUniversity of Minnesota

About this Course

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Business analysts need to be able to prescribe optimal solution to problems. But analytics courses are often focused on training students in data analysis and visualization, not so much in helping them figure out how to take the available data and pair that with the right mathematical model to formulate a solution. This course is designed to connect data and models to real world decision-making scenarios in manufacturing, supply chain, finance, human resource management, etc. In particular, we understand how linear optimization - a prescriptive analytics method - can be used to formulate decision problems and provide data-based optimal solutions. Throughout this course we will work on applied problems in different industries, such as:
(a) Finance Decisions: How should an investment manager create an optimal portfolio that maximizes net returns while not taking too much risks across various investments?

(b) Production Decisions: Given projected demand, supply of raw materials, and transportation costs, what would be the optimal volume of products to manufacture at different plant locations?

(c) HR Decisions: How many workers need to be hired or terminated over a planning horizon to minimize cost while meeting operational needs of a company?

(c) Manufacturing: What would be the profit maximizing product mix that should be produced, given the raw material availability and customer demand?

We will learn how to formulate these problems as mathematical models and solve them using Excel spreadsheet.

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Shareable Certificate

Earn a Certificate upon completion

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Coursera Labs

Includes hands on learning projects.

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Course 3 of 4 in the

Analytics for Decision Making Specialization

Beginner Level

Familiarity with Excel spreadsheets

Approx. 13 hours to complete

English

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Skills you will gain

Analytics
Operations Management
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 3 of 4 in the

Analytics for Decision Making Specialization

Beginner Level

Familiarity with Excel spreadsheets

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 (8 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: LPs for Financial Decisions

4 hours to complete

14 videos (Total 111 min), 1 reading, 2 quizzes

14 videos

"Analytics for Decision Making" Specialization Overview8mMeet Your Instructor: Soumya Sen8m"Advanced Optimization for Decision Making" Course Overview9mModule 1 Overview: LPs for Financial Decisions1mAn Investment Decision Problem5mFormulating an Investment Optimization Problem9mEntering the Investment Optimization Problem in Excel12mFinding the Optimal Investment Strategy7mUnderstanding the Impact of Parameter Changes11mA Multi-Period Cash Flow Decision Problem5mFormulating a Cash Flow Optimization Problem Part 15mFormulating a Cash Flow Optimization Problem Part 28mEntering the Cash Flow Optimization Problem in Excel10mFinding the Optimal Cash Flow5m

1 reading

Applications of Linear Optimization10m

2 practice exercises

Module 1 Practice Exercise: Banking Investments Decision1hModule 1 Graded Exercise: Banking Loan Decision1h

Week2

Week 2

3 hours to complete

Module 2: LP for Supply Chain Decisions

3 hours to complete

10 videos (Total 53 min)

10 videos

Module 2 Overview: LP for Supply Chain Decisions2mA Transportation Decision Problem3mFormulating a Transportation Problem Part 17mFormulating a Transportation Problem Part 25mEntering the Transportation Problem in Excel5mSolving the Transportation Problem3mModel for Production and Inventory Decision Problem5mFormulating an Inventory Planning Problem Part 18mFormulating an Inventory Planning Part 24mEntering the Inventory Planning in Excel 5m

2 practice exercises

Module 2 Practice Exercise: Army Transportation Decision1hModule 2 Graded Exercise: A Car Manufacturing Decision1h

Week3

Week 3

3 hours to complete

Module 3: LP for Staffing Decisions

3 hours to complete

11 videos (Total 67 min), 1 reading, 2 quizzes

11 videos

Module 3 Overview: LP for Staffing Decisions2mThe Model Setup for Staffing Decision Problem1mFormulating a Staffing Decision Problem Part 15mFormulating a Staffing Decision Problem Part 27mEntering the Problem in Excel5mSolving the Staffing Decision Problem in Excel7mSolving the Inventory Planning Problem9mThe Model Setup for Office Assignment Decisions3mFormulating the Office Assignment Decision Problem10mEntering the Office Assignment Problem in Excel6mSolving the Office Assignment Decision Problem6m

1 reading

Why Prescriptive Analytics and Decision optimization are Crucial (IBM)10m

2 practice exercises

Module 3 Practice Exercise: An Amusement Park Staffing Decision1hModule 3 Graded Exercise: An Airline Pilot Staffing Decision1h

Week4

Week 4

4 hours to complete

Module 4: LP for Production Decisions

4 hours to complete

11 videos (Total 56 min), 3 readings, 2 quizzes

11 videos

Module 4 Overview: LP for Production Decisions1mThe Model Setup for a Product Mix Problem4mFormulating a Product Mix Optimization Problem11mSetting up the Product Mix problem in Excel6mSolving the Product Mix Optimization Problem6mThe Model Setup for a Blending Optimization Problem4mFormulating a Blending Optimization Problem7mSetting Up the Blending Decision Problem in Excel4mSolving the Blending Optimization Problem4mCongratulations on Finishing the "Advanced Models for Decision Making" Course2mCarlson School of Management: Master of Science Program in Business Analytics (MSBA)2m

3 readings

Analytics Trends 2021 and Beyond10mCarlson School of Management: MSBA Program Website10mManagement Information Systems (MIS) Research Center10m

2 practice exercises

Module 4 Practice Exercise: A Pharmaceutical Company's Decision1hModule 4 Graded Exercise: Electronics Product Mix Decisions1h

Reviews

4.8

7 reviews

5 stars
82.50%
4 stars
17.50%

TOP REVIEWS FROM ADVANCED MODELS FOR DECISION MAKING

by JHJun 2, 2021

All of the courses in this series are very practical based and give a lot of practice in using the tools.

by NRSep 18, 2021

The concepts are explained well. The lectures are very detail oriented. I just wish there were more examples to follow.

by CLMay 18, 2021

Really enjoyed the lesson. Learned application of optimization analytics in various setting.

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

When will I have access to the lectures and assignments?
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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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