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Soumya Sen
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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OpenCourser.com/course/cs2oje/optimization
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What's inside
Syllabus
Module 1: Introduction to Linear Programming
Prescriptive analytics is a part of business analytics that is aimed at prescribing solutions to decision problems. The most important modeling technique within prescriptive analytics is optimization. In this module, we will learn how to recognize contexts where it can be applied and get introduced to the basics of linear optimization.
Read more
Syllabus
Module 1: Introduction to Linear Programming
Prescriptive analytics is a part of business analytics that is aimed at prescribing solutions to decision problems. The most important modeling technique within prescriptive analytics is optimization. In this module, we will learn how to recognize contexts where it can be applied and get introduced to the basics of linear optimization.
Read more
Module 2: Solving Linear Programs
In order to solve linear optimization problems (i.e., linear programs), we can use graphical methods for basic example problems. For higher dimensional problems, we will use tools like Excel Solver later in the course. The benefit of using graphical methods is that it gives us an intuition into how these problems can be solved.
Module 3: Alternative Specifications & Special Cases in Linear Optimization
In this module we will explore what happens when the model parameters are changed. We will also look at special cases of linear optimization problems.
Module 4: Modeling & Solving Linear Problems in Excel
Having learned how to formulate linear optimization problem and the graphical methods for solving them, we are now going to start solving larger problems using Excel Solver. This module provides an overview of how to set up and solve these decision problems using Excel.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Designed for learners who are looking to enter the field of business analytics, as it will teach skills that are core to entry-level positions
Assumes that learners have little to no knowledge in data analytics or the concepts of prescribed analytics, making the course a suitable starting point
Led by Soumya Sen, a subject-matter expert with years of experience in applied analytics
Emphasizes the practical application of linear optimization models, providing learners with immediately usable skills
Mainly focuses on the concept of linear optimization, limiting its scope in terms of prescriptive analytics techniques
Relies on Excel Solver for problem-solving, which may not be the most effective tool for complex optimization problems
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Reviews summary
Helpful course on optimization
Learners say this course titled Optimization for Decision Making is an excellent, insightful, and helpful course based on its well-structured lectures, engaging assignments, and clear explanations. With its detailed content and real-life case studies, this course is suitable for beginners and experienced students interested in learning optimization techniques.
Course serves as a good refresher for those with prior knowledge.
"It was an interesting refreshed for the most part and went very quickly."
Suitable for learners with beginner level of knowledge.
"As for the course itself I find it helpfull and interesting"
Instructor provides clear and concise explanations.
"Lectures were very clear and concise! "
"The professor was easy to follow."
"I love the calmness and the fact the course was detailed and concise as possible."
Course includes helpful examples and case studies.
"There are a lot of examples to work through and learn from which I find helps make the material easier to learn."
"The lecturer’s clear explanations and engaging case studies provided both a refresher and a deep dive into solving optimization problems."
Course connects concepts to real-world applications.
"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."
"Optimization for Decision Making is good course.It 's not too complex for me.I can make easy and immidiately decision from use graphical.Moreover, I can decision which have to buy or making something .It's very useful for all business to control your cost."
Course lacks downloadable materials such as PDFs and Excel files.
"it will be better if we can download the pdf for the course materials so the learner will be easier to review the course without going back to the video (especially when doing the practice or the graded exam)."
"since i think the learner target is for the beginner level, it also better if we also able to download all of the excel files that used in this course (at least the default template)"
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Optimization for Decision Making with these
activities:
Identify Mentors in the Field of Optimization
Show steps
Connecting with experienced professionals will provide you with valuable insights and guidance throughout your learning journey.
Browse courses on
Optimization
Show steps
-
Attend industry events or conferences related to optimization.
-
Reach out to professors or researchers in the field.
-
Connect with professionals on LinkedIn or other networking platforms.
Review Basic Algebra and Calculus Concepts
Show steps
Refreshing your understanding of these concepts will provide a stronger foundation for comprehending linear optimization.
Browse courses on
Algebra
Show steps
-
Review notes or online resources on basic algebra topics such as linear equations and inequalities.
-
Practice solving simple algebra problems.
-
Review basic calculus concepts such as derivatives and integrals.
Compile a Glossary of Linear Optimization Terms
Show steps
Creating a glossary will provide you with a quick reference for understanding and using linear optimization terminology.
Browse courses on
Optimization
Show steps
-
Gather a list of key terms related to linear optimization.
-
Define each term clearly and concisely.
-
Organize the glossary alphabetically or by category.
-
Review the glossary regularly to reinforce your understanding.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Follow Tutorials on Linear Optimization Applications
Show steps
Exploring how linear optimization is used in practical applications will broaden your understanding of its real-world relevance.
Browse courses on
Optimization
Show steps
-
Search for online tutorials or courses on linear optimization applications.
-
Choose a specific domain or industry, such as manufacturing, finance, or logistics.
-
Follow the tutorials to learn how linear optimization is used to solve problems in that domain.
-
Take notes and document the key concepts and techniques used.
Join a Study Group or Online Forum for Linear Optimization
Show steps
Engaging with peers will provide opportunities for discussion, idea sharing, and collaborative problem-solving.
Browse courses on
Optimization
Show steps
-
Find or create a study group with classmates or online peers.
-
Meet regularly to discuss concepts, work on problems, and share insights.
-
Participate in online forums or discussion boards dedicated to linear optimization.
Practice Excel Solver
Show steps
Applying what you've learned to solve optimization problems will reinforce your understanding of the concepts.
Browse courses on
Excel Solver
Show steps
-
Download the Excel Solver add-in if you haven't already.
-
Load an example optimization problem into Excel.
-
Set up the decision variables, objective function, and constraints in Excel Solver.
-
Use Excel Solver to solve the problem and find the optimal solution.
-
Repeat these steps for various optimization problems to gain proficiency.
Develop a Linear Optimization Model for a Business Problem
Show steps
Applying linear optimization to a real-world problem will deepen your understanding and demonstrate your ability to use it effectively.
Browse courses on
Optimization
Show steps
-
Identify a business problem that can be addressed using linear optimization.
-
Gather data and define the decision variables, objective function, and constraints.
-
Formulate the optimization problem using a linear programming solver, such as Excel Solver or Gurobi.
-
Solve the problem to obtain the optimal solution.
-
Analyze the results and write a report summarizing your findings and recommendations.
Identify Mentors in the Field of Optimization
Show steps
Connecting with experienced professionals will provide you with valuable insights and guidance throughout your learning journey.
Browse courses on
Optimization
Show steps
Show steps
Show steps
- Attend industry events or conferences related to optimization.
- Reach out to professors or researchers in the field.
- Connect with professionals on LinkedIn or other networking platforms.
Review Basic Algebra and Calculus Concepts
Show steps
Refreshing your understanding of these concepts will provide a stronger foundation for comprehending linear optimization.
Browse courses on
Algebra
Show steps
Show steps
Show steps
- Review notes or online resources on basic algebra topics such as linear equations and inequalities.
- Practice solving simple algebra problems.
- Review basic calculus concepts such as derivatives and integrals.
Compile a Glossary of Linear Optimization Terms
Show steps
Creating a glossary will provide you with a quick reference for understanding and using linear optimization terminology.
Browse courses on
Optimization
Show steps
Show steps
Show steps
- Gather a list of key terms related to linear optimization.
- Define each term clearly and concisely.
- Organize the glossary alphabetically or by category.
- Review the glossary regularly to reinforce your understanding.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Follow Tutorials on Linear Optimization Applications
Show steps
Exploring how linear optimization is used in practical applications will broaden your understanding of its real-world relevance.
Browse courses on
Optimization
Show steps
Show steps
Show steps
- Search for online tutorials or courses on linear optimization applications.
- Choose a specific domain or industry, such as manufacturing, finance, or logistics.
- Follow the tutorials to learn how linear optimization is used to solve problems in that domain.
- Take notes and document the key concepts and techniques used.
Join a Study Group or Online Forum for Linear Optimization
Show steps
Engaging with peers will provide opportunities for discussion, idea sharing, and collaborative problem-solving.
Browse courses on
Optimization
Show steps
Show steps
Show steps
- Find or create a study group with classmates or online peers.
- Meet regularly to discuss concepts, work on problems, and share insights.
- Participate in online forums or discussion boards dedicated to linear optimization.
Practice Excel Solver
Show steps
Applying what you've learned to solve optimization problems will reinforce your understanding of the concepts.
Browse courses on
Excel Solver
Show steps
Show steps
Show steps
- Download the Excel Solver add-in if you haven't already.
- Load an example optimization problem into Excel.
- Set up the decision variables, objective function, and constraints in Excel Solver.
- Use Excel Solver to solve the problem and find the optimal solution.
- Repeat these steps for various optimization problems to gain proficiency.
Develop a Linear Optimization Model for a Business Problem
Show steps
Applying linear optimization to a real-world problem will deepen your understanding and demonstrate your ability to use it effectively.
Browse courses on
Optimization
Show steps
Show steps
Show steps
- Identify a business problem that can be addressed using linear optimization.
- Gather data and define the decision variables, objective function, and constraints.
- Formulate the optimization problem using a linear programming solver, such as Excel Solver or Gurobi.
- Solve the problem to obtain the optimal solution.
- Analyze the results and write a report summarizing your findings and recommendations.
Career center
Learners who complete Optimization for Decision Making will develop knowledge and skills
that may be useful to these careers:
Operations Research Analyst
Operations Research Analyst
An Operations Research Analyst applies analytical methods to help organizations make better decisions. This course, Optimization for Decision Making, can be a valuable tool for Operations Research Analysts, as it provides a strong foundation in the principles of linear optimization. This course can help Operations Research Analysts develop the skills they need to identify decision variables, objective functions, and constraints, and use them to formulate and solve optimization problems. This can be essential for making better decisions in a variety of settings, such as manufacturing, logistics, and healthcare.
Data Scientist
Data Scientist
A Data Scientist uses data to solve problems and improve decision-making. This course, Optimization for Decision Making, can be a valuable tool for Data Scientists, as it provides a strong foundation in the principles of linear optimization. This course can help Data Scientists develop the skills they need to identify decision variables, objective functions, and constraints, and use them to formulate and solve optimization problems. This can be essential for making better decisions in a variety of settings, such as marketing, finance, and healthcare.
Business Analyst
Business Analyst
A Business Analyst uses data and analysis to help businesses make better decisions. This course, Optimization for Decision Making, can be a valuable tool for Business Analysts, as it provides a strong foundation in the principles of linear optimization. This course can help Business Analysts develop the skills they need to identify decision variables, objective functions, and constraints, and use them to formulate and solve optimization problems. This can be essential for making better decisions in a variety of settings, such as product development, marketing, and finance.
Management Consultant
Management Consultant
A Management Consultant helps organizations improve their performance. This course, Optimization for Decision Making, can be a valuable tool for Management Consultants, as it provides a strong foundation in the principles of linear optimization. This course can help Management Consultants develop the skills they need to identify decision variables, objective functions, and constraints, and use them to formulate and solve optimization problems. This can be essential for making better decisions in a variety of settings, such as operations, finance, and marketing.
Financial Analyst
Financial Analyst
A Financial Analyst uses data to evaluate investments and make recommendations. This course, Optimization for Decision Making, can be a valuable tool for Financial Analysts, as it provides a strong foundation in the principles of linear optimization. This course can help Financial Analysts develop the skills they need to identify decision variables, objective functions, and constraints, and use them to formulate and solve optimization problems. This can be essential for making better decisions in a variety of settings, such as portfolio management, investment banking, and corporate finance.
Operations Manager
Operations Manager
An Operations Manager plans and oversees the day-to-day operations of an organization. This course, Optimization for Decision Making, can be a valuable tool for Operations Managers, as it provides a strong foundation in the principles of linear optimization. This course can help Operations Managers develop the skills they need to identify decision variables, objective functions, and constraints, and use them to formulate and solve optimization problems. This can be essential for making better decisions in a variety of settings, such as manufacturing, logistics, and healthcare.
Industrial Engineer
Industrial Engineer
An Industrial Engineer designs and improves systems and processes. This course, Optimization for Decision Making, can be a valuable tool for Industrial Engineers, as it provides a strong foundation in the principles of linear optimization. This course can help Industrial Engineers develop the skills they need to identify decision variables, objective functions, and constraints, and use them to formulate and solve optimization problems. This can be essential for making better decisions in a variety of settings, such as manufacturing, logistics, and healthcare.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software applications. This course, Optimization for Decision Making, may be helpful for Software Engineers, as it provides a foundation in the principles of linear optimization. This course can help Software Engineers develop the skills they need to identify decision variables, objective functions, and constraints, and use them to formulate and solve optimization problems. This can be essential for making better decisions in a variety of settings, such as software design, development, and maintenance.
Actuary
Actuary
An Actuary uses mathematical and statistical methods to assess risk and uncertainty. This course, Optimization for Decision Making, may be helpful for Actuaries, as it provides a foundation in the principles of linear optimization. This course can help Actuaries develop the skills they need to identify decision variables, objective functions, and constraints, and use them to formulate and solve optimization problems. This can be essential for making better decisions in a variety of settings, such as insurance, pensions, and investments.
Financial Manager
Financial Manager
A Financial Manager plans and manages the financial resources of an organization. This course, Optimization for Decision Making, may be helpful for Financial Managers, as it provides a foundation in the principles of linear optimization. This course can help Financial Managers develop the skills they need to identify decision variables, objective functions, and constraints, and use them to formulate and solve optimization problems. This can be essential for making better decisions in a variety of settings, such as financial planning, budgeting, and investment.
Marketing Manager
Marketing Manager
A Marketing Manager plans and executes marketing campaigns. This course, Optimization for Decision Making, may be helpful for Marketing Managers, as it provides a foundation in the principles of linear optimization. This course can help Marketing Managers develop the skills they need to identify decision variables, objective functions, and constraints, and use them to formulate and solve optimization problems. This can be essential for making better decisions in a variety of settings, such as marketing planning, execution, and measurement.
Product Manager
Product Manager
A Product Manager plans and manages the development and launch of new products. This course, Optimization for Decision Making, may be helpful for Product Managers, as it provides a foundation in the principles of linear optimization. This course can help Product Managers develop the skills they need to identify decision variables, objective functions, and constraints, and use them to formulate and solve optimization problems. This can be essential for making better decisions in a variety of settings, such as product planning, development, and launch.
Economist
Economist
An Economist studies the production, distribution, and consumption of goods and services. This course, Optimization for Decision Making, may be helpful for Economists, as it provides a foundation in the principles of linear optimization. This course can help Economists develop the skills they need to identify decision variables, objective functions, and constraints, and use them to formulate and solve optimization problems. This can be essential for making better decisions in a variety of settings, such as economic policy, forecasting, and analysis.
Market Researcher
Market Researcher
A Market Researcher studies the market for a product or service. This course, Optimization for Decision Making, may be helpful for Market Researchers, as it provides a foundation in the principles of linear optimization. This course can help Market Researchers develop the skills they need to identify decision variables, objective functions, and constraints, and use them to formulate and solve optimization problems. This can be essential for making better decisions in a variety of settings, such as market research, analysis, and forecasting.
Statistician
Statistician
A Statistician collects, analyzes, and interprets data. This course, Optimization for Decision Making, may be helpful for Statisticians, as it provides a foundation in the principles of linear optimization. This course can help Statisticians develop the skills they need to identify decision variables, objective functions, and constraints, and use them to formulate and solve optimization problems. This can be essential for making better decisions in a variety of settings, such as data analysis, forecasting, and modeling.
For more career information including salaries, visit:
OpenCourser.com/course/cs2oje/optimization
Reading list
We've selected eight books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Optimization for Decision Making.
Provides a comprehensive overview of linear programming and network flows. It classic textbook that is widely used in academic institutions and by industry professionals.
Provides a practical introduction to optimization for decision making. It covers a wide range of topics, including linear programming, integer programming, and nonlinear programming.
Provides a comprehensive overview of convex optimization. It covers a wide range of topics, including linear programming, semidefinite programming, and conic programming.
Provides a comprehensive overview of nonlinear programming. It covers a wide range of topics, including unconstrained optimization, constrained optimization, and dynamic programming.
Provides a comprehensive overview of network optimization. It covers a wide range of topics, including network flows, minimum cost flows, and maximum flows.
Provides a comprehensive overview of stochastic optimization. It covers a wide range of topics, including Monte Carlo simulation, dynamic programming, and robust optimization.
Provides a comprehensive overview of multi-objective optimization. It covers a wide range of topics, including evolutionary algorithms, genetic algorithms, and particle swarm optimization.
Provides a comprehensive overview of optimization theory and methods. It covers a wide range of topics, including unconstrained optimization, constrained optimization, and dynamic programming.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/cs2oje/optimization
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Effort
4 weeks of study, 3-5 hours/week
Level
Introductory
Via
Coursera
Institution
University of Minnesota
Instructor
Soumya Sen
Language
English
Transcripts
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This course belongs to a
collection
called
Analytics for Decision Making. It's comprised of four courses:
- Optimization for Decision Making (viewing)
- Introduction to Predictive Modeling
- Simulation Models for Decision Making
- Advanced Models for Decision Making
Good to know
Designed for learners who are looking to enter the field of business analytics, as it will teach skills that are core to entry-level positions
Assumes that learners have little to no knowledge in data analytics or the concepts of prescribed analytics, making the course a suitable starting point
Led by Soumya Sen, a subject-matter expert with years of experience in applied analytics
Emphasizes the practical application of linear optimization models, providing learners with immediately usable skills
Mainly focuses on the concept of linear optimization, limiting its scope in terms of prescriptive analytics techniques
Relies on Excel Solver for problem-solving, which may not be the most effective tool for complex optimization problems
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