Simulation Models for Decision Making from Coursera

This course is primarily aimed at third- and fourth-year undergraduate students or graduate students interested in learning simulation techniques to solve business problems.

The course will introduce you to take everyday and complex business problems that have no one correct answer due to uncertainties that exist in business environments. Simulation modeling allows us to explore various outcomes and protect personal or business interests against unwanted outcomes. We can model uncertainties by using the concepts of probability and stepwise thinking. Stepwise thinking allows us to break down the problem in smaller components, explore dependencies between related events and allows us to focus on aspects of problem that are prone to changes due to future uncertainties.

The course will introduce you to advanced Excel techniques to model and execute simulation models. Many of the Excel techniques learned in the course will be useful beyond simulation modeling. We will learn both Monte Carlo simulation techniques where overall outcome is of primary interest and discrete event simulation where intermediate dependencies between related events might be of interest. The course will introduce you to several practical issues in simulation modeling that are normally not covered in textbooks. The course uses a few running examples throughout the course to demonstrate concepts and provide concrete modeling examples.

After taking the course a student will be able to develop fairly advanced simulation models to explore fairly broad range of business environments and outcomes.

What's inside

Syllabus

Week 1: Probability Concepts

Uncertainty leads to challenges in decision making. Mathematically, we represent uncertainty by defining probabilities when several of the outcomes are possible in the future. This modules provides an overview of probability concepts that are essential to lay a good foundation for simulation modeling. We will also get our first exposure to Excel based simulations.

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Suitable for third- and fourth-year undergraduate students, as well as graduate students with an interest in learning simulation techniques for business problem-solving

Introduces advanced Excel techniques for modeling and executing simulation models

Emphasizes practical issues in simulation modeling that are often overlooked in textbooks

Includes several practical examples to demonstrate concepts and provide concrete modeling demonstrations

Provides foundational understanding of probability concepts, probability distributions, and Monte Carlo simulations

Covers discrete event simulations, exploring dependencies between related events

Reviews summary

Practical simulation for business decision making

According to learners, this course offers a strong foundation in simulation modeling for business decision-making using advanced Excel techniques. Students widely praise its practical approach, with real-world examples and hands-on activities proving highly applicable. A notable feature is the original material on Discrete Event Simulation in Excel. While generally well-received, a few learners suggest a solid grasp of probability concepts is essential, and some might find the pacing challenging without prior statistical knowledge. Overall, it stands out for its practical focus on quantitative problem-solving.

A foundational understanding of probability and statistics is beneficial.

"While the course reviews probability concepts, having a solid background made it much easier to follow."

"I struggled a bit with the initial probability sections; I wish I had brushed up on statistics beforehand."

"Learners without a strong grasp of basic probability might find the pace challenging."

Instructor explains complex topics clearly and makes content engaging.

"The instructor explains difficult concepts in a very understandable way, making the course engaging."

"I found the lectures clear and well-structured, building complexity step-by-step."

"The teaching style made learning simulation models much less intimidating than expected."

Features original material on Discrete Event Simulation using Excel.

"The discrete event simulation part in Excel was truly eye-opening; I haven't seen this approach anywhere else."

"This module provided truly innovative ways to model complex event dependencies directly within Excel."

"The material on discrete event simulation was completely original and incredibly valuable for my work."

Focuses on solving everyday and complex business challenges.

"The coffee shop examples made the Monte Carlo simulations very relatable and easy to grasp."

"I appreciate how the course breaks down complex business problems into manageable simulation components."

"The practical issues in simulation modeling covered were highly relevant to real-world scenarios I face."

Learn to apply simulation models to business problems using Excel.

"I found the advanced Excel techniques incredibly useful for modeling various business scenarios."

"The course clearly demonstrates how to implement Monte Carlo and discrete event simulations in Excel, which is directly applicable to my job."

"It's great to finally understand how to use Excel beyond basic functions for complex decision making."

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 Simulation Models for Decision Making with these activities:

Organize Course Materials for Easy Reference

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Keeping your course materials organized will facilitate efficient review and study.

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Create a dedicated folder or binder for course materials.
File lecture notes, assignments, and other materials in a logical order.
Label and color-code materials for easy identification.

Practice Basic Probability Concepts

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Familiarizing yourself with basic probability concepts will provide a solid foundation for the course.

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Review the definitions of probability and probability distributions.
Solve simple probability problems involving independent events.
Identify different probability distributions and their properties.

Follow Tutorials on Advanced Excel Techniques for Simulation Modeling

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These tutorials will provide additional guidance on using advanced Excel techniques for simulation modeling.

Browse courses on Advanced Excel Functions

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Search for tutorials on advanced Excel functions, such as RANDBETWEEN(), NORMINV(), and VLOOKUP().
Follow the tutorials and apply the techniques to your own simulation models.
Share your findings and insights with your classmates in the course forum.

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Complete Excel Simulation Drills

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Hands-on practice with Excel simulations will enhance your understanding of the techniques taught in the course.

Browse courses on Monte Carlo Simulation

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Download and install the Excel simulation template provided by the instructor.
Follow the instructions in the template to complete the simulation drills.
Analyze the results of your simulations and compare them to the theoretical expectations.

Read 'Simulation Modeling and Analysis' by Law and Kelton

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This book provides a comprehensive overview of simulation modeling techniques and will complement the material covered in the course.

View Simulation Modeling and Analysis (Industrial... on Amazon

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Read the assigned chapters and review the case studies presented in the book.
Summarize the key concepts and techniques discussed in the book.
Discuss the strengths and weaknesses of simulation modeling as a problem-solving tool.

Develop a Simulation Model for a Real-World Business Problem

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Creating a simulation model of a real-world business problem will allow you to apply the concepts learned in the course to a practical scenario.

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Identify a specific business problem that can be addressed using simulation modeling.
Gather data and assumptions about the key variables involved in the problem.
Develop a simulation model using the Excel template provided by the instructor or another appropriate software tool.
Run simulations and analyze the results to identify potential solutions or strategies for addressing the business problem.

Complete Discrete Event Simulation Drills

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These drills will enhance your understanding of discrete event simulation techniques, which are covered in the latter part of the course.

Browse courses on Discrete Event Simulation

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Study the concepts of discrete event simulation and event scheduling.
Use simulation software or Excel to implement discrete event simulations for various scenarios.
Analyze the simulation results and draw conclusions about the behavior of the system being modeled.

Develop a Comprehensive Simulation Model Report

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Creating a comprehensive simulation model report will showcase your ability to apply the concepts learned in the course to a practical problem and present your findings effectively.

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Select a specific business problem and develop a simulation model to address it.
Write a detailed report that describes the problem, the simulation model, the results of the simulations, and your recommendations based on the analysis.
Present your report to the class or a group of peers for feedback and evaluation.

Career center

Learners who complete Simulation Models for Decision Making will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists use data to solve business problems. Simulation modeling is a valuable tool for Data Scientists, and you will have the opportunity to develop and strengthen this skill-set through taking this course. Simulation Models for Decision Making will teach you how to use statistical methods and mathematical models to build predictive models that can be used to make better decisions. This is a valuable skill for Data Scientists, and it will give you a competitive advantage in the job market.

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Statistician

Statisticians use statistical methods to collect, analyze, and interpret data. Simulation modeling is a valuable tool for Statisticians, and the knowledge and skills you will learn in the Simulation Models for Decision Making course will provide you with a strong foundation for a career in this field.

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Operations Research Analyst

Operations Research Analysts use mathematical and analytical techniques to improve the efficiency and effectiveness of organizations. Simulation modeling is a valuable tool for Operations Research Analysts, and the knowledge and skills you will learn in the Simulation Models for Decision Making course will provide you with a strong foundation for a career in this field.

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Six Sigma Specialist

Six Sigma Specialists use statistical and analytical techniques to improve the quality of products and processes. Simulation modeling can be used to help Six Sigma Specialists identify and eliminate defects. The knowledge and skills you will learn in the Simulation Models for Decision Making course will provide you with a competitive advantage in the Six Sigma field and help you to improve the quality of products and processes.

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Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze financial data and make investment recommendations. Simulation modeling is a valuable tool for Quantitative Analysts, and the knowledge and skills you will learn in the Simulation Models for Decision Making course will provide you with a strong foundation for a career in this field. The course will teach you how to use Excel to build and analyze financial models, a critical skill for Quantitative Analysts.

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Data Analyst

Data Analysts use statistical and quantitative techniques to collect, clean, and analyze data to identify trends and patterns and solve business problems. The skills you will learn in the Simulation Models for Decision Making course, including probability, statistics, and modeling, will provide you with a strong foundation for a career as a Data Analyst. The course will also teach you how to use Excel to build and analyze simulation models, which is a valuable skill for Data Analysts.

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Risk Analyst

Risk Analysts identify and assess risks that could affect an organization. Simulation modeling can be used to help Risk Analysts quantify risks and develop mitigation strategies. The knowledge and skills you will learn in the Simulation Models for Decision Making course will provide you with a strong foundation for a career in this field. The course will teach you how to use Excel to build and analyze risk models, a valuable skill for Risk Analysts.

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Systems Analyst

Systems Analysts design and implement computer systems. Simulation modeling can be used to help Systems Analysts evaluate the performance of different system designs. The knowledge and skills you will learn in the Simulation Models for Decision Making course will provide you with a competitive advantage in the Systems Analysis field and help you to design and implement more efficient and effective systems.

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Management Consultant

Management Consultants help organizations improve their performance by identifying and solving business problems. Many consulting firms use simulation modeling to help their clients make better decisions. The knowledge and skills you will learn in the Simulation Models for Decision Making course will provide you with a competitive advantage in the consulting industry and increase your ability to raise the caliber of your counsel.

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Product Manager

Product Managers are responsible for managing the development and launch of new products. Simulation modeling can be used to help Product Managers make better decisions about product design, pricing, and marketing. The knowledge and skills you will learn in the Simulation Models for Decision Making course will provide you with a competitive advantage in the product management field and help you to launch more successful products.

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Software Engineer

Software Engineers design, develop, and maintain software applications. Simulation modeling can be used to help Software Engineers evaluate the performance of different software designs. The knowledge and skills you will learn in the Simulation Models for Decision Making course will provide you with a competitive advantage in the Software Engineering field and help you to design and develop more efficient and effective software applications.

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Business Analyst

Business Analysts combine advanced problem-solving and analytical skills to help organizations make better decisions. The knowledge gained from Simulation Models for Decision Making will provide you with a better understanding of how to use data to identify inefficiencies, improve processes, and develop better strategies. The course will also teach you how to use simulation modeling to create models that can help predict future outcomes and make better decisions.

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Market Researcher

Market Researchers conduct research to understand consumer behavior and trends. Simulation modeling can be used to help Market Researchers develop and test new marketing strategies. The knowledge and skills you will learn in the Simulation Models for Decision Making course will provide you with a competitive advantage in the Market Research field and help you to develop and test more effective marketing strategies.

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Financial Analyst

Financial Analysts use financial data to make investment recommendations and help businesses make financial decisions. The Simulation Models for Decision Making course will provide you with the skills and knowledge you need to understand financial data and develop simulation models to help you make better investment decisions. The course will also teach you how to use Excel to build and analyze financial models, which is a valuable skill for Financial Analysts.

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Teacher

Teachers educate students in a variety of subjects. Simulation modeling can be used to help Teachers create more engaging and effective lesson plans. Incorporating the course materials into your set of instructional tools will provide additional opportunities to actively engage your students and liven up your syllabi.

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