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William Davis
In this course you will learn to use Monte Carlo simulations to better your decision making when dealing with uncertainty.
Read more
In this course you will learn to use Monte Carlo simulations to better your decision making when dealing with uncertainty.
Read more
In this course you will learn to use Monte Carlo simulations to better your decision making when dealing with uncertainty.
Do you need to make a difficult decision about some uncertain future outcome? Maybe you need to estimate a project cost or schedule, or create a forecast for when your agile-developed software product can be delivered to customers. In this course, Monte Carlo Simulation Fundamentals, you’ll learn how to model these and other uncertainties using a Monte Carlo simulation model in Microsoft Excel. First, you’ll learn why you’ll want to use Monte Carlo simulation to solve estimation problems. Then, you’ll learn how to create a Monte Carlo simulation from scratch, and how to use pre-built Monte Carlo simulation models. Finally, you’ll discover some more complicated problems that commercial Monte Carlo simulation products can solve. By the end of this course, you’ll know what a Monte Carlo simulation is, why it’s used, and how to create your own Monte Carlo simulation using the built-in functions inside Microsoft Excel.
Register for this course and see more details by visiting:
OpenCourser.com/course/3g8yf7/monte
What's inside
Syllabus
Course Overview
Introduction to Monte Carlo Simulation
Understand Commonly Used Probability Distributions
Monte Carlo Simulation Foundations
Read more
Syllabus
Course Overview
Introduction to Monte Carlo Simulation
Understand Commonly Used Probability Distributions
Monte Carlo Simulation Foundations
Read more
Build Your First Monte Carlo Simulation Model
Add a Histogram and Statistics to Your Model
Using a Native Excel Monte Carlo Simulation Model
Build More Complex Monte Carlo Simulation Models
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops modeling and forecasting skills, which are in high demand for professionals in various industries
Builds a strong foundation for understanding Monte Carlo simulations
Delivered by William Davis, an experienced instructor in Monte Carlo simulations
Utilizes Microsoft Excel, which is widely accessible and familiar to many learners
May require additional background knowledge in statistics and probability theory
Covers fundamental concepts without diving into advanced topics or industry-specific applications
Save this course
Save Monte Carlo Simulation Fundamentals to your list so you can find it easily later:
Save
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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 Monte Carlo Simulation Fundamentals with these
activities:
Identify your weak areas in probability and statistics
Show steps
Begin by identifying areas where you need to refresh your knowledge of probability and statistics. This foundation is crucial for building a strong conceptual framework prior to the course.
Browse courses on
Probability
Show steps
-
Take a practice quiz or exam.
-
Review your previous coursework and notes.
-
Consult with a tutor or mentor.
Discuss Monte Carlo methods with peers
Show steps
Engage with fellow learners by discussing concepts, sharing insights, and collaborating on Monte Carlo simulation techniques. This exchange facilitates deeper understanding and strengthens your knowledge retention.
Browse courses on
Monte Carlo Simulation
Show steps
-
Join a study group or online forum.
-
Participate in discussions.
-
Share your own insights and experiences.
Simulate data using Excel
Show steps
Engage in hands-on practice by simulating data using Excel. This exercise allows you to reinforce the core concepts and develop a deeper understanding of Monte Carlo simulations.
Browse courses on
Monte Carlo Simulation
Show steps
-
Create a dataset using a random number generator.
-
Apply different probability distributions to the data.
-
Analyze the simulated data using descriptive statistics and visualizations.
-
Compare the simulated data to real-world data.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Learn about advanced techniques in Monte Carlo simulation
Show steps
Expand your knowledge by exploring advanced techniques in Monte Carlo simulation through online tutorials. These resources provide valuable insights that complement your understanding of the essential principles.
Browse courses on
Markov Chain Monte Carlo
Show steps
-
Identify specific areas where you want to enhance your knowledge.
-
Find reputable online tutorials.
-
Follow the tutorials and practice the techniques.
Build a spreadsheet model of a business problem
Show steps
Apply your newfound knowledge by building a spreadsheet model that incorporates Monte Carlo simulations to tackle a real-world business problem. This project provides a valuable opportunity to test your understanding and develop practical skills.
Browse courses on
Monte Carlo Simulation
Show steps
-
Identify a business problem that can benefit from simulation.
-
Gather and analyze relevant data.
-
Build a spreadsheet model that incorporates Monte Carlo simulations.
-
Interpret the results of the simulations.
-
Communicate your findings to stakeholders.
Create a video tutorial on Monte Carlo simulations
Show steps
Reinforce your knowledge and aid other learners by creating a video tutorial that explains the concepts of Monte Carlo simulations. This activity deepens your understanding and contributes to the broader learning community.
Browse courses on
Monte Carlo Simulation
Show steps
-
Identify a specific topic or concept to cover.
-
Create a storyboard and script.
-
Record and edit your video.
-
Publish and share your video.
Participate in a Monte Carlo simulation competition
Show steps
Put your skills to the test and gain valuable experience by participating in a Monte Carlo simulation competition. This challenging activity pushes your boundaries and helps you excel in applying the concepts you've learned.
Browse courses on
Monte Carlo Simulation
Show steps
-
Find a relevant competition.
-
Form a team or work individually.
-
Develop a solution to the competition problem.
-
Submit your solution and compete.
Contribute to an open-source Monte Carlo simulation library
Show steps
Enhance your understanding and make a meaningful contribution by participating in an open-source Monte Carlo simulation library. This activity allows you to engage with the wider developer community and hone your skills in a real-world setting.
Browse courses on
Monte Carlo Simulation
Show steps
-
Find a suitable open-source library.
-
Identify an area to contribute.
-
Propose and implement your changes.
-
Submit a pull request and collaborate with the community.
Identify your weak areas in probability and statistics
Show steps
Begin by identifying areas where you need to refresh your knowledge of probability and statistics. This foundation is crucial for building a strong conceptual framework prior to the course.
Browse courses on
Probability
Show steps
Show steps
Show steps
- Take a practice quiz or exam.
- Review your previous coursework and notes.
- Consult with a tutor or mentor.
Discuss Monte Carlo methods with peers
Show steps
Engage with fellow learners by discussing concepts, sharing insights, and collaborating on Monte Carlo simulation techniques. This exchange facilitates deeper understanding and strengthens your knowledge retention.
Browse courses on
Monte Carlo Simulation
Show steps
Show steps
Show steps
- Join a study group or online forum.
- Participate in discussions.
- Share your own insights and experiences.
Simulate data using Excel
Show steps
Engage in hands-on practice by simulating data using Excel. This exercise allows you to reinforce the core concepts and develop a deeper understanding of Monte Carlo simulations.
Browse courses on
Monte Carlo Simulation
Show steps
Show steps
Show steps
- Create a dataset using a random number generator.
- Apply different probability distributions to the data.
- Analyze the simulated data using descriptive statistics and visualizations.
- Compare the simulated data to real-world data.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Learn about advanced techniques in Monte Carlo simulation
Show steps
Expand your knowledge by exploring advanced techniques in Monte Carlo simulation through online tutorials. These resources provide valuable insights that complement your understanding of the essential principles.
Browse courses on
Markov Chain Monte Carlo
Show steps
Show steps
Show steps
- Identify specific areas where you want to enhance your knowledge.
- Find reputable online tutorials.
- Follow the tutorials and practice the techniques.
Build a spreadsheet model of a business problem
Show steps
Apply your newfound knowledge by building a spreadsheet model that incorporates Monte Carlo simulations to tackle a real-world business problem. This project provides a valuable opportunity to test your understanding and develop practical skills.
Browse courses on
Monte Carlo Simulation
Show steps
Show steps
Show steps
- Identify a business problem that can benefit from simulation.
- Gather and analyze relevant data.
- Build a spreadsheet model that incorporates Monte Carlo simulations.
- Interpret the results of the simulations.
- Communicate your findings to stakeholders.
Create a video tutorial on Monte Carlo simulations
Show steps
Reinforce your knowledge and aid other learners by creating a video tutorial that explains the concepts of Monte Carlo simulations. This activity deepens your understanding and contributes to the broader learning community.
Browse courses on
Monte Carlo Simulation
Show steps
Show steps
Show steps
- Identify a specific topic or concept to cover.
- Create a storyboard and script.
- Record and edit your video.
- Publish and share your video.
Participate in a Monte Carlo simulation competition
Show steps
Put your skills to the test and gain valuable experience by participating in a Monte Carlo simulation competition. This challenging activity pushes your boundaries and helps you excel in applying the concepts you've learned.
Browse courses on
Monte Carlo Simulation
Show steps
Show steps
Show steps
- Find a relevant competition.
- Form a team or work individually.
- Develop a solution to the competition problem.
- Submit your solution and compete.
Contribute to an open-source Monte Carlo simulation library
Show steps
Enhance your understanding and make a meaningful contribution by participating in an open-source Monte Carlo simulation library. This activity allows you to engage with the wider developer community and hone your skills in a real-world setting.
Browse courses on
Monte Carlo Simulation
Show steps
Show steps
Show steps
- Find a suitable open-source library.
- Identify an area to contribute.
- Propose and implement your changes.
- Submit a pull request and collaborate with the community.
Career center
Learners who complete Monte Carlo Simulation Fundamentals will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists collect, interpret, and analyze data to draw valuable insights and improve decision-making. A foundational understanding of probability distributions and Monte Carlo simulations, such as those taught in this course, will prove invaluable for Data Scientists. By taking this course, aspiring Data Scientists can gain the skills necessary to build accurate and reliable data models that can help businesses make informed decisions in the face of uncertainty.
Financial Analyst
Financial Analyst
Financial Analysts use financial data to make recommendations on investments and other financial decisions, Monte Carlo simulations are widely used in finance for risk assessment and portfolio optimization. By taking this course, Financial Analysts can enhance their understanding of these methods and gain a competitive edge in their field.
Market Researcher
Market Researcher
Market Researchers are responsible for collecting and analyzing data to identify market opportunities and trends. Monte Carlo simulations are frequently used in market research to understand consumer behavior and forecast demand. This course can help Market Researchers build the skills needed to conduct effective market research studies and make accurate predictions.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and analytical techniques to optimize processes and improve efficiency. Monte Carlo simulations play a crucial role in operations research, allowing analysts to model complex systems and evaluate different scenarios. By taking this course, aspiring Operations Research Analysts can acquire foundational knowledge and skills essential for success in this field.
Project Manager
Project Manager
Project Managers are responsible for planning, executing, and delivering projects successfully. Monte Carlo simulations are commonly used in project management to assess project risks and estimate project schedules. This course can equip Project Managers with the tools needed to manage projects more effectively and make informed decisions in the face of uncertainties.
Risk Manager
Risk Manager
Risk Managers identify, assess, and mitigate risks that organizations face. Monte Carlo simulations are widely used in risk management to quantify and evaluate risks. By completing this course, Risk Managers can enhance their knowledge of these techniques and develop the skills needed to manage risks effectively.
Software Developer
Software Developer
Software Developers design and develop software systems. Monte Carlo simulations are occasionally used in software development, particularly in the testing and performance analysis of software systems. While not a core skill for Software Developers, this course may provide a helpful introduction to these techniques for those interested in specializing in software testing or performance engineering.
Statistician
Statistician
Statisticians collect, analyze, and interpret data to draw meaningful conclusions. Monte Carlo simulations are a fundamental tool in statistics, used for sampling, modeling, and hypothesis testing. By taking this course, aspiring Statisticians can build a solid foundation in these methods and prepare for advanced studies in the field.
Actuary
Actuary
Actuaries analyze and manage financial risks. Monte Carlo simulations are widely used in actuarial science to model complex financial scenarios and assess risks. While this course provides a foundational understanding of these techniques, further specialized training and certification are typically required for a career as an Actuary.
Business Analyst
Business Analyst
Business Analysts identify and analyze business problems and opportunities. Monte Carlo simulations are sometimes used in business analysis to assess risks and make informed decisions. While not a core skill for Business Analysts, this course may provide a helpful introduction to these techniques for those interested in specializing in risk analysis or decision-making.
Data Analyst
Data Analyst
Data Analysts collect, analyze, and interpret data to identify trends and patterns. Monte Carlo simulations are occasionally used in data analysis, particularly in modeling and forecasting. While not a core skill for Data Analysts, this course may provide a useful introduction to these techniques for those interested in specializing in predictive analytics.
Financial Planner
Financial Planner
Financial Planners help individuals and families manage their finances and plan for the future. Monte Carlo simulations are sometimes used in financial planning to assess the impact of different investment strategies and retirement scenarios. While not a core skill for Financial Planners, this course may provide a helpful introduction to these techniques for those interested in specializing in retirement planning or financial modeling.
Investment Analyst
Investment Analyst
Investment Analysts assess and make recommendations on investments. Monte Carlo simulations are occasionally used in investment analysis to evaluate the risks and returns of different investment portfolios. While not a core skill for Investment Analysts, this course may provide a helpful introduction to these techniques for those interested in specializing in risk assessment or portfolio management.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical techniques to analyze financial data and make investment decisions. Monte Carlo simulations are widely used in quantitative analysis to model complex financial scenarios and assess risks. This course may provide a helpful introduction to these techniques for aspiring Quantitative Analysts, but further specialized training and knowledge of advanced mathematics and statistics are typically required.
Teacher
Teacher
Teachers educate students at all levels, from kindergarten through university. Monte Carlo simulations are rarely used in teaching, except perhaps in advanced statistics or mathematics courses at the university level. This course is unlikely to be directly applicable to a teaching career.
For more career information including salaries, visit:
OpenCourser.com/course/3g8yf7/monte
Reading list
We've selected nine 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
Monte Carlo Simulation Fundamentals.
This textbook explains the use of simulation modeling and Monte Carlo methods in project planning.
An industry-focused guide for using Monte Carlo simulations in the context of finance and risk management.
A reference book containing a wide range of numerical methods, including a discussion of Monte Carlo simulation.
A research-focused reference for those interested in the details of Monte Carlo algorithms.
Provides a comprehensive overview of Monte Carlo methods for financial engineering. It covers a wide range of topics, from the basics of probability and statistics to more advanced topics such as option pricing and risk management.
Provides a comprehensive overview of stochastic simulation and Monte Carlo methods. It covers a wide range of topics, from the basics of probability and statistics to more advanced topics such as Markov chain Monte Carlo.
Provides a practical guide to using Monte Carlo simulation in Stata. It covers a wide range of topics, from the basics of probability and statistics to more advanced topics such as Bayesian inference.
Provides a practical guide to using Markov chain Monte Carlo methods. It covers a wide range of topics, from the basics of probability and statistics to more advanced topics such as Bayesian inference.
Provides a comprehensive overview of data analysis using regression and multilevel/hierarchical models. It covers a wide range of topics, from the basics of probability and statistics to more advanced topics such as Bayesian inference.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/3g8yf7/monte
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Time
209 hours
Level
Introductory
Via
Pluralsight
Instructor
William Davis
Language
English
Good to know
Develops modeling and forecasting skills, which are in high demand for professionals in various industries
Builds a strong foundation for understanding Monte Carlo simulations
Delivered by William Davis, an experienced instructor in Monte Carlo simulations
Utilizes Microsoft Excel, which is widely accessible and familiar to many learners
May require additional background knowledge in statistics and probability theory
Covers fundamental concepts without diving into advanced topics or industry-specific applications
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