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Sergei Savin
and
Senthil Veeraraghavan
Useful quantitative models help you to make informed decisions both in situations in which the factors affecting your decision are clear, as well as in situations in which some important factors are not clear at all. In this course, you can learn how to create quantitative models to reflect complex realities, and how to include in your model elements of risk and uncertainty. You’ll also learn the methods for creating predictive models for identifying optimal choices; and how those choices change in response to changes in the model’s assumptions. You’ll also learn the basics of the measurement and management of risk. By the end of this course, you’ll be able to build your own models with your own data, so that you can begin making data-informed decisions. You’ll also be prepared for the next course in the Specialization.
Register for this course and see more details by visiting:
OpenCourser.com/course/2n0jtr/modeling
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What's inside
Syllabus
Week 1: Modeling Decisions in Low Uncertainty Settings
This module is designed to teach you how to analyze settings with low levels of uncertainty, and how to identify the best decisions in these settings. You'll explore the optimization toolkit, learn how to build an algebraic model using an advertising example, convert the algebraic model to a spreadsheet model, work with Solver to discover the best possible decision, and examine an example that introduces a simple representation of risk to the model. By the end of this module, you'll be able to build an optimization model, use Solver to uncover the optimal decision based on your data, and begin to adjust your model to account for simple elements of risk. These skills will give you the power to deal with large models as long as the actual uncertainty in the input values is not too high.
Read more
Syllabus
Week 1: Modeling Decisions in Low Uncertainty Settings
This module is designed to teach you how to analyze settings with low levels of uncertainty, and how to identify the best decisions in these settings. You'll explore the optimization toolkit, learn how to build an algebraic model using an advertising example, convert the algebraic model to a spreadsheet model, work with Solver to discover the best possible decision, and examine an example that introduces a simple representation of risk to the model. By the end of this module, you'll be able to build an optimization model, use Solver to uncover the optimal decision based on your data, and begin to adjust your model to account for simple elements of risk. These skills will give you the power to deal with large models as long as the actual uncertainty in the input values is not too high.
Read more
Traffic lights
Traffic lights
Read about what's good
what should give you pause and
possible dealbreakers
Suitable for students who are returning to study after a break or who are new to quantitative methods
Appropriate for students with a business background who want to improve their decision-making skills
Provides a solid foundation in quantitative modeling techniques
Taught by experienced instructors with strong academic and industry credentials
Offers practical examples and case studies to illustrate the application of quantitative modeling
Requires basic mathematical skills and a willingness to engage with technical concepts
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Reviews summary
Modeling business risk with excel tools
According to learners, this course offers a solid foundation in modeling risk and realities using quantitative methods, particularly focusing on Excel-based tools like Solver and simulation. Many students find the content highly practical and directly applicable to their work in areas like finance and business analysis. The lectures are often praised for clarity and structure. However, a notable number of students mention that the course assumes significant prior knowledge in statistics and advanced Excel, making it challenging for beginners. Some also felt that parts of the course, particularly the Excel implementation steps or certain theoretical sections, were rushed or lacked depth. Overall, it's seen as a valuable course for those with the right background.
Concepts generally well explained.
"The instructor explained complex topics like probability distributions and simulation in Excel very clearly."
"The lectures were well-structured and easy to follow."
"The instructor is excellent, explaining complex ideas simply."
Directly applicable using Excel tools.
"The practical exercises using Solver were super helpful for applying what I learned immediately to my work projects."
"The Excel-based approach is very practical for real-world application."
"Very practical course using Excel. I appreciated the step-by-step guides on building models and using Solver..."
"I learned how to use practical tools and strategies that I could apply immediately to my work."
Some sections or implementation felt fast.
"Some parts felt a bit rushed, particularly the section on correlation and efficient frontier in week 2."
"The pace was too fast, especially in week 2 dealing with multiple variables."
"The Excel part felt rushed in places."
Requires prior statistics & Excel knowledge.
"It assumes a strong background in statistics which I didn't have."
"The course assumes too much prior knowledge in both statistics and advanced Excel."
"Requires a decent level of Excel proficiency."
"A statistics refresher would be beneficial before starting."
"Not suitable for beginners."
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 Modeling Risk and Realities with these
activities:
Think Bayes
Show steps
Enhance your understanding of probability and Bayesian inference by reviewing the book Think Bayes.
View
Probably Overthinking It: How to Use Data to...
on Amazon
Show steps
-
Read the book and take notes
-
Work through the exercises in the book
-
Discuss the book with others
Monte Carlo Simulation Tutorial
Show steps
Expand your understanding of uncertainty modeling by following a tutorial on Monte Carlo simulation.
Browse courses on
Monte Carlo Simulation
Show steps
-
Learn the basics of Monte Carlo simulation
-
Follow a step-by-step tutorial to build a Monte Carlo simulation model
-
Run the simulation model and analyze the results
Data Visualization with Excel
Show steps
Develop your data visualization skills by creating charts and graphs in Excel to represent complex data.
Browse courses on
Data Visualization
Show steps
-
Learn about different chart types in Excel
-
Create a chart from a data set
-
Customize the appearance of a chart
-
Interpret data from a chart
Six other activities
Expand to see all activities and additional details
Show all nine activities
Excel Solver Practice
Show steps
Reinforce your understanding of optimization techniques by using Excel Solver to solve linear programming problems.
Browse courses on
Optimization
Show steps
-
Review the Excel Solver documentation
-
Create an Excel model for a simple optimization problem
-
Use Solver to solve the optimization problem
-
Analyze the results of the optimization
Peer Review of Modeling Assumptions
Show steps
Gain feedback on your modeling assumptions by sharing your work with peers for review.
Browse courses on
Modeling
Show steps
-
Create a model and document your assumptions
-
Share your model with peers
-
Receive feedback and revise your model
Risk Assessment Exercises
Show steps
Improve your risk assessment skills by completing a series of exercises.
Browse courses on
Risk Assessment
Show steps
-
Identify hazards and assess their risks
-
Develop risk mitigation strategies
-
Evaluate the effectiveness of risk mitigation strategies
Data Modeling Workshop
Show steps
Deepen your understanding of data modeling by attending a workshop.
Browse courses on
Data Modeling
Show steps
-
Register for a data modeling workshop
-
Attend the workshop and participate in exercises
-
Apply what you learned to a real-world data modeling project
Risk Management Case Study
Show steps
Apply your knowledge of risk management by developing a case study that analyzes a real-world scenario.
Browse courses on
Risk Management
Show steps
-
Identify a business scenario with risk factors
-
Analyze the risks associated with the scenario
-
Develop a risk management plan
-
Evaluate the effectiveness of the risk management plan
Contribute to an Open-Source Decision-Making Project
Show steps
Apply your knowledge of decision-making theory by contributing to an open-source project.
Browse courses on
Decision-Making
Show steps
-
Find an open-source project related to decision-making
-
Identify an area where you can contribute
-
Make a contribution to the project
-
Review the feedback on your contribution
Think Bayes
Show steps
Enhance your understanding of probability and Bayesian inference by reviewing the book Think Bayes.
View
Probably Overthinking It: How to Use Data to...
on Amazon
Show steps
Show steps
Show steps
- Read the book and take notes
- Work through the exercises in the book
- Discuss the book with others
Monte Carlo Simulation Tutorial
Show steps
Expand your understanding of uncertainty modeling by following a tutorial on Monte Carlo simulation.
Browse courses on
Monte Carlo Simulation
Show steps
Show steps
Show steps
- Learn the basics of Monte Carlo simulation
- Follow a step-by-step tutorial to build a Monte Carlo simulation model
- Run the simulation model and analyze the results
Data Visualization with Excel
Show steps
Develop your data visualization skills by creating charts and graphs in Excel to represent complex data.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Learn about different chart types in Excel
- Create a chart from a data set
- Customize the appearance of a chart
- Interpret data from a chart
Six other activities
Expand to see all activities and additional details
Show all nine activities
Excel Solver Practice
Show steps
Reinforce your understanding of optimization techniques by using Excel Solver to solve linear programming problems.
Browse courses on
Optimization
Show steps
Show steps
Show steps
- Review the Excel Solver documentation
- Create an Excel model for a simple optimization problem
- Use Solver to solve the optimization problem
- Analyze the results of the optimization
Peer Review of Modeling Assumptions
Show steps
Gain feedback on your modeling assumptions by sharing your work with peers for review.
Browse courses on
Modeling
Show steps
Show steps
Show steps
- Create a model and document your assumptions
- Share your model with peers
- Receive feedback and revise your model
Risk Assessment Exercises
Show steps
Improve your risk assessment skills by completing a series of exercises.
Browse courses on
Risk Assessment
Show steps
Show steps
Show steps
- Identify hazards and assess their risks
- Develop risk mitigation strategies
- Evaluate the effectiveness of risk mitigation strategies
Data Modeling Workshop
Show steps
Deepen your understanding of data modeling by attending a workshop.
Browse courses on
Data Modeling
Show steps
Show steps
Show steps
- Register for a data modeling workshop
- Attend the workshop and participate in exercises
- Apply what you learned to a real-world data modeling project
Risk Management Case Study
Show steps
Apply your knowledge of risk management by developing a case study that analyzes a real-world scenario.
Browse courses on
Risk Management
Show steps
Show steps
Show steps
- Identify a business scenario with risk factors
- Analyze the risks associated with the scenario
- Develop a risk management plan
- Evaluate the effectiveness of the risk management plan
Contribute to an Open-Source Decision-Making Project
Show steps
Apply your knowledge of decision-making theory by contributing to an open-source project.
Browse courses on
Decision-Making
Show steps
Show steps
Show steps
- Find an open-source project related to decision-making
- Identify an area where you can contribute
- Make a contribution to the project
- Review the feedback on your contribution
Career center
Learners who complete Modeling Risk and Realities will develop knowledge and skills
that may be useful to these careers:
Risk Manager
Risk Manager
Risk managers help companies identify and manage risks. They use a variety of quantitative and qualitative techniques to assess risks and develop mitigation strategies. This course would help someone interested in becoming a risk manager by teaching them how to build quantitative models and incorporate risk and uncertainty into their models. It would also give them a foundation in the measurement and management of risk.
Quantitative Analyst
Quantitative Analyst
Quantitative analysts use mathematical and statistical models to analyze financial data. They develop trading strategies and make investment recommendations. This course would help someone interested in becoming a quantitative analyst by teaching them how to build quantitative models and incorporate risk and uncertainty into their models.
Insurance Actuary
Insurance Actuary
Insurance actuaries use mathematical and statistical models to assess the risks of insurance policies. They develop pricing strategies and make recommendations on policy coverage. This course would help someone interested in becoming an insurance actuary by teaching them how to build quantitative models and incorporate risk and uncertainty into their models.
Data Scientist
Data Scientist
Data scientists use mathematical and statistical models to analyze large datasets. They develop algorithms to identify patterns and trends, and they build models to predict future outcomes. This course would help someone interested in becoming a data scientist by teaching them how to build quantitative models and incorporate risk and uncertainty into their models.
Machine Learning Engineer
Machine Learning Engineer
Machine learning engineers use mathematical and statistical models to develop machine learning algorithms. These algorithms can be used to identify patterns and trends in data, and to make predictions about future outcomes. This course would help someone interested in becoming a machine learning engineer by teaching them how to build quantitative models and incorporate risk and uncertainty into their models.
Operations Research Analyst
Operations Research Analyst
Operations research analysts use mathematical and statistical models to solve business problems. They develop strategies to improve efficiency and productivity. This course would help someone interested in becoming an operations research analyst by teaching them how to build quantitative models and incorporate risk and uncertainty into their models.
Statistician
Statistician
Statisticians use mathematical and statistical methods to collect, analyze, and interpret data. They develop models to predict future outcomes and make recommendations on how to improve processes. This course would help someone interested in becoming a statistician by teaching them how to build quantitative models and incorporate risk and uncertainty into their models.
Market Researcher
Market Researcher
Market researchers use mathematical and statistical models to analyze market data. They develop strategies to improve marketing campaigns and increase sales. This course would help someone interested in becoming a market researcher by teaching them how to build quantitative models and incorporate risk and uncertainty into their models.
Business Analyst
Business Analyst
Business analysts use mathematical and statistical models to analyze business data. They develop strategies to improve business processes and increase profits. This course would help someone interested in becoming a business analyst by teaching them how to build quantitative models and incorporate risk and uncertainty into their models.
Economist
Economist
Economists use mathematical and statistical models to analyze economic data. They develop theories to explain economic behavior and make predictions about future economic trends. This course would help someone interested in becoming an economist by teaching them how to build quantitative models and incorporate risk and uncertainty into their models.
Financial Advisor
Financial Advisor
Financial advisors help individuals and businesses manage their finances. They develop investment plans and make recommendations on how to save for retirement, buy a home, or start a business. This course would help someone interested in becoming a financial advisor by teaching them how to build quantitative models and incorporate risk and uncertainty into their models.
Data Analyst
Data Analyst
Data analysts help companies make informed decisions by analyzing data. They use a variety of statistical techniques to identify trends and patterns in data, and they build models to predict future outcomes. This course would help someone interested in becoming a data analyst by teaching them how to build quantitative models and incorporate risk and uncertainty into their models. It would also give them a foundation in the measurement and management of risk.
Financial Analyst
Financial Analyst
Financial analysts help companies understand their financial situation. They build financial models to estimate a company's worth and predict its future cash flows. Many financial analysts use specialized software to build these models. This course would help someone interested in becoming a financial analyst by teaching them how to build quantitative models and incorporate risk and uncertainty into their models. It would also give them a foundation in the measurement and management of risk.
Management Consultant
Management Consultant
Management consultants help companies improve their performance. They use a variety of analytical techniques to identify problems and develop solutions. This course would help someone interested in becoming a management consultant by teaching them how to build quantitative models and incorporate risk and uncertainty into their models. It would also give them a foundation in the measurement and management of risk.
Software Engineer
Software Engineer
Software engineers design, develop, and maintain software applications. They use a variety of programming languages and tools to create software that meets the needs of users. This course would help someone interested in becoming a software engineer by teaching them how to build quantitative models and incorporate risk and uncertainty into their models.
For more career information including salaries, visit:
OpenCourser.com/course/2n0jtr/modeling
Reading list
We've selected seven 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
Modeling Risk and Realities.
Provides a comprehensive overview of the quantitative methods used in risk management, including topics such as risk measurement, risk modeling, and risk management. It valuable resource for students and practitioners who want to learn about the latest quantitative risk management techniques.
Provides a comprehensive overview of enterprise risk management, including topics such as risk identification, risk assessment, and risk mitigation. It valuable resource for students and practitioners who want to learn about the latest risk management techniques.
Provides an overview of the risk management practices used by financial institutions, including topics such as credit risk, market risk, and operational risk. It valuable resource for students and practitioners who want to learn about the latest risk management techniques.
Provides a comprehensive overview of risk management in the insurance industry, covering topics such as risk identification, risk assessment, and risk mitigation. It valuable resource for students and practitioners who want to learn about the latest risk management techniques.
Provides a comprehensive overview of risk management and crisis response, covering topics such as risk identification, risk assessment, and risk mitigation. It valuable resource for students and practitioners who want to learn about the latest risk management techniques.
Provides a practical guide to risk management, covering topics such as risk identification, risk assessment, and risk mitigation. It valuable resource for students and practitioners who want to learn about the latest risk management techniques.
Provides a comprehensive overview of risk management in the public sector, covering topics such as risk identification, risk assessment, and risk mitigation. It valuable resource for students and practitioners who want to learn about the latest risk management techniques.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/2n0jtr/modeling
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Effort
4 weeks of study, 1-3 hours/week
Via
Coursera
Institution
University of Pennsylvania
Instructors
Sergei Savin
Senthil Veeraraghavan
Language
English
Transcripts
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آذربایجان دیلی
This course belongs to a
collection
called
Business and Financial Modeling. It's comprised of five courses:
- Decision-Making and Scenarios
- Introduction to Spreadsheets and Models
- Modeling Risk and Realities (viewing)
- Wharton Business and Financial Modeling Capstone
- Fundamentals of Quantitative Modeling
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