Computational Thinking for Modeling and Simulation from edX

Representation -- How do you encode information about the world in a computer? How do your choices in representation affect the ease with which you can solve problems?
Decomposition -- How do you break a large and diverse problem into many simpler parts?
Discretization -- How do you break up space and time into a large number of relatively small pieces? What are the alternative ways of doing this? What are the consequences of discretization procedures for accuracy and speed?
Verification -- How do you build confidence in the results of a model?

What you'll learn

By the end of this course, students will be able to:

Select and implement methods for interpolation and understand their consequences for convergence of model results as discretization is refined.
Carry out a few simple methods for numerical integration
Implement procedures for numerical differentiation
Write programs to solve systems of equations, both linear and non-linear

What's inside

Learning objectives

Select and implement methods for interpolation and understand their consequences for convergence of model results as discretization is refined.
By the end of this course, students will be able to:
Carry out a few simple methods for numerical integration

Implement procedures for numerical differentiation
Write programs to solve systems of equations, both linear and non-linear

Select and implement methods for interpolation and understand their consequences for convergence of model results as discretization is refined.
By the end of this course, students will be able to:
Carry out a few simple methods for numerical integration
Implement procedures for numerical differentiation
Write programs to solve systems of equations, both linear and non-linear

Syllabus

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Provides foundation for learners completely new to the field of computational thinking

Suitable for learners eager to advance their understanding of computational thinking beyond the foundational level

Provides opportunities to use the programming language of the learner's choice

May require additional learning for learners without background in calculus and matrix algebra

Focuses on mathematical techniques rather than conceptual understanding of computational thinking

Learners may need to supplement the course with additional resources to gain a comprehensive understanding of computational thinking

Reviews summary

Watered-down course materials

According to one student, the materials for the course titled Computational Thinking for Modeling and Simulation are watered down when compared to MITx's other offerings. This learner says the experience left them disappointed.

This course's materials are not as strong or difficult as MIT's local offerings.

"This is not 2.086 MIT offers to its local students."

Career center

Learners who complete Computational Thinking for Modeling and Simulation will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data scientists prepare data for analysis, build models using that data, and then analyze the results. They use their findings to solve problems and make predictions. This course can help build a foundation in computational thinking, which is essential for success in this role. By learning how to break down problems into smaller parts, represent data in a computer, and verify the results of models, you will be well-prepared to succeed as a data scientist.

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Software Engineer

Software engineers design, develop, test, and maintain software systems. They use their knowledge of programming languages and algorithms to create software that meets the needs of users and businesses. This course can help build a foundation in computational thinking, which is essential for success in this role. By learning how to break down problems into smaller parts, represent data in a computer, and verify the results of models, you will be well-prepared to succeed as a software engineer.

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Operations Research Analyst

Operations research analysts use mathematical and analytical techniques to solve problems in business and industry. They use their skills to improve efficiency, productivity, and decision-making. This course can help build a foundation in computational thinking, which is essential for success in this role. By learning how to break down problems into smaller parts, represent data in a computer, and verify the results of models, you will be well-prepared to succeed as an operations research analyst.

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Financial Analyst

Financial analysts use their knowledge of finance and economics to make investment recommendations and provide financial advice to clients. They use their skills to analyze financial data, build models, and forecast future trends. This course can help build a foundation in computational thinking, which is essential for success in this role. By learning how to break down problems into smaller parts, represent data in a computer, and verify the results of models, you will be well-prepared to succeed as a financial analyst.

See salaries and explore the career path for Financial Analyst

Quantitative Analyst

Quantitative analysts use their knowledge of mathematics, statistics, and programming to develop and implement trading strategies. They use their skills to analyze financial data, build models, and forecast future trends. This course can help build a foundation in computational thinking, which is essential for success in this role. By learning how to break down problems into smaller parts, represent data in a computer, and verify the results of models, you will be well-prepared to succeed as a quantitative analyst.

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Actuary

Actuaries use their knowledge of mathematics, statistics, and economics to assess risk and uncertainty. They use their skills to develop and implement insurance and pension plans. This course can help build a foundation in computational thinking, which is essential for success in this role. By learning how to break down problems into smaller parts, represent data in a computer, and verify the results of models, you will be well-prepared to succeed as an actuary.

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Data Analyst

Data analysts use their knowledge of data analysis techniques to extract insights from data. They use their skills to identify trends, patterns, and anomalies in data. This course can help build a foundation in computational thinking, which is essential for success in this role. By learning how to break down problems into smaller parts, represent data in a computer, and verify the results of models, you will be well-prepared to succeed as a data analyst.

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Business Analyst

Business analysts use their knowledge of business processes and data analysis techniques to identify opportunities for improvement. They use their skills to develop and implement solutions that improve efficiency, productivity, and decision-making. This course can help build a foundation in computational thinking, which is essential for success in this role. By learning how to break down problems into smaller parts, represent data in a computer, and verify the results of models, you will be well-prepared to succeed as a business analyst.

See salaries and explore the career path for Business Analyst

Statistician

Statisticians use their knowledge of statistics and data analysis techniques to collect, analyze, and interpret data. They use their skills to draw conclusions about the world around us. This course can help build a foundation in computational thinking, which is essential for success in this role. By learning how to break down problems into smaller parts, represent data in a computer, and verify the results of models, you will be well-prepared to succeed as a statistician.

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Market Researcher

Market researchers use their knowledge of market research techniques to collect, analyze, and interpret data about consumers and markets. They use their skills to help businesses understand their customers and make better decisions. This course can help build a foundation in computational thinking, which is essential for success in this role. By learning how to break down problems into smaller parts, represent data in a computer, and verify the results of models, you will be well-prepared to succeed as a market researcher.

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Risk Analyst

Risk analysts use their knowledge of risk management techniques to identify, assess, and mitigate risks. They use their skills to help businesses make informed decisions about risk. This course can help build a foundation in computational thinking, which is essential for success in this role. By learning how to break down problems into smaller parts, represent data in a computer, and verify the results of models, you will be well-prepared to succeed as a risk analyst.

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Consultant

Consultants use their knowledge of business and industry to help clients solve problems and improve performance. They use their skills to develop and implement solutions that meet the needs of clients. This course can help build a foundation in computational thinking, which is essential for success in this role. By learning how to break down problems into smaller parts, represent data in a computer, and verify the results of models, you will be well-prepared to succeed as a consultant.

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Economist

Economists use their knowledge of economics to study the production, distribution, and consumption of goods and services. They use their skills to analyze economic data and make predictions about the future. This course can help build a foundation in computational thinking, which is essential for success in this role. By learning how to break down problems into smaller parts, represent data in a computer, and verify the results of models, you will be well-prepared to succeed as an economist.

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Teacher

Teachers use their knowledge of education and subject matter to teach students at all levels. They use their skills to create lesson plans, deliver instruction, and assess student learning. This course can help build a foundation in computational thinking, which is essential for success in this role. By learning how to break down problems into smaller parts, represent data in a computer, and verify the results of models, you will be well-prepared to teach your students about computational thinking.

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Researcher

Researchers use their knowledge of research methods to conduct research in a variety of fields. They use their skills to design and implement research studies, collect and analyze data, and draw conclusions about their findings. This course can help build a foundation in computational thinking, which is essential for success in this role. By learning how to break down problems into smaller parts, represent data in a computer, and verify the results of models, you will be well-prepared to succeed as a researcher.

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Computational Thinking for Modeling and Simulation

What you'll learn

What's inside

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Syllabus

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Reviews summary

Watered-down course materials

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