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Computational Thinking for Modeling and Simulation

Develop the thought processes involved in formulating a problem so a computer can effectively carry out the solution.  In particular, this course emphasizes use of computers for modeling physical systems and predicting their behavior.
Computational Thinking for Modeling and Simulation
Este curso está archivado
9 semanas estimadas
3–5 horas por semana
Al ritmo del instructor
Con un cronograma específico
Gratis
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Sobre este curso

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Computational thinking is becoming widely recognized as a skill necessary for every educated person in a technologically advanced society. 

We will focus on just a subset of computational thinking which concerns creating models of the physical world – something that engineers frequently need to do.  Because of that choice, this course covers many topics normally viewed as within the domain of mathematics such as algebra and calculus, but the solution procedures are algorithmic rather than symbolic.

The major themes of the course are:
  • 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?

De un vistazo

  • Institución: MITx
  • Tema: Informática
  • Nivel: Intermediate
  • Prerrequisitos:
    • Algebra
    • Calculus
  • Idioma: English
  • Transcripción de video: English

Lo que aprenderás

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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

Plan de estudios

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What is Computational Thinking? (representation, discretization, error, decomposition, verification)

Interpolation (building simple surrogates for more complex functions)

Integration (processes for numerical quadrature)

Randomness (generating and using pseudorandom variables in models)

Differentiation (numerical derivatives)

Solving equations (Gaussian elimination for linear systems, Newton-Raphson for non-linear systems)

Acerca de los instructores

Preguntas frecuentes

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Q: Is computational thinking about thinking like a computer does? 
A: No.  It’s about using computers to expand your own thinking.

¿Quién puede hacer este curso?

Lamentablemente, las personas residentes en uno o más de los siguientes países o regiones no podrán registrarse para este curso: Irán, Cuba y la región de Crimea en Ucrania. Si bien edX consiguió licencias de la Oficina de Control de Activos Extranjeros de los EE. UU. (U.S. Office of Foreign Assets Control, OFAC) para ofrecer nuestros cursos a personas en estos países y regiones, las licencias que hemos recibido no son lo suficientemente amplias como para permitirnos dictar este curso en todas las ubicaciones. edX lamenta profundamente que las sanciones estadounidenses impidan que ofrezcamos todos nuestros cursos a cualquier persona, sin importar dónde viva.

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