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Home » Basic and Health Sciences » Mathematics » Introduction to Computational Thinking (Fall 2020) (M-I-T) » Evolution in time and space: Advection and diffusion in 1D (M-I-T)

Evolution in time and space: Advection and diffusion in 1D (M-I-T)

Course:Introduction to Computational Thinking (Fall 2020) (M-I-T)
Discipline:Basic and Health Sciences
Institute:MIT
Instructor(s): Prof. Alan Edelman, Prof. David P. Sanders, Grant Sanderson, Dr. James Schloss, and Henri Drake
Level:Undergraduate

Introduction to Computational Thinking (Fall 2020) (M-I-T)

An overview of modern climate modeling (M-I-T)
Analysing Covid-19 data (M-I-T)
Arrays: Slices and views (M-I-T)
Basics of arrays in Julia (M-I-T)
Billiard models and event-driven simulations (M-I-T)
Building an ocean model from scratch (M-I-T)
Closing remarks (M-I-T)
Computational thinking illustrated (M-I-T)
Convolutions in image processing (M-I-T)
Image seam reminiscing (M-I-T)
Convolutions in the real world (M-I-T)
Introduction to climate modeling (M-I-T)
Convolutions on GPUs (M-I-T)
Introduction to DataFrames (M-I-T)
Defining new types (M-I-T)
Introduction to macros (M-I-T)
Environments for programming with Julia (M-I-T)
Introspection (M-I-T)
Everybody talks about R0 (M-I-T)
Iterative numerical schemes for Poisson and Laplace (M-I-T)

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