MIT 18.S191/6.S083/22.S092 | Fall 2020

Introduction to Computational Thinking

by Alan Edelman, David P. Sanders, Grant Sanderson, & James Schloss, Benoit Forget

Course home Software installation Cheatsheets Homework 0
Course content

week 1

Lecture 1 - Images and Abstraction Lecture 2 - Convolutions Homework 1

week 2

Lecture 3 - Dynamic programming, Views and GPUs Lecture 4 - Live coding seam carving Homework 2

week 3

Lecture 5 - Structure and Dispatch Lecture 6 - Understanding data Homework 3

week 4

Lecture 7 - Introspection, COVID Data visualization Lecture 8 - Probability via computation

week 5

Lecture 9 - Computational thinking, graphs are matrices, the expression problem Lecture 10 - Graphs and disease spread Homework 4

week 6

Lecture 11 - Epidemic modeling & Documenting code Lecture 12 - Macroscopic models: discrete vs continuous Homework 5

week 7

No class on 10/13 as per MIT Calendar Lecture 13 - Graphs and Network Dynamics Homework 6

week 8

Lecture 14 - Raytracing, your own parallelism, abstract arrays Lecture 15 - Billiard model and event-driven simulation

week 9

Lecture 16 - Raytracing in 3D Lecture 17 - Raytracing live-coding Homework 7

week 10

Lecture 18 - Hierarchical Thinking, Greedy Algorithms, Jacobi's Method, and Multigrid Lecture 19 - Floating Point Arithmetic Homework 8

week 11

Lecture 20 - Introduction to Climate Modeling, Nonlinear dynamics and Stability Lecture 21 - Nonlinear Climate Dynamics and Snowball Earth Homework 9

week 12

Lecture 22 - Diffusion Equation and Time and Space evolution Lecture 23 - Heat Transfer by Ocean Currents Homework 10

week 13

Lecture 24 - Ocean Modeling, Generic Programming Lecture 25 - An overview of modern climate modeling

week 14

Lecture 26 - Discrete Fourier Transform

Synchronize play when the class is live

Lecture 4 - Seam carving live coding session

Edit this page on Last modified: March 10, 2022. Website built with Franklin.jl and the Julia programming language.