MIT OCW 18.S191 Introduction to Computational Thinking (Fall 2022) (50 files)
 Lecture 25 - Modeling climate change.mp4 |
237.61MB |
| Lecture 25 - Modeling climate change.en.vtt |
97.54kB |
| Lecture 24 - Resistors, stencils and climate models.mp4 |
182.91MB |
| Lecture 24 - Resistors, stencils and climate models.en.vtt |
106.37kB |
| Lecture 23 - Advection and diffusion - PDEs in 1D.mp4 |
165.31MB |
| Lecture 23 - Advection and diffusion - PDEs in 1D.en.vtt |
86.36kB |
| Lecture 22 - Snowball Earth and hysteresis.mp4 |
194.33MB |
| Lecture 22 - Snowball Earth and hysteresis.en.vtt |
85.49kB |
| Lecture 21 - How to collaborate on software.mp4 |
230.08MB |
| Lecture 21 - How to collaborate on software.en.vtt |
91.58kB |
| Lecture 20 - A first climate model.mp4 |
246.64MB |
| Lecture 20 - A first climate model.en.vtt |
85.14kB |
| Lecture 19 - Why can't we predict the weather？.mp4 |
200.84MB |
| Lecture 19 - Why can't we predict the weather？.en.vtt |
93.91kB |
| Lecture 18 - Libraries & parameterized types.mp4 |
222.85MB |
| Lecture 18 - Libraries & parameterized types.en.vtt |
97.06kB |
| Lecture 17 - Time stepping and differential equations.mp4 |
194.01MB |
| Lecture 17 - Time stepping and differential equations.en.vtt |
95.19kB |
| Lecture 16 - Optimization.mp4 |
120.68MB |
| Lecture 16 - Optimization.en.vtt |
81.78kB |
| Lecture 15 - Linear models and simulations.mp4 |
123.72MB |
| Lecture 15 - Linear models and simulations.en.vtt |
89.62kB |
| Lecture 14 - Discrete & Continuous.mp4 |
219.43MB |
| Lecture 14 - Discrete & Continuous.en.vtt |
87.21kB |
| Lecture 13 - Random walks II.mp4 |
202.11MB |
| Lecture 13 - Random walks II.en.vtt |
97.56kB |
| Lecture 12 - Random walks I.mp4 |
168.17MB |
| Lecture 12 - Random walks I.en.vtt |
98.35kB |
| Lecture 11 - Random variables as types.mp4 |
207.41MB |
| Lecture 11 - Random variables as types.en.vtt |
87.64kB |
| Lecture 10 - Modeling with stochastic simulation.mp4 |
156.72MB |
| Lecture 10 - Modeling with stochastic simulation.en.vtt |
487.27kB |
| Lecture 9 - Sampling and random variables.mp4 |
179.83MB |
| Lecture 9 - Sampling and random variables.en.vtt |
94.69kB |
| Lecture 8 - Principal Component Analysis.mp4 |
197.45MB |
| Lecture 8 - Principal Component Analysis.en.vtt |
91.51kB |
| Lecture 7 - Structure.mp4 |
187.57MB |
| Lecture 7 - Structure.en.vtt |
90.17kB |
| Lecture 6 - Dynamic Programming and Seam Carving.mp4 |
152.26MB |
| Lecture 6 - Dynamic Programming and Seam Carving.en.vtt |
105.24kB |
| Lecture 5 - Inverses and Newton method.mp4 |
213.25MB |
| Lecture 5 - Inverses and Newton method.en.vtt |
99.43kB |
| Lecture 4 - Transformations 2 - Composability and Linearity.mp4 |
224.54MB |
| Lecture 4 - Transformations 2 - Composability and Linearity.en.vtt |
104.53kB |
| Lecture 3 - Transformations & AutoDiff.mp4 |
208.17MB |
| Lecture 3 - Transformations & AutoDiff.en.vtt |
90.85kB |
| Lecture 2 - Transforming Images.mp4 |
241.05MB |
| Lecture 2 - Transforming Images.en.vtt |
92.33kB |
| Lecture 1 - Course Welcome + Intro to Arrays & Images1.mp4 |
234.54MB |
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Type: Course
Metadata:
Tags:
Metadata:
@article{,
title= {MIT OCW 18.S191 Introduction to Computational Thinking (Fall 2022)},
journal= {},
author= {Prof. Alan Edelman and Prof. David P. Sanders and Prof. Charles Leiserson},
year= {},
url= {https://ocw.mit.edu/courses/18-s191-introduction-to-computational-thinking-fall-2022/},
abstract= {This class uses revolutionary programmable interactivity to combine material from three fields creating an engaging, efficient learning solution to prepare students to be sophisticated and intuitive thinkers, programmers, and solution providers for the modern interconnected online world.
Upon completion, students are well trained to be scientific “trilinguals”, seeing and experimenting with mathematics interactively as math is meant to be seen, and ready to participate and contribute to open source development of large projects and ecosystems.
More info: https://computationalthinking.mit.edu/Fall22/},
keywords= {},
terms= {},
license= {CC BY-NC-SA 4.0},
superseded= {}
}
Citation:
Edelman, P. A., Sanders, P. D. P., & Leiserson, P. C.. (2024). MIT OCW 18.S191 Introduction to Computational Thinking (Fall 2022) [Data set]. Academic Torrents. https://academictorrents.com/details/d72ad3cf23be9be6df34240d3ea24b3071003d9e