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I didn't find an overview of what will be covered in the course and who the intended target audience is. Did anybody find some infos about this course?

whymauri 6y ago
Here's details from a departmental e-mail from mid-July (likely outdated). ----- Prerequisites: Students should have a good familiarity with any popular programming language such as Python or R, and ideally have taken or are taking a math class such as 18.02 (multivariable calc). ----- Contents: General-purpose Computing, Data manipulation, abstraction, optimization, machine learning, performance, Random walks, graphs, automatic differentiation, differential equations ----- Format: We plan to experiment each week with * 30 minutes of asynchronous lecture (the story) * Five 6-minute quick video how-tos * 30 minutes of live, engaging lecture with nongraded quiz questions to test understanding * 30+ minutes of break-out sessions, help, questions and answers, or discussion * (Mostly) weekly problem sets * Letter grading typical of the Fall 2020 semester * Freshmen are advised to be aware of credit limits and the process to petition
- UncleOxidant 6y ago
  After watching last week's convolutions lecture it seems like 30 minutes is too short. 45 minutes would probably be better. I could probably even listen to Sanderson for an hour.
ViralBShah 6y ago
The course is really for anyone who has a curiosity in applying computational science to solving problems. If you are motivated by Victor's essay on "What can a technologist do about Climate change" (http://worrydream.com/ClimateChange/ http://worrydream.com/ClimateChange/) or Alan Edelman's "A programming language to heal the planet" (https://www.ted.com/talks/alan_edelman_a_programming_language_to_heal_the_planet_together_julia https://www.ted.com/talks/alan_edelman_a_programming_languag...), then you should follow this class. It does many things differently than the traditional way of teaching such a course. Specifically the emphasis on applications that matter today (epidemiology, climate change, etc.) are a key part of the course, where a more traditional approach may have been to cover a series of numerical methods.
- igotsideas 6y ago
  Just read "What can a technologist do about Climate change.” Thank you for posting that. Has me wanting to change what I’m currently working on.

whymauri 6y ago

Here's details from a departmental e-mail from mid-July (likely outdated). ----- Prerequisites: Students should have a good familiarity with any popular programming language such as Python or R, and ideally have taken or are taking a math class such as 18.02 (multivariable calc). ----- Contents: General-purpose Computing, Data manipulation, abstraction, optimization, machine learning, performance, Random walks, graphs, automatic differentiation, differential equations ----- Format: We plan to experiment each week with * 30 minutes of asynchronous lecture (the story) * Five 6-minute quick video how-tos * 30 minutes of live, engaging lecture with nongraded quiz questions to test understanding * 30+ minutes of break-out sessions, help, questions and answers, or discussion * (Mostly) weekly problem sets * Letter grading typical of the Fall 2020 semester * Freshmen are advised to be aware of credit limits and the process to petition

UncleOxidant 6y ago
After watching last week's convolutions lecture it seems like 30 minutes is too short. 45 minutes would probably be better. I could probably even listen to Sanderson for an hour.

ViralBShah 6y ago

The course is really for anyone who has a curiosity in applying computational science to solving problems. If you are motivated by Victor's essay on "What can a technologist do about Climate change" (http://worrydream.com/ClimateChange/ http://worrydream.com/ClimateChange/) or Alan Edelman's "A programming language to heal the planet" (https://www.ted.com/talks/alan_edelman_a_programming_language_to_heal_the_planet_together_julia https://www.ted.com/talks/alan_edelman_a_programming_languag...), then you should follow this class. It does many things differently than the traditional way of teaching such a course. Specifically the emphasis on applications that matter today (epidemiology, climate change, etc.) are a key part of the course, where a more traditional approach may have been to cover a series of numerical methods.

igotsideas 6y ago
Just read "What can a technologist do about Climate change.” Thank you for posting that. Has me wanting to change what I’m currently working on.