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From a tooling perspective look into Pluto.jl
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AppSignal
AppSignal knows why the f*#k it crashed. Stop vibe-debugging. Every exception, every backtrace, grouped so you see patterns, not noise.
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I like what little I have read so far in Statistics with Julia. There is also the recent MIT course Intro to Computational Thinking that uses Pluto and includes statistics and probability at a moderately advanced level.
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6S083
Materials for MIT 6.S083 / 18.S190: Computational thinking with Julia + application to the COVID-19 pandemic
The Syllabus and problems are MIT / CC BY-NC-SA licensed, so you are actually allowed to use it pretty much as-is. https://github.com/mitmath/6S083/blob/master/LICENSE.md
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I am teaching a master course on optimization in Julia. You can find the material here and a small blog post I have written about this here.
Related posts
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A data scientist's journey building a B2B data product with Julia and Pluto
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What have you "washed your hands of" in Python?
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The counter-intuitive rise of Python in scientific computing
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Julia Frameworks to Create Desktop GUI’s and Web Apps
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Simple, reactive programming environment for the Julia Language