Calculus with Julia

There's no language I'd want to teach (applied) math in more than Julia. Lean is obviously kind for anything involving a proof, but for teaching anything with linear algebra involved the syntax alone is enough of a reason to prefer Julia.

Optimization, specifically the kind that JuMP tackles, is another field where teaching is probably easier in Julia than any other language

The stated goal is to introduce math concept without computer language or use being a burden. But then I took a quick glimpse at the derivative chapter, and at the top there is "using Sympy", so you don't only use Julia but also sympy. Mathematica and Matlab are the alternative in a university setting in which free licenses for students are available, with strong numerical and symbolic capabilities . I think Julia is a lovely language, but perhaps Julia + Sympy is a difficult proposal for attaining the stated goal. S.Rational(1) + S.Rational(1,3) type of things from sympy are hard to digest.

Edited: Added: I think if you love teaching calculus using Julia then the passion you transmit might compensate for the additional burden of using Julia plus SymPy.

Julia should have been adopted for numerical computation and ML by places like Google.

They went with python and it's just too general and verbose.

I'm just picking up Julia for my DSP course at uni, and came across this nice intro. It's very well-paced for a first introduction to programming!

Great resource. Julia is one of the best PLs coming out of MIT.

Anyone using Julia outside university settings? I tried to get into it around 5 years ago, and it felt good, was conceptually interesting, but haven't seen any adoption or talks anywhere outside the academia

What's the developer experience like with Julia nowadays? Any IDE / static analysis / debugger options that doesn't feel like experimental?

I would love to see things flipped around: Teach calculus as code, and work in the concepts after. This looks like a conventional approach with code tacked on after. What I see here: concept -> math notation -> code. I'd go: code -> concept -> math notation.

20 quadrillion ants is about 2.5 million ants per human - pretty insane to think about. I thought I had a grasp on their abundance, but I'd still probably have underestimated their numbers by an order of magnitude previously.

We still mog them on mass and volume though. 2.5 million of the average ant would only make the size of a human leg, if that.

Seems like a fun way to teach basic calculus. I think a notebook style, maybe a Julia equivalent of Jupyter, would work better.

From my quick skim, the book is quite light on proofs, which I think is a big mistake for intro calculus classes. Proofs are usually what you need to get a solid feel for the material, at least at the start. Developing intuition on how things work by playing around with Julia, and using that to inform exploration to come up with theorems, and using that data to help develop a proof would be a more interesting approach. Maybe they do this in later chapters. For example, when teaching eulers method for integrating the ODE, visually graphing the error compared to the actual as step size changes could give the reader some intuition about the order of the method.

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