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The code in this repo is considerably different to what is mentioned within the videos, with the video code sometimes having more detail and this repo sometimes having more detail. For a stark example please compare this repo's factorisation code against the factorisation video, although this issue is present throughout the course. I appreciate wanting to update this repo, but it would be good if the course linked to a specific commit/tag. Also, I'd expect this repo to be ahead of the video and therefore not missing any content.

Hi there,

Just followed the course on https://juliaacademy.com and it was great, thanks for all the effort of building this!!

Most content and video is really good and at a good level in my opinion. I believe there should be a bit more reviews, but this is not crucial.

However, I found the last video on Factorization really detailed, long, and needed a strong background on Linear Algebra. It clearly outweighs other subjects, and I'm not sure this is a good thing:

• It's hard for non specialist, in another level of other subjects.
• It makes feel that Julia is designed for LinearAlgebra, which is probably a bit true, but do you want to pass this message?

It would be great if you added this repository also here...

Factorizations video seems to be outdated. The examples given in the video does not match notebook and also some of the function are not working anymore.

lufact() & lu(x, Val{false}) seems to be no more supported, but in the MIT documentation it is not indicated.
MIT documentation

A little confused on why the assert is failing for me in the screenshot below. I believe it's due to floating point precision issues, but I'm curious how any notebook would pass if that's the case. To preface, I will also mention the assert for the eigenvalues passes fine.

If I use the Diagonal constructor or diagm function I (seemingly) get the same result as the expected answer, but the assert still fails. Interestingly A_diag == A_diag2 returns true. Checking their types and using isdiag() suggests it should be equivalent? Even using the approximation comparison ≈ gives a false result.

Furthermore, it doesn't seem to be a problem for the lowertri comparison. It passes just fine.

Doing a subtraction I see there is difference in the final calculation so it must be a precision issue but then I figured it'd fail for everyone. It passes fine for the lowertri because they're just integers.

I think you mistakenly overwrote the Strings chapter with a copy of the Getting Started Chapter

Just in case it is useful, using your code in: https://github.com/JuliaAcademy/Introduction-to-Julia/blob/main/9%20-%20Julia%20is%20fast.ipynb, I added a couple of small bits to benchmark R.

See the gist: https://gist.github.com/jmcastagnetto/fce3cad5856517250ad1cdc468d49865

Well, this seemed to be a great course (even though I do not have the mathematics background to understand the last two parts), but throughout it, I had a problem hearing the two people giving out lectures. In the case of the guy, it was mollified a great deal by the fact that he used YouTube which allows me to get captioning. The woman, however, used something else, and without captioning, I found myself having to again and again back it up to try to understand what was being said. I did like that the platform she used gave a place for me to make notes, but I found my tribulations with hearing to make it quite not worth it. Now, these are most likely not issues for your average student, but I am a 60 year old man with a certain degree of hearing loss. I would suggest that you give caption capability, if possible, to the lady's lectures. I don't have any idea how many people it might help, but it certainly would have made this entire course a LOT easier for me! Thank you.

at the end of the .ipynb file there are exercises that say to click on "validate" at the top when finished. where is "validate" that I click? Is it within the jupyter notebook when I'm playing with the .ipynb file? I can't figure out how to validate

In 4 - Conditionals.ipynb the first example is FizzBuzz but the text following this on ternary operators talks as if it if preceded by a simpler if / else block. The version in the video flows much better (see #6 I guess).

When the @Assert is called at 11.2, it will not approve the result.
That is, where we see:

@assert A_diag ==  [-128.493    0.0      0.0      0.0       0.0;
             0.0    -55.8878   0.0      0.0       0.0;
             0.0      0.0     42.7522   0.0       0.0;
             0.0      0.0      0.0     87.1611    0.0;
             0.0      0.0      0.0      0.0     542.468] 

Will return false. The reason is this expression does not consider the minor terms of the floats.
When I make the following:

A_diag - [-128.493    0.0      0.0      0.0       0.0;
             0.0    -55.8878   0.0      0.0       0.0;
             0.0      0.0     42.7522   0.0       0.0;
             0.0      0.0      0.0     87.1611    0.0;
             0.0      0.0      0.0      0.0     542.468] 

The result is:

5×5 Matrix{Float64}:
 -0.000227648  0.0          0.0         0.0          0.0
  0.0          1.54469e-5   0.0         0.0          0.0
  0.0          0.0         -3.27207e-5  0.0          0.0
  0.0          0.0          0.0         1.47751e-5   0.0
  0.0          0.0          0.0         0.0         -0.000269853

So it is impossible to correctly answer the exercise.