This course uses python and pytorch and will have you building something that can tell 30+ breeds of cats and dogs apart in the first lesson. While the old course from Andrew ng you mentioned starts with theory and by the end gets to doing something useful, the fastai course starts with best practices and moves into the underlying theory later.
Also Andrew Ng has a newer deeplaearning.ai course on coursera that is all python and doesn’t do Octave.
https://news.ycombinator.com/item?id=21301117
I derive the normal equations in just two lines of matrix algebra, never use calculus, assume nothing about probability.
The normal equations are plenty simple to program in nearly any programming language. For the linear algebra, just use LINPACK or for a really simple approach just write your own Gauss elimination linear equations solver.