Math 0-1: Linear Algebra for Data Science & Machine Learning (Udemy.com)

For me, as someone who is changing careers and entering the world of data and ML, these lessons are an important foundation for understanding the process behind the formulas — how to get there and what they are for. But I admit that these classes are tiring. In my view, they are important, but keeping the motivation to continue is not easy. Many times I get lost in the professor’s fast reasoning. He wants to show everything, but in the middle of the process he skips steps and says “do this at home as an exercise”. Obviously, mathematics is “knowing the rules of the game and playing over and over until you become a professional”, but when we’re trying to follow a line of reasoning, it becomes confusing while we’re watching the video. In my case, watching one of his videos is never just the duration of the video — it’s much longer — and I use AI to help me organise the professor’s reasoning. Because of that, for me it has been slow and very demanding. The professor is fantastic, and you can tell he loves what he does. I will continue.

It actually did not match because i firstly want to learn linear algebra and then ML but this course if for those who find ML a bit hard and want to review Linear Algebra. But overall it is good.

Yes, it not only gives the contents necessary as a building block for more advanced machine learning concepts, but also give the intuition and the applications.

Excellent refresher course for linear algebra. Covers some advanced topics as well, which are waived in other classes.

Its an interesting course. I learned a lot and it clarified many of my confusions about linear algebra.

So far for section one true and great advices. I want admit my ego has held me back plenty of times concerning learning.

I took this course mostly as a refresher. I found the explanations clear. The content is pretty complete and targeted on the ML use case.

I only felt confused when taking other courses where lecturer usually skiped the matrices' calculation detail. But this course will guide you to break down matrices' calculation step by step. For example, in lecture 85, this course will tell you how to put the sum into the matrix.

So far.... very good

Very beginner-friendly course. Not too long, and not too short. Great, digestible content. Would have liked to hear a bit more about the deep learning applications for LLMs and diffusion models!