Master linear algebra: theory and implementation in code (Udemy.com)

I was initially struggling to get the intuition of linear algebra for machine learning concepts and this course really helped me out to do so. Specially the visualisation and the foundation of linear algebra.

I just completed this course, and it is easily one of the best linear algebra resources out there. Mike X Cohen has a fantastic teaching style that focuses heavily on geometric intuition rather than just boring, manual arithmetic. Learning how to implement these concepts directly in code (Python/MATLAB) completely changed how I view math. The sections on eigendecomposition and SVD were incredibly clear and gave me the exact foundation I need for machine learning and data science. The coding challenges were challenging but highly rewarding. Highly recommended for anyone who wants to actually understand linear algebra instead of just memorizing formulas!

I already knew that Mike's books are clear and useful. To be honest, I thought his online classes might just be a recap of those books, and that would have been good value. In fact, the Udemy classes offer a whole new perspective. So I am delighted to be able to approach the topic from two angles. Mike's presentation (both written and spoken) is on par with the best university courses that I have taken. 5/5

I have started the course 3 months ago, and I'm still in section 11, I think that every part in the course is interesting, informative, conceptually clear, and relatable to other concepts/fields! Mainly, I registered because I wanted to deeply know/understand eigen-decomposition and SVD, and I noticed that almost every section builds up for this goal, and I'm super-duper excited to start sections 12, 13 and 14! Thank you Dr. Mike

good for learning linear algebra

Very clearly explains the core concepts necessary for a deep understannding of linalg. I love the simplicity of the slides, helps stay focused and is easy on the eyes.

Wow! When I was in secondary school, I spent countless hours solving matrix problems without really understanding their real-world applications. This feels like a true aha moment for me now. Thank you very much.

This course is a great way to start or extend ones current knowledge and the best I found so far when it comes to online learning. The explanations are clear and consice and the code challenges help to memorize and apply the concepts explained. However, for some parts towards the end (e.g. quadratic form) I wished there would be one or two real world application in the code challenges (e.g. where in a certain AI algorithm is concept X used). So to get most out of this course, I really recommend to find application yourself (ask your favourite LLM) and then try to code the algorithm from scratch.

This is by far the best Linear Algebra course I’ve ever seen. Mike explains every concept with incredible clarity, breaking down even the most complex ideas into simple, intuitive steps. His teaching is hyper-detailed yet easy to follow. Truly a masterpiece for anyone who wants to really understand linear algebra.

Since linear algebra is fundamental to machine learning, and the instructor’s teaching style in the ANTS courses appealed to me, I decided to enroll. Here are my thoughts: 1. The combination of theoretical knowledge and practical coding is highly effective and greatly enhances the understanding of core concepts. 2. The instructor successfully bridges the gap between linear algebra theory and its real-world applications. The examples provided are highly relevant to my research, particularly in time series analysis. 3. The video lengths are well-balanced, including both short and longer segments. The shorter videos are easy to complete and provide a sense of accomplishment, which motivates continued learning. 4. The course covers many key concepts in machine learning applications, and the content is very well-organized. Although I had studied linear algebra previously, I still found this course incredibly valuable.