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

This course is great. It cuts out a lot of the unnecessary noise and problems in a traditional calculus class keeping the points needed for DS and ML. I have done multiple calculus courses in college already and so this has been a great refresher. Straight to the point, well explained all without the semester worth of unnecessary info with actual relevant applications. Great course

I took this class as a refresher for a grad school class on math for machine learning. I really only needed the Calc 1 section, but TLP covered the topics so well I just kept learning. Likely to take some of the other courses TLP offers for content bolstering for grad school or for extending my learning around topics of interest not covered in class.

It was really good for me to learn how the lecture explained the basics of calculus in detail how things are proven and what kinds of approaches are used. However, for certain formulas, like the Taylor series, we had to accept them without proof. Since that topic wasn't covered in this lecture, we just had to move on, which was a bit unfortunate. Aside from that, the explanations were very detailed, which I liked.

I am currently a data scientist. I graduated from college almost 20 years ago and I realized that I need a refresher on calculus as I try to wrap my head around the latest developments in deep learning. This course was perfect! I feel much more confident in my math literacy and I have already purchased the next course (on linear algebra). Thank you Lazy Programmer!

A great course to get a refresher on calculus for deep learning. The author gives very intuitive explanations of complex topics without neglecting the rigorous part of mathematics. It would be good, in my opinion, if there were more exercises in the course, especially in the last section on calculus 3. But overall, it is a great course for everybody who remembered something from high school mathematics :)

I have taken this course and have spent lot of hrs and can tell that, this 12 hrs course will take lot of time to understand and complete (150 hrs). This can be done if we have 100% free time for 4 weeks. Good thing is if you have little idea of Calculus and we flow what is being taught, this course will make us ready to understand ML. Having said that the instructor should again go back and try to minimize the un-necessary or repetitive content.

This was great! I literally remembered nothing about calculus (or most university math for that matter) and this course made it so understandable for beginners. I was able to follow along and as I go back through the course to brush up on things, I know I'll be an expert in no time. Thank you!!!

Very well-detailed and encouraging course. Just completed over half the course and I can say it's the best math course I have encountered. The way Lazy Programmer explains the topics and logic of the steps in very simple terms is what I liked very much about it. And structuring the topics in this course is the main backbone of the course which makes it thrilling and engaging to learn more.

I really wish this course was available three years before its release when I started going down the Lazy Programmer rabbit hole. Having taken over 15 of his courses to date, there were many times when I felt lost during his lectures because I had forgotten most of my undergrad calculus. The course boils Calculus 1, 2 and 3 down to the essentials most relevant to machine learning and deep learning. A lot of time, however, is also spent on theorem proofs, which I presume are more for interest than necessity. Calculus has been around for about 400 years now, so I think we can safely take Newton and Leibniz at their word. I was somewhat disappointed that the lectures on Taylor expansions are only available with VIP access. This discrepancy between regular Udemy students and VIP students is most annoying, to be honest. Nonetheless, I hope Lazy Programmer continues this math foundations series into linear algebra, probability and statistics.

This class has been challenging as I haven't taken a college math class since the early 90's (and it wasn't Calculus). But, I've been able to follow the instructor and understand the material (by taking tons of notes and doing the exercises). Knowing that these are the concepts needed to understand future ML material; the instructor is excellent at putting the Calculus into perspective.