Instructions were very poor in many cases , Khan Academey is much better source for explanation of concepts

Instrructions on PCA are so Awful , that I decided to drop from the course

pathetic course

A truly amazing course!

The Calculus course from the Mathematics for ML specialisation is a really fun and effective way of learning. I think that it takes lots of skills and hard work to prepare course like that. It starts very gentle so that it's easy for those who haven't done calculus for a long time, but after refresing on the basics, it jumps to more interesting topics to end up in Taylor series for approximations, Lagrange multipliers, the chain rule application for deriving backpropagation algorithm and some basic optimisation algorithms.

All along they way they're showing everything visually, so that we can build intuitions to have confidence in using the math later on, when there are too many dimensions to visualise the function. The exercises are enough to start feeling comfortable with doing calculations by hand, while the programming assignments shows how to do that in code. Really nice bonus are interactive materials where we can really feel what the math and the algorightms are about (it's great for building intuitions).

Extremely well built course. The quality of materials is excellent and practice exercises really help to deepen the understanding. But what I did like the most were programming assignments, where students are asked to implement mathematical equations as python scripts. The reason I liked such assignments so much was that I needed to build a general understanding (and sometimes come up with general solutions on paper) before writing the code. I did not need any background knowledge of python, because I only needed to write arithmetical equations, pretty much using python as a calculator. In that way I had a chance to focus on the subject matter while leaving python do all the calculations. Now, if I screwed up something in my equations, there were tests written for me, where I could check my solution (e.g. presenting visually how well my script did etc.). That really helped the learning process.

Although the course doesn't cover all of the details of a traditional calculus course, it helps you build an understanding of the fundamentals in the language of calculus, as well as some intuition as to where it might be usefully applied in machine learning.

The lecture videos are top notch and overall both instructor do an amazing job in teaching and developing the intuition required to understand the meaning of the tools used in multivariate calculus. The quizzes are strongly related to what's taught and even what's best, the programming assignments (for which is not required any programming ability) show how to use in practice what you learned.

I think the enthusiasm of the instructor is the cherry on top since it makes a huge difference when it comes to delivering the content precisely and effectively.

The course gives an in-depth knowledge of vector calculus and how it used for fitting data by software programs like MATLAB and PYTHON. The course videos themselves may not suffice to complete the course and the tasks. I had to refer to KHAN ACADEMY and other internet resources to understand better the concepts being taught in the course. The assignment questions range from medium to hard type and require additional time and resources to complete them. The Python codes included in the assignments may look strange if you haven't done any courses on Python. Overall, the course meets my expectations, and I strongly recommend it to anyone looking to move to data science careers.

It's great, however if you are hoping that they would teach you to differentiate like teachers in high school then you are in the wrong place. But, if you want to build an intuition about calculus, optimization techniques, neural networks then you are in the right place. Personally, I was good at calculus in school so it was relatively easy for me, but if that's not the case for you I would recommend that you brush up your basic differentiation. Also basic knowledge of python numpy library would be super useful. Also this course will introduce some really scary looking formulas, so don't be intimidated they just look scary. Best of Luck !

A solid course, recommended for those who want a deeper understanding of the math behind machine learning. It is well taught and organized, with many quizzes so students work through problems themselves,

However,

a) don't think for a moment that a six minute video can be absorbed in six minutes, or a quiz can be completed in the suggested time. From my experience, count on taking twice as long

b) there are so many concepts introduced that I needed to refer a number of times to outside resources like Khan Academy or 3 Blue 1 Brown

Overall, a worthwhile course.

D

David and Sam are amazing: The found the right balance between bulding up intuition and mathematical rigor. Also their use of coding labs is spot on: Not too much coding language related complexity that would distract from the real objectives of the course, while not making out of the labs a trivial exercise of code copy/paste.

While I did Multivariate Calculus in depth back in University, that was 30 years ago, and I needed a good refresher before taking on some advanced ML/AI courses. This Maths for ML specialization did hit the spot.

You will need the basics of Calculus in place. You can't just wake up and start Calculus with this course. With that said, the basics covered serve to be a good revision of the calculus. Certain applications such as the Neural Networks have been done hastily as others say on the forums (and I wholeheartedly agree) but then again this is not a course on Machine Learning. still some more examples from the instructors wouldn't hurt :) The exercises are great. Neither too hard nor too tough.

Simply excellent course. The breadth of topics one needs to cover is astounding. I liked the way the topics and ordered, and following a common structure. The best part is the assignments - one really needs to understand every word of what the instructor says to solve it. They are tough in general to anyone who's done their bachelors/masters long time ago. For those who are not used to programming, the assignments can be difficult.

Amazing instructors and well designed course. Definitely a recommendable course to get intuitive knowledge on mathematical concepts that are relevant for machine learning. What I especially loved about it: it neither went too much into annoying and exhausting detail, nor was it simple. If you take this course, take some time to concentrate and get the brain cells running - will be a satisfying and rewarding experience! 11/10!

It took me at least 3 hours every day to understand and absorb the contents. It's that I'm not a native English speaker and I'm almost in the dark about mathmetics which is covered at university. Nevertheless, every step in the course was worth investing. I could know why I, as a would-be developer, should understand and keep mathmetics in my head. I downloaded all videos of this course and I'm gonna repeat them.

This is my first encounter with Multivariate Calculus and surely the course has been extremely helpful beginner-friendly. I recommend investing in practical mathematics courses as this specialization if you are new to machine learning field. You will be equipped with enough math background and should feel confident to enter more technical machine learning/deep learning courses.

A truly fundamental stepping stone!

I learned limit, derivatives and integrals in high school. Afterwards, I took a few calculus lessons at university. However; I have never got a chance to see this theoretical background to put into practice. For this reason, I have never learned the essence of which means is calculus. I wouldn't have gotten a detailed education on this topic anywhere in Turkey. It was crucial for me, thank you for all !

The videos are well designed and are direct in teaching the course material. For those with Calculus experience, it acts as a nice refresher and further expands it through higher dimensions. For those planning to learn more about Machine Learning and data science, the course also bridges mathematical gaps. Overall, I learned a lot and had fun while taking the course.

Awesome course, so much to learn, and all concepts built up from basic, had fun with all assignments and stand-pit like interactive things, really boosted the understanding, i felt that prof. copper's speed of teaching was fast for me persoanlly , i had to pause many times and think what he said, but prof. david's pace was perfect for me, both instructors are great!

Great course to refresh multivariate calculus skills. I remember going through the traditional method of teaching this subject in college. And while taking the college courses many years ago I ways pondered how I would use the theorectical derivations. The methods used by David and Sam really opened my eyes and now I understand how to apply multivavriate calculus.

A beautifully designed course, in which I could strongly settle the principles behind Linear Regression and Neural Networks. It did a wonderful job, filling the gaps I had from some other material I had checked on the web, but that was too technical, from a beginner's point of view. I feel so motivated by this course, that I will finish the specialization!

Such an impressive set of instructors! I loved the enthusiasm at which the material was taught and injections of British humor. Now, this is not an easy course, but one that requires work. Plan on reacquainting yourselves with pencil, paper and practice. So, do the work, repeat videos when required, rely on classmates in the forums and you'll do fine.

Simply brilliant ! Although the exercises might tend to be fairly simplistic, the quality if this course is top-notch. I truly believe it is one of the best material out there to get a grasp on fundamental concepts underpinning machine learning and data science.

I would definitely recommend the entire specialisation to anyone interest in this field.

This is legitimate the best course on coursera. The video production and animations are beyond words. Also the amount of efforts put into quizzes and assignments is clearly visible. They are soo much helpful in understanding and practicing of the concepts taught. I loved doing this course. I wish there were more courses like in this specialization.

Great course about multivariate calculus and its application in machine learning. This completes very well the math side of things with other courses about machine learning, like from Andrew Ng. The instructors are great, the explanations clear and I like very much the code exercises! Can't wait to start the 3rd course of this specialisation.

Highly recommend it for engineering students or even graduates, since some schools in my country do not teach some of these topics and programming in their engineering programs. The discussion accompanied by graphical and interactive tools really helped me understand some of concepts. The quizzes and assessment focus on the important points.

The explanations are very clear and intuitive, the teachers explain very well and give guidelines so that you can do your own analysis and experimentation. The programming exercises are not complex but you must pay attention and take notes. So far both courses (linear algebra and multivariate calculation) are very, very good.