Towards the end, you see that the lecturers and the Team lost their motivation for a bit. Explanations are done very quickly and the exercises lack proper programming. The last one for example can't be passed if you write the functions in two different cells (as it is displayed in the workbook when you start), you need to copy them to one cell. This is really badly designed.

The first few weeks were a great introduction to derivatives, but the further it got the more the content seemed rushed and the exercises lazy. I will now go back and read secondary literature to really understand those parts, and not just calculate derivatives over and over. Samuel was a fantastic instructor though, kudos!

It's one of the toughest things that I've done in my life. The content is really interesting and applicable, but at times you might get stuck with quizzes or assignments because there is not enough guidance given. All in all, I'd recommend this course to everyone working in analytics.

A quick short introduction to multivariate calculus and few machine learning techniques, but without much detail mathematical proofs for some ideas. It's a maybe good introductory course for beginners of calculus. Not recommended for learns who seek for details of ideas.

Weeks 1-3 (4) were pretty nice; weeks 5 and 6 were terrible. The harder the topics, the less explanation was given, the pacing by the end was atrocious and course delves into statistical topics while it probably could've dedicated these weeks to other relevant topics.

The last 2 modules have very promising content, yet the instructor did not do well enough. I found myself totally lost in the confusing explanation of David, although I've already have experience in Multivar Calc and take this course just as a refresher.

Weeks 5 and 6 could be greatly improved in terms of clarity and quality of the explanations. More solved examples would be very helpful and appreciated. On the other hand, weeks 1 to 4 met the expectations and were very ilustrating.

Such a easy course, if you totally a novice in multi-variables calculus, you could take this course, Whereas, if you are familiar with calculus, it will be quite easy for you.

I hope more programming assignment about Machine Learning

the connection seemed poor between weekly targets. it was super easy at first and became very difficult at last, honestly i do not think this is designed for students with no relavant foundations in math or machine learning.

The instructor for this course actually tried to explain the concepts, unlike the other two courses in this specialization. However, no one is available to answer questions.

I feel that the course was too fast paced. I had to constantly refer to many other website like khan academy and 3b1b. The course skipped many details and lacked intuition.

You will get some intuition of mathematics used in Machine Learning as well as there will be less fear in doing ML courses if you would complete this course.

Course would be prefect if there would not be technical issues with opening notebooks. It slows me down by 1 week. But content was really relevant to ML.

Overall average course. Not that much good as expected because of David Dye. He was teaching very poor in this course as compared to course-1.

Last 2 weeks completely diverged. Failed to converge. I wish content was more elaborate.First course of this specialization was far better.

Role of discussion forum is very less. Please improve on that to have healthy participation. Otherwise, course content is really good.

first 4 weeks were good. Starting from week 5 course explanation was bad. Was required to watch other videos.

Lecture videos are quite sparse, and the quizzes test things that they don't teach you in the lecture

A bit fast paced, could be much more beneficial with some added explanations.

Too fast to understand what instructors says.. but lecture contents are good

The basics is explained so light, that you wonder if it is of any use.

It was a lot of fun at points. Would recommend to anyone else.

Strong disconnect between teaching videos and assignments.

Course would enhanced if pdf's of lectures were provided.

There is a decent space for course improvement.