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I passed the "Machine Learning" course by Andrew NG in 2019, and I took this course as a part of my specialization. So this course looks like a simplified and cut version of its predecessor. Most of the Lab files are not downloadable as PDFs, so, after the course finishes - you can't have that data with you. Quizzes are so much oversimplified, like 2 questions, I think in the previous course it was much harder and it took me time to learn things. This review is a bit chaotic, I am sorry for that. I know that Andrew Ng is a great teacher, and in the previous course, he gave so much more valuable information and the simplification of that course makes me sad.

I found it hard to follow and confusing. By the time, we finally got to do some hands on work, I felt totally unprepared. Could have done more to explain the python code or to work the student slowly into the coding assignment. All in all, I can not say if it a good specialization, yet after the first course I am looking for something more hands on and beginner friendly. I am a bit disappointed as I have heard only stellar things about this course.

The quizzes and labs are too easy to be of value, with many of the quiz answers literally being written in the image displayed above the question, and labs basically just require you to translate a specific equation into Python.

There isn't really a way to tell if I understand the content or not, I recommend you do not pay for this course.

I cant seem to access my optional lab materials even when i have not exceeded deadlines and dont have have an outstanding payment. it keeps telling me session timed out and keep repeating the same when i click the reopen button. i really enjoyed the course but i didnt like the fact that i couldnt access my optional lab material.

Very, very very basic. If you're looking to freshen up some concepts, this is not for you. I wouldn't even recommend this course to CS students as the course avoids at all costs at explaining the maths behind machine learning.

Too much content per week. You learn the basics of the formulas, but it is difficult to digest all the information in only three weeks and with practical exercises in Python if you have no practice in the language.

The logistic regression part really needs rework, It is not so clear for an engineer student and is very confusing at some parts

Great course if you know how to program, but you really need a python background to appreciate it.

quite too basics...too few practical exercise, just scratching the surface of ML

Impossible to do the exercises if you don't pay. The course is interesting.

Very nice and helpful for my next career steps.

too theoretical, not much hands on learning

i want to see my name on this certeficate

no math exercises to practice

Oversimplified

not good

Me paso lo mismo con el curso anterior y es que si no realizas los laboratorios aunque hayas aprobado todo y a pesar de que los test te dan como aprobados dicen que no apruebas y que quedas en 0%, es algo como reiterativo con coursera asi que me rindo, no continuo intentando sacarme certificados por acá

Mostly I was inundated with Nagware after ever short video segment, only to discover that Machine Learning learning was not even introduced. Wasted much time on trivialities like linear regression. I never learned anything about Machine Learning, per se.

Although i can see that the next course is included in my learning program but i can not progress in it because the system keeps on asking me to pay for the course.

I'm very excited to move to the next level of this field i after i took this foundational courses. It is well organized and very engaging course.

This course is not for beginners. If you are not already familiar with programming and advanced math don't waste your time.

They don't provide slides, so there's not way to take notes or go back and reference material.

Too much math, not enough practical code examples