The course was indeed pretty interesting, I've learned a lot of new things (and got to learn how to do a little bit of coding using Python). The only thing I would recommend is to add some more datasets, because even though it's pretty easy to find some datasets on the Internet, I think 3 out of 5 suggested datasets were extremely difficult to figure out and were much more complex than the other two.

Not impressed with the teaching style.

Seems that lectures were being read and not taught.

A must to do introductory course. I will never regrett taking that valuable course but I have to say that some improvements would make it much better. The theoretical background is too short and the proffesors seem to spend more time to describe simple functions like saying put there an ('underscore', 'parenthesis') than seting the reasons of doing that and what are the targets of the programmes. Any way all of these problems and maybe some more are not a reason for someone who wants to start machine learning to not participate in that course especially if he is a pythonist.

A good introduction to Machine Learning. Makes me curious to know about the methods that are available outside of this course. Great material as usual.

Update After actually studying Machine Learning for months: A pretty intro to the world of ML. After learning the math behind it and other algorithms, I can say that this specialization is pretty much just the Statistical interpretations of your analysis (explained with the implementation of some powerful yet basic algorithms without really getting into the Hard Core math behind it)

Excelente curso. Explicações didáticas com exemplos reais implementados e detalhados em python. Descrição muito boa das aplicações das técnicas apresentadas bem como de suas limitações. Parabéns para as professoras por esse excelente curso e muito obrigada por nos disponibilizar este trabalho maravilhoso no Coursera.

I really liked this course. Concepts well explained. I was hoping for more practical exercises on different types of data sets along with how to improve model accuracy in various algorithm taught. concept such as pruning etc. were missing. But I am sure in future, we will have more on it. Thanks Professor.

I enjoyed this course a lot. It's easy and I've learnt what I need to apply the machine learning techniques. Easy and simple. You don't need to be a mathematician.

It is very interesting, helpful, useful and wonderful course. Everybody who interesting in statistic must surely learn this course.

Great classes. It is the beginning to machine learning, and you can try more classes about it. You can find many job about it.

Very good course. I recommend to anyone who's interested in data analysis and machine learning.

Good introduction with python example for famous algorithm such as random forest and k-mean

There is some problems because of changes both in SAS and Python after creating the course

Option of learning both SAS and Python is great!

Excellet! I highly recommend!

easy to capture the concept

short vedios and good ma

This is good course

Well structured .

Excellent course

GREAT KNOWLEDGE

Great course!

Great Class!

все супер

Noiiice!

Good!