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.

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)

GREAT KNOWLEDGE

Absolutely unbalanced course. Course has 4 different topics, but it does not explain well non of them. In reality whole course should be dedicated for at least one of provided topics.

It´s a good course but it does not goes deep enough in the examples and techniques.

Learned some really useful ML models.

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.

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

все супер

Unfirtunately superficial and outdated view on the subject.

Great course!

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.

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

More Implementation oriented and less math

also contains distracting background videos when explaining important concepts

Well structured .

The material is good but the functions should have been explained in more detail. There is kind of repetition of same thing. It should have given some more examples and changes in code to explain the different types of ways to apply same algorithm.

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 goes over and over about the adolescent examples, which makes it annoying. The quality and production of the video is bad. Why to use moving scenes in the background (like the horses or the highway)? That's distractive and takes the focus of the content, better to use a blackboard.

Good!

I definitely appreciate this information on Machine Learning. And from an outsider perspective would say it is quite clear - when I put it into practice will see how it goes. I do like the video format and will say that through out the course the instructor

Excellet! I highly recommend!

Very good. I enjoyed doing it and learned a lot.

I would have liked that it had included r as one of the softwares.

easy to capture the concept

Excellent introductory course on machine learning focusing on simple linear and multiple regression, lasso regression and k-means clustering. A background in Python programming is useful but not required as the instructors discuss the techniques with annotated code examples.

Course could be better