Chevron Left
Back to Machine Learning for Data Analysis

Learner Reviews & Feedback for Machine Learning for Data Analysis by Wesleyan University

322 ratings

About the Course

Are you interested in predicting future outcomes using your data? This course helps you do just that! Machine learning is the process of developing, testing, and applying predictive algorithms to achieve this goal. Make sure to familiarize yourself with course 3 of this specialization before diving into these machine learning concepts. Building on Course 3, which introduces students to integral supervised machine learning concepts, this course will provide an overview of many additional concepts, techniques, and algorithms in machine learning, from basic classification to decision trees and clustering. By completing this course, you will learn how to apply, test, and interpret machine learning algorithms as alternative methods for addressing your research questions....

Top reviews


Oct 4, 2016

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


May 6, 2020

Clear and explanatory approach to the object. Instructors have great teaching transmissibility.

Filter by:

1 - 25 of 67 Reviews for Machine Learning for Data Analysis

By Mukkesh M

May 30, 2019

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)

By Фаткулбаянов Т Р

Feb 7, 2018

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.

By Macarena E

Sep 19, 2017

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.

By Richard C

Mar 1, 2016

Not impressed with the teaching style.

Seems that lectures were being read and not taught.

By Γεώργιος Κ

Jul 4, 2018

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.

By Manoj K

Feb 22, 2016

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.

By Павел Б

Jul 25, 2016

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

By Ruben D S P

Jun 29, 2018

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

By Bruno G C

Oct 5, 2016

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

By Adrielle d C S

Feb 6, 2018

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.

By Kostas P

May 7, 2020

Clear and explanatory approach to the object. Instructors have great teaching transmissibility.

By Edward M

Jun 25, 2016

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

By Dmitry B

Jan 25, 2018

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

By Deleted A

Jun 28, 2016

Option of learning both SAS and Python is great!

By Edita G

Nov 30, 2020

Great course about machine learning methods

By Genara P

Apr 6, 2017

Excellet! I highly recommend!

By Jinbo C

Jan 7, 2017

easy to capture the concept

By Deleted A

Sep 7, 2016

short vedios and good ma

By thoai n

Dec 19, 2019

This is good course

By Karthik z

Nov 9, 2017

Well structured .

By Yaman S

Feb 28, 2016

Excellent course

By Santhosh K J

Feb 25, 2019



Jun 6, 2022

Great Learning


Jul 10, 2020

Good to learn

By Смирнов В Г

Feb 26, 2018

Great course!