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

4.2
stars
298 ratings
64 reviews

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

KP
May 6, 2020

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

BC
Oct 4, 2016

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

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51 - 63 of 63 Reviews for Machine Learning for Data Analysis

By Susanne W B

Mar 1, 2016

It was okay for an introduction to the methods, but I would have liked to learn about them in more details, i.e. the course was too short.

By Monika K

Apr 29, 2016

This level of detail was good for easier statistical concepts but there are much better courses on Coursera for Machine Learning

By Ponciano R

Jan 23, 2019

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

By Xiaoyang G

Apr 15, 2016

It's not an intro class. But you can practice a lot if you know something.

By Tristan B

Mar 1, 2016

Not deep enough on diagnostic and interpretation

By Karthick K

Dec 12, 2016

Course could be better

By Teo S

Oct 31, 2016

Personally felt this course have a lot more potential. The explanations in the lectures felt very robotic especially when describing the scripts. At times the lectures slides felt like displaying the subtitles and reading off them. A lot more diagrams could have been illustrated for explanations. I have to watch other videos in youtube to get a better grasp of the concepts.

Good thing is that this is an introductory course, and the codes are given.

By Vanessa Q M

Sep 4, 2017

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.

By Остроухов М Н

Mar 6, 2018

Unfirtunately superficial and outdated view on the subject.

By THEODOSIOS M A

Sep 3, 2016

Not good at all.We see different processes without anyone making clear the reason why we should apply this processes ,under which conditions and what is the question that we have to answer when we apply these processes.The only good is that we get into some new terms and see new things.I could say that for me,it wouldn't make such a difference if it wasn't in this specialization.

By Aurimas D

Feb 1, 2019

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.

By Liuyijie

Jun 15, 2016

Actually i want rate 0, as the instruction for the installation of new tools are quite vague and misleading

By karishma d

Oct 20, 2020

Most horrible course. Material are not enough and plus projects are hardly curated