Jan 17, 2017
excellent course. Be prepared to learn a lot if you work hard and don't give up if you think it is hard, just continue thinking, and interact with other students and tutors + Google and Stackoverflow!
Mar 01, 2017
Issues of every stage of the construction of learning machine model, as well as issues with several different machine learning methods are well and in fine yet very understandable detail explained.
par Peter G•
Feb 28, 2016
Absolutely useless random un-explained list of facts and advices that is thrown to a learner without any attempt to give a systematic approach. Pure waste of time and effort. Can only be suitable to those, who already know the subject well and can use some additional facts that are randomly presented in this "course".
par Norman B•
Feb 07, 2016
This is too high level for a machine learning course. You don't exactly learn a lot about the techniques just how to use them and name them out if you're having a conversation with a person. My least favorite course in the series
par Michael R•
Jan 19, 2016
lecture can be really unclear sometimes because lecturer breezes through the actual implementation of training/predicting: "use x, y, and z [underlines some stuff on screen]" and you're done
Also lots of mistakes/typos in lecture and quizzes
par Agatha L•
Jan 23, 2018
I was disappointed with this course. For better or worse ML is a part of data science and, in this course, the instructional depth was lacking. The lectures provided examples of how to implement a few ML algorithms in R, with very little actual instruction on the intricacies of these algorithms, theoretical foundations etc. Taking the course I felt somewhat cheated (a google search would have done the job of the class), and frustrated with various little bugs in Quiz/Assignment content.
par Haolei F•
Mar 13, 2016
Need to get more in-depth
par Y. B•
Feb 06, 2016
incomplete and not clear. extremely disappointed.
par Michael R•
Oct 03, 2019
It's a mediocre intro to some machine learning tools. I think the course materials could be drastically improved.
par Stephen E•
Jun 27, 2016
To be honest I don't think this is worth the money.
par Etienne B•
Mar 01, 2016
Cannot take the exam, I have to pay... wtf... I will probably pay at the end, but I want to take the class first. Without certificate I cannot prove I took the course.
par yi s•
Jul 19, 2016
too general no depth, not recommended for science or engineering degree holders
par Stephane T•
Jan 31, 2016
Too much surface, not enough depth.
par Thomas H•
Feb 08, 2016
Project description versus requirements were terrible, not sure if the new Coursera format played a role in the issues or not. Quite a few of the homework items require guessing as the answers don't align to the results of the latest tools they have you use. If the first class or three in the series was like this I wouldn't have taken the courses.
par Robert O•
Apr 06, 2016
Very little depth. I don't recommend this if you don't already have background in statistics or R. I really didn't learn anything. I mostly just gamed the quizzes and projects.
par Gianluca M•
Oct 20, 2016
Gosh I hated hated hated this course. Nothing to learn here. You will just be given lots of names with no explanation whatsoever.
I often felt really angry at the teacher because of the way he would introduce entire prediction models without explaining anything about them. Also, I really didn't like the fact that the course is centered on caret, a "shortcut" package to do stuff fast. Before doing things fast I need to know what I am doing! Finally, the quizzes and assignments are completely disconnected from the courses.
The worst course I have ever taken on coursera.
par Jo S•
Feb 04, 2016
Poor compared with some of the others on this specialisation. The lectures are too fast and high level, with no allowance given for people who are unfamiliar with this area and attempting to learn it.
par Danielle S•
Mar 22, 2016
Material is very high level. No ppt's are given, so all links presented in the video's cannot be viewed.
Quizzes are based upon old packages, so incorrect answers are provided.
No replies at discussion board from TA"s or instructors.