VG
Nov 9, 2020
Great introduction to ML.Demands focus and hard work. Forces one to review earlier courses - Statistical Inference, regression models, EDA.Leaves lots of appetite for additional knowledge and skills.
JC
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!
By Ann B
•Sep 6, 2017
Good class to get the basics of Practical Machine Learning. This course is best taken as a part of the data science series from John Hopkins.
By Gabriela C
•Dec 14, 2020
It's harder than the previous one. it would be nice to update some the quizzes as they are based on older versions of R Studio libraies.
By Hernan S
•Dec 13, 2016
The quiz should be constructed in a way that depends less on the version of the libraries used. The rest of course was excellent.
By Jakub W
•Sep 24, 2018
Vary practical approach, almost no theory or in-depth explanation of the subject, but a lot of focus on applying ML in practice
By Md F A
•Aug 14, 2017
To me with this course, the best learning aspect is the final project; how to use Machine Learning Algorithms on data analysis.
By Rhys T
•Oct 10, 2017
Good course, some aspects of the assignment were a bit beyond the scope of what the course teaches but overall I learnt a lot.
By NÃck F
•Sep 27, 2016
Was pretty good, but quite short and some assignments did not align as well with the lecture material as they could have.
By Michael O
•Jan 10, 2020
This is a great course, but it would be good to see it updated to use the newer evolution of the caret package, parsnip.
By Tongesai K
•Feb 8, 2016
Very good course. I am very knew to this topic but am sure will find a lot of application in my speciality - geophysics
By Kevin S
•Mar 3, 2016
Good introduction to machine learning, might suffer a bit from trying to cover too much ground in such a short time.
By SEBASTIAN E C
•Aug 17, 2021
Maybe final review must be verified by an expert, also the kind of data to analyse must be change over the time.
By Sulan L
•Nov 19, 2018
I hope we can have more détails in this cours and to see how to use the algorithms for the big data. Thank you.
By A. R C
•Oct 20, 2017
I enjoyed it but it needs indeed to deep into many concepts, which are just briefly named during the course.
By Marcelo G
•Aug 15, 2016
Great course, very demanding, but it could use more reading material, ebooks instead of links on video.
By Jeffrey T
•Mar 28, 2016
Good overview of available techniques and the Caret package. Will get you started in machine learning.
By BIBHUTI B P
•Jul 24, 2017
This was a superb module which created a deep learning insight within me focusing on future technology
By João R
•Aug 20, 2017
Got confused how to perform cross validation and when. Other than that, very practical. Great job.
By Daniel R
•May 14, 2016
The course is really great, however it should last a little longer, 4 weeks is hard to accomplish
By César A C
•Jul 26, 2018
Very interesting course. May be a little bit harder than the previous ones but it could be done.
By Greig R
•Nov 14, 2017
Good course, I learnt a lot. It does need to be updated with more modern versions of software.
By Pieter v d V
•Jun 28, 2018
Very quick overview. If you really want to know something about it read the reference books.
By Guilherme C C
•May 18, 2016
Title says everything. Practically and basically no theory explained. Good course though.
By Carlos C
•Aug 12, 2017
Excellent content so I give 4 starts. I stat less because the trainer speaks too fast.
By carlos j m r
•Oct 5, 2017
I thought there were Swirl practice as other courses, however this course is very good.
By alon c
•Mar 10, 2016
Great Course, will be nice to have more projects to see how it goes with different data