(3 Reviews)
(24 Reviews)
EL
Feb 28, 2017
A long course compared to others in the specialization, but a lot of great material. Very well presented, the instructors know how to present this material and make it easy to grasp and understand.
ST
Nov 22, 2016
The course is full of the cases and the real life examples coupled with the theory background. Its very simple to understand and the course will definitely be of an value for people looking for
By NAVIN B
•Oct 20, 2016
Excellent!
By Katarzyna P
•Dec 8, 2015
excellent!
By JUAN A S
•Nov 21, 2021
Excellent
By DR. S T C
•Jul 14, 2020
Excellent
By Flt L G R
•Jun 16, 2020
THANKS...
By Prasenjit P
•Aug 8, 2018
Superb!!!
By K K
•Dec 6, 2018
A
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S
O
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By Odemir D J
•Jul 21, 2021
Great !
By Fabio L G Á
•Aug 23, 2020
Awesome
By Ajayi I M
•Feb 27, 2019
Awesome
By Mohamed H
•Jan 28, 2022
Thanks
By hossam m
•Nov 19, 2020
Thanks
By mansi g
•Oct 30, 2018
superb
By 龚子轩
•Jul 7, 2018
课程长度适中
By Ghazanfar
•Dec 1, 2017
Excell
By Federico C
•May 7, 2017
Great!
By Bauyrzhan S
•Jun 12, 2018
Good!
By mohammad j
•Sep 6, 2021
good
By Mona A A
•Jul 24, 2020
good
By Dhiraj K
•Aug 20, 2019
g
o
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By ALAA A A
•Jan 11, 2018
good
By Manas K K
•Dec 31, 2017
V
By Dristy C
•Oct 7, 2017
C
By Kevin M
•Mar 25, 2020
Solid process overview of managing a data analysis project.
Overall a straightforward course and the length/depth is appropriate for the course objectives.
Some of the material is entry level management and experienced managers can judge how best to consume the course
The course does not directly cover supervised / unsupervised learning but refers to association and prediction. There is no mention of cross-validation data sets, F1, precision, or recall as "measures" for evaluating the formal models.
The EDA section could be bolstered by mentioning feature scaling as part of the exploratory data analysis. There is no direct mention of cluster analysis, k-means, PCA, or similar tools that may be applicable to EDA.
By Neil I
•Jun 9, 2020
Good course if you have some knowledge of data analysis and an interest in the area. On completing I felt more confident about my abilities, in my ability to work with data scientists, as well as critiquing some past projects and realising how I might have improved them. (I also now realise and can explain why recommendation algorithms are so annoying, which is perhaps more important.)