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Avis et commentaires pour d'étudiants pour Data-driven Decision Making par PwC

4.6
étoiles
5,340 évaluations
1,018 avis

À propos du cours

Welcome to Data-driven Decision Making. In this course, you'll get an introduction to Data Analytics and its role in business decisions. You'll learn why data is important and how it has evolved. You'll be introduced to “Big Data” and how it is used. You'll also be introduced to a framework for conducting Data Analysis and what tools and techniques are commonly used. Finally, you'll have a chance to put your knowledge to work in a simulated business setting. This course was created by PricewaterhouseCoopers LLP with an address at 300 Madison Avenue, New York, New York, 10017....

Meilleurs avis

JQ
26 mai 2017

Congratulation is a great course, a Professional level.\n\nThank you PwC for share the experience of the HUMAN TALENT.\n\nThank to the instructors a really great course.\n\nThank you and God bless you

BH
22 avr. 2020

An excellent course journey for this subject - Data Driven Decison Making, very good content with relevant case assignment and they are paced comfortably to allow me as learner to grasp the knowledge.

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926 - 950 sur 982 Avis pour Data-driven Decision Making

par Nyee N T

27 janv. 2020

An informative course with a high level perspective and real life examples, suitable for beginners and senior executives.

par Anshuman D

12 oct. 2016

The course is good for elementary understanding, th exercises were fun too. However, the tools could have been described

par Ahmad S G

6 oct. 2019

This course is good but it only has theories. Practical use of Excel or any other analytical tool should also be added

par C S

13 janv. 2020

Really long PwC commercial. Had a few choice nuggets of information. Hearing the vocab a bunch was good.

par Preetam P

10 juil. 2019

It was good but quite basic with less real-time examples from different industries to explain the point.

par Charu L S

9 juin 2017

very basic information ! The cost of the course is not justified for the content shared/displayed.

par Shane W

27 févr. 2018

A little dry, but a good introduction of the theory that underpins the rest of the modules.

par Mark F

28 avr. 2017

Too high level compared to what I expected, but does give a good overview of the topic.

par Shubham K

4 mai 2020

Need to be more application based. But for a beginner its a good course.

par Jack W

14 août 2017

Good demonstration of data analysis at a glance but that's all it is.

par Dzmitry R

2 avr. 2019

I was expecting in depth explanation of decision making. Thank you.

par Hadeel K A

10 déc. 2017

the rating was unfair and they did not provide efficient feedback

par Archana

13 nov. 2019

The final assignment was not marked fairly by other students.

par Shane W

1 juin 2017

Nice introductory overview of the application of analytics

par YOUMBI N F Y L

8 mai 2020

We expected to learn pratical skills during this training

par Ahmed A

14 janv. 2018

Could have been much shorter.. too much repetition.

par Kehinde R O

7 août 2019

GOOD COURSE BUT TOO THEORETICAL NOT DEEP ENOUGH

par Francisco M L

9 sept. 2020

Demasiado teórico, poco práctico.

par Aygul K

24 juil. 2020

There are so much ads about PWC

par Natalia M

19 oct. 2016

extremely high level

par Jitendria v

20 juil. 2017

overview was good

par Saumyajit D

19 janv. 2017

Overview is good

par Ayushi G

13 juil. 2017

Very Theoretica

par Swarada S P

18 avr. 2019

It was OK.

par Michaela B

13 juil. 2018

Positive is that this course gives you basic understanding of data analysis. 2 weeks of this course went quite okay, although I noticed in the first week already that presenters are reading what they are saying. The third week is SO boring and I cannot wait for this course to end. I can say for me it's the most expensive and the most boring course on coursera so far. I tried several courses here and none of them was so bad. Honestly, I expected more from this one as it's PWC but honestly it seems to me like 'Yeah, let's read some paragraphs from fancy lectures and books and make some money of it'.