Chevron Left
Retour à Data-driven Decision Making

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

4.6
étoiles
5,538 évaluations
1,056 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.

Filtrer par :

826 - 850 sur 1,019 Avis pour Data-driven Decision Making

par Mahesh M

9 juil. 2018

Content was sufficient however more practice challenges would have made this course more effective

par SRIKANTH G

16 mai 2020

Very good course to get broader in sight on importance of data and also various methods of data.

par Zhang G

15 juil. 2019

Too many concepts and high level introductions. Could be better just combine it to the course 2

par AFFIA R M

7 sept. 2019

Awesome course. A very good course to introduce a new learner into the 'world' of Big Data.

par Uchenna

26 déc. 2020

Well structured Course. An exceptional introductory ground into the Field of data science

par Alberto G C

22 août 2018

Good introduction to Data Analytics - Looking to forward to completing the specialization

par Douglas G

19 janv. 2018

Can be a touch axiomatic, but I'm sure it's a good basis for more important skills later.

par Par G

18 févr. 2019

The criteria or guidance for the final assessment wasn't clear, or could not be found.

par Nancy B

23 nov. 2018

Nice mix of technical, strategics and processes. I found the framework most helpful.

par Lucy T

20 déc. 2020

good introduction of data analysis framework, packed with real world examples of d

par Fadoua E

10 nov. 2019

I appreciate the quality of the videos used in this course and also the continent.

par Yin C

26 mai 2019

Very good. It's good to know the main tools and tech approaches of data analytics.

par Sudarshan Y

30 mai 2018

A pdf demonstrating the use of different analysis techniques would be very useful.

par Susan B

20 août 2017

A good overview, but the last week really ramped up the materials without warning.

par Tim M

20 janv. 2021

Good to begin with when you're completely new to data analytics and visualisation

par swathi

3 mars 2019

The course not only introduces data analytics but also has in-detail description.

par Arun R

6 sept. 2018

Its a good start for people who want to start their career with data & analytics

par osama n

3 mai 2017

it's my first online course , i liked it too much . it was an amazing experience

par Aashay C

27 sept. 2016

Very good introduction into the field. Peer reviewed assignment could be better

par Yue Z

16 févr. 2020

high-level overview; little hands-on experience. good primer on key concepts.

par Jon C G

7 févr. 2017

Primera parte muy teorica, pero productiva, se adquieren muchos conocimientos

par Сидорова Е Е

26 oct. 2018

Too much theory, but the course is really inspiring and interesting. Thanks!

par Pham X T

23 mai 2018

Great course for new comers but not very much information, just an overview

par Thomas G

30 juil. 2021

The final project was really helpful and engaging using course material.

par Mourad D

8 mars 2020

A great introduction to data science, although it lacks a lot of depth.