(76 avaliações)
(48 avaliações)
SJ
9 de set de 2017
This is a great starter course for data science. My learning assessment is usually how well I can teach it to someone else. I know I have a better understanding now, than I did when I started.
MD
27 de ago de 2016
Is really hard to summarize the potential of Data Science and being clear, but I think that the instructors have done their best, so that we can achieve the most from the Course.\n\nGreat Job!
por Weihua W
•30 de dez de 2015
Advises are really good. The course charges too much! A one week course should set a reasonable price, for instance, $19.
por Mohammad S R
•13 de set de 2017
An engaging course for beginners who need to answer the important question i.e. Is Data Science a field of my interest ?
por Anders R K
•24 de out de 2015
I really liked it. Some of tje jargon was a bit technical though. But overall really appriated the opportunity yo learn,
por James M
•9 de nov de 2020
Test questions seem haphazard and do not appear to be validated. It feels like they are written by a bad AI algorithm.
por Ajayeswar R
•16 de jan de 2019
this course is not-technical as I was hoping for.This is an overview.But it was presented very beautifully.
Thank you
por Lai Y W @ L Y W
•13 de ago de 2020
Easy and straight to the point undamental basic information for non data science background executive. Good course!
por HUIYAN Z
•18 de dez de 2016
Very basic introduction to data science. The class is well-organized and suitable for new learners of data science.
por Stanisław R
•6 de set de 2018
I would call it Overview of Data Science. It puts Data Science in perspective of other fields, but is too shallow.
por Alan M F
•9 de mai de 2020
Good overview of Data Science. Very broad but a good starting point for someone with some statistical background.
por Willzhang
•4 de dez de 2019
An overview of Data science, great guidance to a new skill and methodolegy. My first finished course in coursera.
por Alvaro M L
•6 de ago de 2018
Fair overview of the goals, differences, pitfalls, roles and processes involved in deliverying analytic services.
por Anuradha A
•10 de fev de 2020
Helps learn about Data Science objectives, process, structure, toolbox and hype in short with real-life examples
por Paolo P
•24 de ago de 2017
As good as it possibly can be for such a very short, high-level course. It can be completed in just a few hours.
por Gabriela E L M
•5 de mai de 2017
Goes to the point, warns about thinking wrong about DS because of hype and lack of (scientific) sustainability.
por Harsha
•4 de out de 2016
Good intro to data science and has given overall information what a data scientist actually do in a high level.
por M H
•5 de ago de 2020
All the lessons are interesting and enjoyable, some are just excellent. Thanks Johns Hopkins, Thanks Coursera.
por Bales.mr@gmail.com
•6 de out de 2017
Good overview, could go into more depth at least for those with even a bit of a background in data / analytics
por Manoj G
•7 de jul de 2018
This is the great course where I do able to understand the basics of Data Science and what it all dealt with.
por Jose F V G
•2 de jul de 2018
Content was super high level. Deeper content will do (more examples, pages, exercises or real life practice).
por Michel G
•26 de dez de 2018
Knowledgeable professors. Had to spend some extra time researching some of the terms not covered in course.
por Andrew E
•4 de jul de 2017
It is what it is: a crash course. Good to immerse in before committing to longer and more expensive courses.
por Rui R
•5 de jun de 2017
Not dificult, but can be improved !
In terms of time, it is not time consuming. Better to whom has less time.
por SAURAV P
•30 de dez de 2015
A very articulate orientation, which meticulously arouses interest about different corners of Data Science.
por Christophe A
•4 de jun de 2020
Interesting overview of what is Data Science. I would have hoped more concrete examples and case studies.
por caroline l
•11 de mar de 2018
Good basics, but basic and you really need to have knowledge of many Data Science terms before you start.