Chevron Left
Tools for Data Science(으)로 돌아가기

IBM의 Tools for Data Science 학습자 리뷰 및 피드백

4.5
별점
18,720개의 평가
2,756개의 리뷰

강좌 소개

What are some of the most popular data science tools, how do you use them, and what are their features? In this course, you'll learn about Jupyter Notebooks, RStudio IDE, Apache Zeppelin and Data Science Experience. You will learn about what each tool is used for, what programming languages they can execute, their features and limitations. With the tools hosted in the cloud on Cognitive Class Labs, you will be able to test each tool and follow instructions to run simple code in Python, R or Scala. To end the course, you will create a final project with a Jupyter Notebook on IBM Data Science Experience and demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate....

최상위 리뷰

RR

Apr 25, 2019

To the contrast of other reviews, I find the content very well bifurcated and fed to the learners. The course very easily digestable and I have had a great amount of fun learning it.. Go for it!!!!

MA

Nov 29, 2019

This course helped me finding open source tools. I knew about Jupyter Notebooks, but I also got to know more tools. Further, I got IBM subscription too, it would definitely help me in my work.

필터링 기준:

Tools for Data Science의 2,730개 리뷰 중 126~150

교육 기관: Carol L

Jul 30, 2019

Este es un curso introductorio a las herramientas de analisis de datos, especialmente la de IBM. Me agradoó mucho porque se sentraron en la herramineta mas que en los lenguajes que se deberian manejar, los cuales serán abordados en los proximos cursos.

교육 기관: Morgane B

Jul 21, 2020

Ce cours est utile pour se familiariser rapidement avec un certain nombre d'outils data utilisés dans le monde à l'heure d'aujourd'hui. Les explications sont assez claires. Pour les labs et les devoirs, il faut juste suivre les consignes à la lettre.

교육 기관: Pedro C G

Dec 05, 2019

It is quite god to get to know the tools available

Recommendations, there are some changes to the current platforms, that information should be updated.

Question, why did we sign on to cognitive lab if the assignment will be completed in Watson Studio?

교육 기관: VENKATESAN N

Apr 08, 2020

It was awesome learning from coursera. Contents are well created to be understood by anyone easily. It's amazing and i wish everyone who is interested in data science should take up this course. Looking forward to take up more courses in course era

교육 기관: Rodney C B

Aug 08, 2019

Very good intro to the tools available.

The improvement to the training would be also how to do it in my own computer without connecting necessarily to an external tool and then once I'm ready use the tools IBM provide for a professional deployment.

교육 기관: James C

Mar 23, 2019

I enjoyed this class. It gives good exposure to Jupyter and Zeppelin notebooks, as well as IBM Watson Studio. Students can spend extra time with these tools to get more depth of knowledge (but still introductory knowledge). Also includes some R.

교육 기관: Bright T O

Oct 29, 2019

The learning has been broken down step by step. This has helped me gained deeper understanding about RStudio, Zeppelin Notebook, Jupyter, Python 3 and more. Now I feel more encouraged to continue the course till the very end. Thank you Cousera.

교육 기관: Christopher T Y E

Jun 28, 2019

good intro to very very surface essentials of watson, zeppelin, jupyter, rstudio. though i didn't like the relatively extensive reading. video tutorials would be easier to follow cos a pic speaks a thousand words! but tqvm for this course!!!!

교육 기관: badal s

May 21, 2020

It is an amazing course that helps us understand the basic tools required to be a Data scientist. The course was indeed insightful and I highly recommend the aspirers of data science or analytics to begin this course and have happy learning.

교육 기관: HVictor

Sep 18, 2019

I've only had the chance to work with Jupyter notebooks as its what I had originally started learning with. This course allowed me to see other tools that are out there. Expanding my visibility into areas I had otherwise not been aware of.

교육 기관: Priscilla S

Apr 27, 2020

Great way to learn about the open source tools for data science to dive deeper. One suggestion would be to consider updating the IBM Watson Studio section videos. It appears that significant updates have been made to the website since 2018.

교육 기관: Anette F

Nov 04, 2018

Great introduction into Open Source Tools and into the basic workings of these tools. I love the labs, this is so hands-on and really gives the most realistic view on data science tasks and how they are done that I have come across so far.

교육 기관: Neelabh S

Mar 28, 2020

Really nice introductions to these amazing tools such as Jupyter Noteboos, Zeppelin, IBM Watson Studio and RStudio IDE. Very easy to grasp and the final project helps practice all the basics in Jupyter notebook using some Python code.

교육 기관: Jafed E

Jul 06, 2019

I enjoy the lectures. The professor has a good speaking and teaching style which keeps me interested. Lots of concrete math examples which make it easier to understand. Very good slides which are well formulated and easy to understand

교육 기관: Jason K

May 21, 2019

Very good explanation of all tools that is available to users to enable them to work effectively. The labs also proved helpful with practicing and getting familiar in terms of navigation and getting use to the different environments.

교육 기관: Mateusz K

Jan 01, 2019

Nice review of existing open source tools and free to use web services implementing those tools. Personally I would also enjoy some introduction to either how to set up those open source tools on a personal computer or private cloud.

교육 기관: Vishal n

Apr 27, 2020

this course I good enough to under stand which tools are applicable in data processing in data science . thanks Coursera for providing such a course that was very funy I enjoyed my valuable time learning with Coursera and faculty

교육 기관: Suraj R G

Dec 03, 2019

Fantastic course it was. I got overview of most of the open source tools for Data Science.

The Assignment at the end of the course was also interesting as it summarizes all the things we learned.

Thank you for such awesome content.

교육 기관: Daniel F d P

Apr 12, 2019

Eu adorei esse curso. Me ensinou muito mais do que apenas ferramentas de código livre para data science. Aprendi também sobre computação na núvem e ganhei vivência na IBM Cloud, além de aprender sobre como baixar dados públicos.

교육 기관: Sakiru Y

May 01, 2020

The course is quite technical but very educational and instructive. Though I got a bit confused when I created the Watson Studio, because the platform was different from what the instructor used. But it is an interesting course

교육 기관: Aman S T

Apr 12, 2020

This course was good It will teach you various open source tools that are being used in data science fields like RStudio, Jupyter notebooks, Scala, Hadoop,Apache spark etc. I would definetly suggest you to take this course .

교육 기관: Devasish A

Jan 02, 2020

Just enough to know the different types of open source tools that can be used to data science. to learn the tool completely, we need to refer to many tutorial materials within.

Good Introduction session for tool applications.

교육 기관: Avirup C

Aug 17, 2019

The course is exceptionally good in order to introduce you various details about the tools that you require for Data Science Analytics.

Exceptionally well made support by IBM and Coursera is as a whole best for these courses.

교육 기관: Eric G

Oct 07, 2018

Great course and the tools provided are very useful. You have to really work by yourself to read and understand the tools though, because there is no way other than practice to learn the various notebooks and how they work.

교육 기관: Moonsuk S

May 22, 2020

I am novice to this field. Nevertheless, I did not have much troubles in catching up the class because the contents of this courses are very well organized and the level of the class was well adjusted. Thank you very much!