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学生对 IBM 提供的 Open Source tools for Data Science 的评价和反馈

4.6
14,935 个评分
2,013 条评论

课程概述

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....

热门审阅

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!!!!

NS

Jun 30, 2019

This course is very nice to understand Python, Zappelin and R Studio basics on code and concepts, in which you will get hands on along with creating a free IBM Cloud and Watson Studio account.

筛选依据:

351 - Open Source tools for Data Science 的 375 个评论(共 2,001 个)

创建者 Laxmi Y

Nov 30, 2019

This is a basic course for a beginner level learner to get hang of Data Science

创建者 Austin H

Oct 26, 2019

Brief introduction for where to find and how to use the open source data tools.

创建者 Chinmaya R

Sep 04, 2019

Course so far so good. The course navigation on Coursera is not up to the mark.

创建者 ATHANASIADOU E

Aug 05, 2019

Very good for beginners. Overview of the open source tools to get familiarized.

创建者 Greice M N

Feb 27, 2019

Os vídeos precisam ser atualizados para acompanhar a nova versão da plataforma.

创建者 Manoj K P

Feb 06, 2019

Easy and fast way to learn the introduction of the cloud tools for data science

创建者 Moyo J

Feb 21, 2020

I learnt something new order than Jupyter Notebooks, learnt Zeppelin Notebooks

创建者 Zhenbo L

Oct 07, 2019

Great online Data Science course, open my view about the data scientist world.

创建者 Rajasekaran G

Apr 29, 2019

Kindly update the videos in the course to match the changes in IBM watson site

创建者 Juan A

Mar 11, 2019

Excelent Course. Very practical, a different course . Very Fast and intuitive.

创建者 Luis A P G

Nov 28, 2019

An excellent introduction to IBM Watson, RStudio, Jupyter notebooks and more!

创建者 LAURA T G

Oct 07, 2019

Very useful

I had to work really hard, so I've got so much knowledge from here

创建者 Kolukulapalli V

Oct 04, 2018

Very useful open source tools that can be used for data science and analytics

创建者 Filipe A d M S

Oct 17, 2019

This course gave me an excelente base to start doing more jobs in this field

创建者 Sukrut D

Mar 23, 2019

Excellent Course it gives all basic information about tools for data science

创建者 ShuTong

Nov 27, 2018

very good content. Now I have more knowledge about open sources. SO amazing.

创建者 Vincent L

Sep 13, 2018

Great overview of the tools we'll be using in the rest of the certification.

创建者 Vibhor G

Jan 15, 2020

Best Course for starting and have a look at the basics of coding languages.

创建者 Venkatasai M G

Jan 07, 2020

Good course for better exposure in open source tools used for data science.

创建者 Stephen H

Aug 09, 2019

Easy to learn and great tools that I had no idea existed until this course!

创建者 ozan a

May 20, 2019

It gave a good basis on what kind of tools are being used for data science.

创建者 Chris G

Jan 02, 2019

Excellent introduction to relevant open source tools used in Data Science.

创建者 Igor L

Mar 23, 2020

Great introductory course to free open source tools when working with Data

创建者 chaitra M P

Jan 11, 2020

Some part of the video did not match the current date practical experience

创建者 Guzenko S

Jan 06, 2020

It's an interesting course about main tools for beginners data scientists.