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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
stars
12,745 个评分
1,616 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

FM

Dec 28, 2019

This is a great course, but the tutorials are outdated, which may slightly detract from studies. But the course aggregate a lot to my formation and allowed me to know new tools to be a data scientist!

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!!!!

筛选依据:

101 - Open Source tools for Data Science 的 125 个评论(共 1,610 个)

创建者 Derrick K

Apr 23, 2019

I was really excited to dealing with IBM Watson Studio through the Internet. Also, given IBM Badge made me feel very worthwhile about learning. Thanks for this practical lecture.

创建者 Luis H

Jan 09, 2019

The information is clear and allowed me to complete all the activities, just be aware that the IBM tool is not upgraded in the course so research and web navigation is mandatory.

创建者 KUDA T C M W

Oct 14, 2019

Once I enrolled in this course I had no idea about Data Science tools. This course is the best for who don't know anything in Data Science tools and very beginners in this area.

创建者 Haywood N

Aug 19, 2018

An invaluable hands-on provision. I feel as though I am adequately hatted with the basic skills and equipped with the efficient tools for my next steps in pursuing Data Science.

创建者 Rudolph M N

May 16, 2019

I use a chromebook and these tools were very helpfull for someone who is new to the discipline and cannot reliably boot a python terminal or R studio on his primary machine.

创建者 Devvrat M

Dec 02, 2019

Great course for understanding the essentials tools required to implement Data Science. Juypter Notebook and Zappelin Notebooks are the most preferred Notebooks to work on.

创建者 陈嘉琪

Aug 27, 2019

Brief introduction to manny useful online tools for data science. Although it seems to be easy to accomplish this course, it really helps me learn more about data science.

创建者 Tassio C d A G

Feb 24, 2019

This course is primordial to meet the tools applied to the slim courses. Explicit concepts and ease of access in the course. Course clear, structured and of great value.

创建者 Zaheer R

Oct 14, 2019

Makes you familiar with the software tools needed to write code in Data Science. It is not an programming class but rather a great tutorial around each piece software.

创建者 Nikhil K

Jan 26, 2019

Thanks a lot to Coursera & mentors. I am really very happy for such a wonderful teaching pattern which is not only beginner friendly but interesting & interactive too.

创建者 Glener D M

Jan 22, 2019

I learned how to use Jupyter Notebook in the IBM Data Science Experience and practically with its proficiency in preparing a notepad along with the Markdown recording.

创建者 Andrew B

Jan 06, 2019

Useful tools for the beginning data scientist. However I found that all courses listed through this specialization are available for free through Cognitive Class Labs.

创建者 Gopala R

Oct 03, 2018

Very nice introduction to online tools with simple hands on training. Labs and quizzes are build the confidence of the student whether novice or expert in other areas.

创建者 Pinky C

Dec 12, 2019

Thanks for creating this course but while doing it with complete specialization according to first course it feels little hard and not connected with previous course

创建者 Vivekanand P

Sep 11, 2019

Nicely documented learning. Only suggestion is to update the content of lab where instructions are per the old DSX tool and are not exactly same for Watson studio.

创建者 Andrew K J

Jul 12, 2019

I found this course very useful. I especially enjoyed practice with new markdown tools in Jupyter which were very useful for creating well formatted notebooks.

创建者 Ramiro B

Sep 22, 2019

As elementary as it could be, it's a great introduction to Jupyter Notebooks indeed. But starting from this, I could see farther the reaching of Data Science.

创建者 Patrícia P A

Jan 17, 2019

São muitos recursos e um mundo de ferramentas. O curso passa pela mais relevantes e propõe atividades práticas em cada uma delas. Muito bom ter este panorama.

创建者 Azhan A

Sep 05, 2019

Awesome course. Lots of Learning. These free sources adds lots of ease to your work, its like everything tool you can think of is present in a single place.

创建者 Onkar s

Aug 23, 2019

Really helpful in terms of getting a knowledge about the main core technologies used in Data Science.I would recommend this course to the absolute beginner.

创建者 Girish B P

Jun 26, 2019

Course content was good, but IBM watson contents need to be updated and lots of issues while creating project. hopefully it gets resolved for other students

创建者 Ekwoge E B

Jun 10, 2019

This course help open a very broad area of tools to use for Data Science I had no idea even existed. I am thrilled and motivated to work on this even more

创建者 Maria N L

May 16, 2019

Excellent introduction to basic open source tools used in data science; however, the content needs updating since the UI of IBM Watson Studio has changed.

创建者 Jorge A C C

Nov 30, 2019

Muy recomendable, me encanto la oportunidad de poder hacer uso del Jupyter, Zeppelin, R en los entornos como el Skill Network Labs y el IBM Watson Studio