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学生对 IBM 提供的 Tools for Data Science 的评价和反馈

4.5
21,122 个评分
3,252 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, JupyterLab, RStudio IDE, Git, GitHub, and Watson Studio. 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 Skills Network 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 Watson Studio and demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers....

热门审阅

RR
Apr 24, 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!!!!

AJ
Sep 15, 2020

Absolutely Loved this course!! Challenging at times to keep up with all the terms and processes. The course provided great insight into Data Science. Would highly recommend it as your first course.

筛选依据:

251 - Tools for Data Science 的 275 个评论(共 3,223 个)

创建者 Md. A A J

May 2, 2020

This course creates a friendly environment to learn Jupiter notebook, Zeppelin Notebooks, RStudio and IBM Watson Studio step by step.

Course materials and assignments are great!!

创建者 Derrick K

Mar 7, 2020

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 8, 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 Ronaldo L

Apr 5, 2021

I would like to thank you for the good structure the course has and of course the material is very well explained. It lacks nothing in terms of content from an in class course.

创建者 Abhishek G

Sep 7, 2020

I learned about a lot of tools that I hadn't heard before. The course walks through deep insights into IBM Watson Studio and every aspect of it. This is a very detailed course.

创建者 Margaret M G

Apr 19, 2020

intimidated to learn the analytics tools and worried i was too much of a beginner to take this course on. It was very easy to follow the steps 1 by 1 to learn these tools.

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 Abdul H

Jun 9, 2020

This was a fantastic course. I managed to learn a vast set of skills in both Skills Network Lab and IBM Watson studio. I recommend Coursera to all of my friends and Family.

创建者 Devvrat M

Dec 1, 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 Motivation&Relaxation C

Apr 12, 2020

It was a great experience!! I had a great time learning how to create a new project, then a notebook where you can write codes using Markdown Cells, Headers, HTML,etc.

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 25, 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 6, 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 3, 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 GREGORY M

Mar 24, 2020

Loved the practical exercises and information. Hands on in the notebooks in a few different environment gave me confidence to try out other things on my own. Thanks.

创建者 Raghupati Y P

Feb 22, 2020

This course is little tough to clear at Assignment Stage but if your curious and determined then it's just the matter of time and you will start loving DATA SCIENCE.

创建者 Pinky C

Dec 11, 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 Diana J

Jul 13, 2020

its a bit challenging for a fresher in computers but with help of faculty support that is compensated .Special thanks to Miss Mallika...I could complete the course.

创建者 JUDIKA R S T

Jun 28, 2020

This course help me as beginner to understand about tools for data science such as rstudio, IBM cloud to create notebook and how to create simple code using phyton

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.