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Отзывы учащихся о курсе Tools for Data Science от партнера IBM Skills Network

4.5
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Оценки: 24,397

О курсе

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....

Лучшие рецензии

GC

12 апр. 2020 г.

It serves perfecty its aim that is giving a first glance of the open course tools for data science. Of course each tool is briefly touched and it hands over the student the duty to deepen each tool.

RR

24 апр. 2019 г.

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!!!!

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201–225 из 3,918 отзывов о курсе Tools for Data Science

автор: HVictor

18 сент. 2019 г.

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.

автор: Priscilla S

27 апр. 2020 г.

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.

автор: Anette F

3 нояб. 2018 г.

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.

автор: Kanishk K

11 авг. 2020 г.

At the beginning, this course tries to overwhelm you with a lot of tools and you'd think IBM is just advertising but later in doing a simple project in this course you'd be thankful IBM provided all the tools in one place in the cloud.

автор: Neelabh S

28 мар. 2020 г.

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.

автор: Jafed E G

6 июля 2019 г.

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

автор: Jason K

21 мая 2019 г.

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.

автор: Mateusz K

1 янв. 2019 г.

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.

автор: Harry F

21 сент. 2021 г.

Excellent course to begin introduction to the most useful tools for data science from data compilation to model building process.

The videos and demos are very understoodn and show too many information about the data science tools.

автор: 053 V N

27 апр. 2020 г.

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

автор: Suraj R G

3 дек. 2019 г.

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.

автор: Daniel P

12 апр. 2019 г.

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.

автор: Michael S

5 апр. 2021 г.

I enjoyed these weeks of Data Science introduction so far. Thanks for providing all the tools needed at Watson Studio and rare opportunity to get familiar with the most recent technologies and tools. That this course was about.

автор: Sakiru Y

1 мая 2020 г.

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

автор: Mehmet C

3 дек. 2021 г.

This course was heavier than the first one; it gives more opportunity to experiment on lab sessions which I like and it gives detailed view of a lot of tools that is currently available for people who is interested in data.

автор: Lokesh D

23 июля 2021 г.

A comprehensive course on the different tools used in Data Science pipeline. Since it is an IBM course, most of the tools covered are from IBM, although I felt some more content on non-IBM tools could have been more helpful.

автор: Aman T

11 апр. 2020 г.

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 .

автор: DEV A

2 янв. 2020 г.

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.

автор: Avirup C

16 авг. 2019 г.

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.

автор: Rohit M

25 апр. 2022 г.

The overview reagarding the tools for data science is very good. It has covered many insights and classification of tools that a data scientist can utilize and also make note of such tools to work effectively with the data.

автор: Eric G

7 окт. 2018 г.

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.

автор: Moonsuk S

22 мая 2020 г.

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!

автор: Marceline C M

14 февр. 2020 г.

I loved the practical approach of the course. It's not just listing of tools but step by step application which makes me more confident-I know exactly where to fetch each tool I need in a Data Science Project.

Thank you.

автор: Jatin S

4 июня 2020 г.

The Tools which were mentioned in the course are really helpful and important.

Through this course, you can get to know about various tools used in Data Science with their use and explanation. I really liked this course.

автор: Apurva R

25 мар. 2020 г.

Though the interface in the videos were little outdated, the IBM professionals are working on it to make it better. The style of teaching is incredible. Extremely responsive team. Thanks for giving us a chance to learn.