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

4.5
звезд
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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151–175 из 3,917 отзывов о курсе Tools for Data Science

автор: Philipp R

21 апр. 2019 г.

Great introduction to various tools offered by IBM. The course does not go into depths but rather shows what is out there. To really get the most out of this course, one needs to be motivated to explore the tools on one's own time. But that is a given in this field, I'd say. Therefore, five stars

автор: Mahesh M

24 янв. 2021 г.

This gave me the brief introduction of Data science with IBM tools, the essential third party tools for Data scientists. Introductory knowledge on almost all data science related techniques is appreciable. One can enhance it completely by going through future courses in the same specialization.

автор: Sagarika S

9 июня 2020 г.

The course is amazing for beginners as well as for professionals for building the concepts. I am really thankful to all the instructors for delivering the concepts very clearly. I recommend this course to everyone who wants to learn the different tools to build their foundation in Data Science.

автор: Abrar M I

17 дек. 2020 г.

This course did a great job of summarizing the coding and non-coding tools required for data science as well as highlighting the different levels of interaction with data and modeling and how collaboration is achieved as well as learning in the field. This was awesome, would highly recommend!

автор: Fiorella M

16 июля 2020 г.

This course is excellent to understand as an introduction the principal tools that are usted in the data science field. With this knowledge I have a more clear view on the tools I would like to investigate. I recommend this course for beginners with no clue of the tools usted in data science.

автор: Aman C

1 окт. 2019 г.

This was a really intuitive course with hands on experience on Jupyter Notebooks, Rstudio, Python 3.

It turns out to be the more I'll practice the more I'll learn and this course really turned out to be helpful as a stepping stone towards it. Thanks a lot for creating such an amazing course.

автор: Danesh T

23 апр. 2020 г.

In the modern digital world transformation of world and the data science is very useful in our daily life activities and increases the quality of life and now a days the information is the wealth and it is used in the future career and so many applications of data science is used.

Thank you

автор: Maksim M

7 мар. 2019 г.

This course gives good practical understanding of the open source tools for data science, such as Jupyter Notebooks, Zeppelin Notebook, RStudio IDE, IBM Watson Studio. Now I know what they are and how to use them, although had absolutely zero idea about the matter before taking the course.

автор: çağdaş y

20 февр. 2022 г.

Great course to learn data science tools. Try to note everything down and great instructor. But I sometimes lost my focus, too much information about tools that I could not fit in my knowledge because I have no previous experince.

Helpful instructors also online for any kind of quesitonç

автор: Monica A

19 июля 2020 г.

Really good course. It listed so many important commercial and open source tools and provided material to explore and do hands-on on the important ones like GitHub, Jupyter Notebook on Watson Studio. It also showcased the entire process of how modeling works in data science.Thanks alot !

автор: Benson N K

12 июля 2019 г.

An extremely nice course, easy to understand and easy to follow video directions shared by the instructors. Ave learnt so many open source tools that I can use in various data models and how identify the best tool to use depending on dynamics of the data and tasks ahead. Kudos IBM Team

автор: Gilberto F

2 дек. 2018 г.

Once again is a pleasure for my be part of this Awesome courses in this brilliant website who help people to improve their skills, in my case with 2 financial aid approved I have no words to describe how I feel right now. Many thanks to all people who make this possible.

Happy Learning.

автор: Andrea C

18 апр. 2020 г.

I thought this was very informative and relevant. What I didn't like was the lack of integrity that some of the people using the course have. They clearly were giving bad marks on assignments for no reason. Working in Data Science requires integrity so if you don't have it, get lost.

автор: GK M

15 апр. 2021 г.

Excellent course for whoever wants to start exploring Data science as a career options or just use it to solve real life problems using large and complex data. It encourages the users to go beyond the content and explore the emerging world of technology which supports data science.

автор: Jai K B

28 июля 2021 г.

I am glad to complete this level.

Useful concepts and theories for learning RStudio and Jupyter Notebook/Jupyter Lab and Python and IBM Watson. I learned a lot from this course.

Thank you so much IBM and Coursera for select me and trust on abilities.

Best Regards,

Jai Kumar Baakeriya

автор: Zakaria A

26 мая 2019 г.

The course is engaging and interesting. It is really good and would recommend to anyone who wants to take a look into data science and start working on it. The ungraded assignments may be a bit confusing but you will manage to get through. Overall it was a fairly good experience.

автор: Shruthi K

24 апр. 2020 г.

This course was very helpful. This course taught me what are the open-source tools used in Data Science and how to use them. Happy to learn new things. Thankyou Coursera and IBM. And also a big thanks to the instructors who made this course. Looking forward to learn more things.

автор: Dragoljub R

25 мар. 2020 г.

I've been able to learn basics in data science software. It was a nice experience and an introduction to something I am looking for to learn. I would recommend to all without prior experience, though those who have already worked with those tools this course won't mean too much.

автор: Samuel D S

12 мар. 2020 г.

As I have an old laptop with 3GB RAM, I had a lot of trouble running my IBM Watson. Only when I changed to a laptop with a 4GB RAM, I was able to run my IBM Watson. But I had a difficult time trying to figure out how to solve this problem. But overall it was a very good course.

автор: ASHISH K

12 мар. 2020 г.

I think the practice with the ed courses really helped me . And i would like to add the online Jupiter book is really awesome which saves us downloading and installing other software.

The course instructor approach was really commendable and the concept delivery was really good.

автор: Ruiming Y

31 мар. 2021 г.

Fantastic course! I have been hoping to learn how to use Jupiter notebook systemically for a long time, and this course provides a best chance to do that. I also learn how to use markdown and I can say I am even more specialized than some of my friends who are programmers lol!

автор: Jake Z

21 янв. 2020 г.

Great course! I was already aware of Jupyter Notebooks but it was great seeing the other tools available along with their pros and cons. Learning about the IBM Watson capabilities is also incredibly useful for at home projects where my pc only has so much processing power.

автор: Nadeesha J S

18 мар. 2019 г.

The other courses I took are too easy sofar for me. One course is like one lecture to me in college level. I am not sure how this is gong to help. I would expect the courses to get harder. However. I learnt a lot from this course as it asks us to do a lot of extra reading.

автор: Moray B

17 апр. 2019 г.

Great course. I knew some python, SQL, Jupyter before but all very point knowledge. The first course provided some great data science context and I now understand at a high level Zeppelin and RSudio, and how to work in both a Cloud production environment with Watson Lab.

автор: Ashfaaq I

7 мая 2020 г.

I learnt a lot in this course. I was able to start a new journey with open source tools for data science and the videos in the course were clear and easy to understand. I would recommend this course for any future data scientist to learn his/her tools for data science.