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IBM による Tools for Data Science の受講者のレビューおよびフィードバック

4.5
18,720件の評価
2,756件のレビュー

コースについて

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....

人気のレビュー

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!!!!

MA

Nov 29, 2019

This course helped me finding open source tools. I knew about Jupyter Notebooks, but I also got to know more tools. Further, I got IBM subscription too, it would definitely help me in my work.

フィルター:

Tools for Data Science: 76 - 100 / 2,728 レビュー

by ABHIJIT S

May 30, 2020

Good Day

I am personally thankful and grateful for this opportunity .

Thanks and Warm Regards.

ABHIJIT SENGUPTA

Portfolio URL : https://about.me/abhijitsengupta

Website : www.pactolianconsulting.com

E - Mail : abhijit@pactolianconsulting.com

Kolkata , India

Skype : abhijit.sengupta357

Ph. : + 91 33 25907110

Cell : + 91 9163863607

Whatsapp : + 91 8017648297

+ 91 6290750012

by Vagia X

Feb 20, 2019

I did not know about Cognitive Class Labs. I was trying to install all these different packages in order to be able to work with them and make progress but I have always had difficulties. I am super excited that I finally realised that there is a much easier way to work with all these amazing tools on line without any problem :-) Thanks a lot Coursera and IBM for this amazing course :-)

by Juan D P

Apr 12, 2019

It was a very good introductory course to the Open Source tools available for the practice of Data Science. The pace is normal and the contents are enough to understand and fulfill the requirements in the final project assignment. The IBM Watson Studio presented some issues but they were solved in less than 24 hours by the IBM Engineers. Kudos to the support team!

by Kefang A Y

Apr 18, 2019

It is very useful to know the IBM cloud platform and practical. The cloud platform is very complicate and may do many things. It looks like a forest for me.

Some videos is old interface. If there are step by step instructions, it will save me some time to quickly start. Assignment is easy, but take time to get used to the environment and to know where am I.

by Oluchukwu C G

Apr 19, 2020

I have to give it 5 star cause it was so explanatory and exciting, though the video instructions need to be upgraded cause the web interface as at April 19th, 2020 isn't the same as the Video instructions. So that needs to be upgraded!!! But you work your way round it if you pay attention!!!

Nevertheless, it's a wonderful course and very exciting!!!!

by Mamtha V S

Feb 20, 2019

Loved it! The most useful aspect was the cognitive class cloud web environment, which truly allows you the flexibility and mobility to practice from anywhere. There is no need to download install software, so you can access the course, literally from any machine, in a seamless manner. That's a very neat feature for someone who is working.

by Mohammed A M A

Jun 29, 2020

Assignment assessment is not controlled and sometimes assessors don't assess based on the right content. I encountered this issue in several courses' assignments. I hope that the peer-graded assignment undergoes some revision to establish a more credited assessment approach.

Thank you for your consideration.

Coursera is always the best!

by Joseph G

Nov 29, 2019

I learned so much in this course. I had no idea these tools were available in one place online. In preparation for doing the IBM Professional Certificate, I spent about a week installing programs and languages and stressing out about GUIs and IDEs. This course showed me multiple ways to get around all this and use IBM online tools.

by Jess M

Jan 29, 2019

A lot of this is outdated since the IBM Watson stuff has been completely revamped, and the Zeppelin Notebooks tutorials were difficult to follow, since they seemed to have already been run when I went in, and therefore I couldn't tell what was function and what was output. But it's great to have all these free tools available.

by James L M

Jun 10, 2020

This actually helps me since I have no background regarding the tools needed for development in Data Science. Week 1 and 2 are particularly helpful since it introduces a lot of tools that one could use. Week 3 is a bit promotional and week 4 is true challenge. The course really guides you on how to start jupyter notebook.

by Ankit T

Apr 19, 2020

It was a great experience to learn the various open-source tool for data science. I have gained considerable knowledge of the Jupyter Notebook and IBM Watson Studio. It will be of great help for learners if the data science experience tool videos will be modified with IBM Watson Studio navigation and notebook creation.

by Isis S C

Jan 19, 2020

Loved the course! It presents integrated environments where we can perform data analysis (+all previous and post steps) using multiple languages in open-source tools. IBM Skills Network Labs is perfect for learning, IBM Watson Studios enables collaboration and scalability, for enterprises. Super convenient tools!

by Frances B

Mar 20, 2019

the course is great for people getting into the field of data science and have no clue where to start with resources for the filed. It helps build confidence and security knowing there are resources at our finger tips, for free, and with guidance from the the tutorial videos provided in this course. great stuff.

by Atal S S M

Mar 05, 2019

Very informative on the open source tools available. It does get tricky sometimes to understand the instructions of the notebooks as the videos display an older version and the current website would have the updated version. IBM Cloud is a huge advantage to work on Python,R and Scala with spark kernels for free.

by Mike M

Dec 14, 2019

Very beneficial, albeit somewhat painful , in getting the assignment done since the videos (at the time of this review) are not exactly correlated with current software (Watson v. Data Experience).

But hey, we are to be problem solvers, so that was just one minor hurdle to overcome and learn from in the process!

by Avadhoot

Jul 18, 2020

This course was intensive on tools used in Data Science. It was an overwhelming experience for I learnt to use resources on Github and understood how Jupyter notebooks are important in writing long codes. All in all , a great experience and would like to complete the full IBM data science specialization soon.

by Travis T

Jun 04, 2020

It's a good overview of all the tools that can be used for data science. If you're following along with the IBM course, it gives you a good idea of what you could be using for your capstone class. They do not detail much of tools rather introduce them to you. It'd be up to you to delve deeper if you'd like.

by Luis F G M

Aug 05, 2020

Astonishing course for learning the basics of the tools used for data science, open source tools and comercial tools, at the beginning it might be a bit overwhelming because of lots of terms that are unknown by most starters like me, but as the course goes on and if you are commited, it's a piece of cake

by CHIN-HUNG, Y

May 24, 2019

Nice in introducing approaches to data science; however, some parts appears unnecessary to be mentioned right in the beginning. For example: Appache Zeeplin and Zeppling for Scala are more of courses in either intermediate or advanced level. Perhaps postponing it till database would be a better option.

by Elmer B E

Jun 22, 2020

This is a very comprehensive presentation on the available tools for Data Science both Open Sources and that of IBM proprietary tools. As presented, you as a Data Scientist has the sole option which of these tools are fit for your data science studies. Very enlightening and full of thoughts to ponder.

by Isha C

Sep 23, 2019

Good introduction to free and paid programs available for practicing and understanding data science! It shows detailed UI walkthroughs and tutorials, and gets you started setting up accounts that you will most likely use many years while learning data science and programming (R, Scala, Python, etc).

by Courtney B

Sep 24, 2018

Love it! It's such a gentle introduction to the tools of the trade as well as the languages we need to learn in order to use them. The labwork is my favorite part. The only way you can learn anything interactive like this is by diving in and trying things out, and now all I want to do is learn MORE.

by Philipp R

Apr 21, 2019

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

by Sagarika S

Jun 09, 2020

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.

by Fiorella M

Jul 16, 2020

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.