Chevron Left
Back to Tools for Data Science

Learner Reviews & Feedback for Tools for Data Science by IBM

4.5
stars
29,164 ratings

About the Course

In order to be successful in Data Science, you need to be skilled with using tools that Data Science professionals employ as part of their jobs. This course teaches you about the popular tools in Data Science and how to use them. You will become familiar with the Data Scientist’s tool kit which includes: Libraries & Packages, Data Sets, Machine Learning Models, Kernels, as well as the various Open source, commercial, Big Data and Cloud-based tools. Work with Jupyter Notebooks, JupyterLab, RStudio IDE, Git, GitHub, and Watson Studio. You will understand what each tool is used for, what programming languages they can execute, their features and limitations. This course gives plenty of hands-on experience in order to develop skills for working with these Data Science Tools. 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. Towards the end the course, you will create a final project with a Jupyter Notebook. You will demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers....

Top reviews

DE

Aug 14, 2022

I love the detailing of every aspect of this course. The Labs, the free subscriptions and free trials provided by IBM Skills Network, everything has been so amazing. Thank you Coursera, thank you IBM.

MO

Apr 17, 2023

the best course for the beginner who is going to start his data science journey. This course tells you all options like tools, libraries, programming languages, etc. Highly recommended for beginners.

Filter by:

3626 - 3650 of 4,764 Reviews for Tools for Data Science

By Rui Y

Oct 12, 2020

The general introduction could be useful for beginner who is new into the tech industry. I would recommend to look at the sections first before start. If you know them already, please skip as it doesn't not provide anything new. In addition, why do I have to pay subscription fee to watch IBM training videos?

By Alexandru F

Jul 23, 2019

Decent overview of the open source tools used in Watson Studio. I would have liked a more hands-on approach, but considering that this course comes after the "What is Data Science?" introductory course, it fits the purpose of broadly understanding what Jupyter Notebooks, Zeppelin Notebooks and RStudio is.

By Joaquin G R

Feb 8, 2019

I changed my mind. This course is not so bad. I don't rate it 4-5 because I don't like the fact that the interface in IBM Watson Studio is not the same as the current one which makes it a little bit confusing and because some of the videos have audio issues and introduce some concepts without explantion.

By Jay A

Oct 23, 2020

In this one, I am giving a 3 star, not because of the course content. But because of the way it is delivered.

Without a proper introduction to various things such as Git or GitHub, codes are thrown at the screen suddenly. And it is confusing. Though a proper reading material comes at a much later stage.

By Rebecca A R

Mar 4, 2020

Instructions are not very clear at all and almost impossible to follow. Things took a lot longer than they should have just to get to where you needed to be. The work required was not difficult, but the lack of instructions on how to navigate and get where you needed to be was extremely frustrating.

By Necip F E

Apr 9, 2021

Learning about the frameworks and apps was nice. Watson Cloud is kinda cool. However, mentioning too many names in one video was sort of challenging and IBM tools part was sooo overwhelming (especially SPSS video was like taken from an advance tutorial and has nearly zero annotations on the visuals)

By Michael L

Aug 22, 2020

Week 2 was not very well produced. The IBM produced videos were very well done. Had to do some self-service poling around to get information that should have been presented in the course work. Each time I visit the IBM Watson studio it is a new exploration to get started on assignments/projects.

By Caroline V j a

Jul 3, 2020

The tools are at a very very high level and covers so much on machine learning. A beginner needs to learn about the basics of Data science before taking up a course on the tools. Otherwise it will not be of much use. It covers lots of machine learning terms which a beginner might not aware of.

By Bard F

Mar 18, 2020

Course has a lot of information which is outdated from the tools. This should be updated at least by a text file. Also note that the test tool does not work with a computer running linux which also should be informed.

Else the topic was great and the course was really interesting and compelling.

By Maciej H

Mar 24, 2022

It is great to see what tools are used for data science but some explaination on how particural nodes in the workflow work (from the mathematical/alghorithmical point of view) would be even better. The final exam was rather about learning things by heart than actually understanding the topics.

By Katlego M

Aug 18, 2020

The videos have no sense of continuity. There is also a section where the video lecturer who is showing us how to use jupyter notebooks is rushing through the tutorial and even gives a video lecture from his car. Not as professional as I would like or expect for something of Coursera's calibre

By Felipe J d L B

Nov 15, 2023

Average. The peer reviewed and screenshot-taking is a mistake, just get rid of it. Apart from that, the R Studio section is badly structured. You either explain the syntax and funcion of the commands or don't even bother asking people to type them in since they have no idea what is going on.

By Lukas L

Dec 9, 2020

Some videos were unclear. For example, the one where teacher were sitting in the car. I could feel that he was in a rush at the moment, and has to make a course at the same time. In some other videos repeated the same problem - speech was unclear and not all things were properly explained.

By Diego L

Apr 2, 2020

I got some problems with R Studio with https://labs.cognitiveclass.ai/ it stops several times so I decided to use the IDE with IBM cloud. The lesson was a little bit too much easy for me and a little bit boring maybe next time next time the course could use only tools present in IBM cloud.

By Clayton S

Feb 2, 2019

Very IBM centric but I guess you get that on an IBM course. However I was getting a few problems with some IBM sites until I upgraded my account (time outs/ errors etc) so I would suggest doing that using the free coupon - I think this issue is more prevalent in places outside the USA?

By Thinh N

Oct 2, 2018

At the end of the course, what you need to remember is that "we have a very useful platform for data science that is IBM Watson Studio". However, because it is an enterprise software, its price is very high. So you should end up using something else or be restricted in its Lite version.

By David B

Jan 27, 2020

A little disappointed this module of the course was only really markdown and focused a lot on IBM's products rather than actual technical code. However, I understand that others taking this course are most likely very new to coding and data science, and need an introduction like this.

By Melissa K

Feb 24, 2019

Course content should be updated for IBM Watson. No point in having tutorials to show you where things are when it looks different in reality. Also, I think the videos assumed learners had a baseline knowledge and just glossed over things that would have been nice to learn more about.

By Nachanan

May 23, 2020

The content of the course is shown to be widely-known in the data science field as there are many discussions in the internet regarding this topic. However, the videos in this course are not up to date which cause many issues in practical side of the course and also the assignments.

By Attila K

Nov 11, 2019

1) The course itself is way too fluffy. It's more like a marketing brochure of the IBM services.

2) And it's not even a good one as the name of the systems have changed, the way they are operating has changed, and you can not even do some of the tasks by following the course anymore.

By Peter C

Jan 19, 2020

The course was excellent to introduce the tools you have promised us. However the narrator of Zeppelyn Notebook and RIDE videos was not engaging enough. It would be more efficent and engaging if you can introduce those two tools in the same manner as you did with Jupyter notebooks.

By Alvaro L V

Mar 11, 2020

The content and resources for learning are excellente. However, I had a lot of problems for signing in the IBM cloud and it is impossible to contact Coursera for help. At last I managed to have my account, after some hours lost, and some emails sent directly to IBM Cloud helpdesk.

By stefania s

Dec 5, 2019

the third week was very tiring. the use of Watson studio was not intuitive and the videos did not explain well what to do. I lost a lot of time creating a project because I had a different configuration than the one shown in the video. I had to enable options that were not default

By Gabija K

Dec 18, 2019

The information is really bad, because it contradicts the actual functionality from the website. The material need to be removed and corrected. Now it's a waste of money, as all course explains how to use specific tools, while providing incorrect view.

Peer assignment was nice.

By Takudzwa G

May 11, 2023

The layout of the course feels cumbersome. At the end there will be hundreds of topics only hinted on and not explained. The course content needs to be reviewed for reduction. This could be a specialization on its own. However it does the job of introducing data science tools.