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Learner Reviews & Feedback for Tools for Data Science by IBM Skills Network

26,032 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


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.


Apr 12, 2020

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.

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3651 - 3675 of 4,249 Reviews for Tools for Data Science

By Suraksha S

Apr 2, 2020

Its a bit outdated

By Anton S

Jun 8, 2021

yaa mayan lah yaa

By Tandeka B

Apr 20, 2020

old information.

By Ritik k

Nov 27, 2019

outdated content

By Jonethan R

Mar 20, 2022

Outdated guides

By lavesh b

May 5, 2020

It is too basic

By Sandipan D

Nov 27, 2018

Videos outdated

By Yadder A

Feb 23, 2019

It's too easy.


Apr 22, 2021

Needs update

By Abdullah A

Dec 26, 2018

not clear it


May 26, 2019

good course

By Igor L

Oct 2, 2019

Too easy

By Farzan B

Oct 20, 2018

Too easy

By Nahim A R

Jan 21, 2023

Not Bad

By 손승건

Jan 16, 2020

not bad

By Sanket B

Jun 10, 2019

its ok

By Osama H

Jul 4, 2020


By Chakradhar K

Apr 7, 2020


By Omer Z C

Sep 30, 2021

By Humza A

Mar 1, 2019


By Dominic I

Feb 11, 2022

Outdated material that has not been updated...

The first week is mainly memorization with no hands on/interactive items.

The second week gets better, but the instructions are a bit outdated for JupyterLab functions such as the 'insert' tab which is nowhere to be seen. Items of the markdown lab simply don't work, as when it wants you to copy the html code to Jupyterlab the code is actually compiled into a link (hard to explain but basically means you would have to separately look into creating HTML hyperlinks).

The third week is mainly about IBM's own products such as Watson Studio, but the course is obviously outdated in this aspect with items being called different names and payment verifification required to simply creat an IBM cloud account. Sadly for me, any payment method selected was declined and so the process was highly frustrating.

The fourth week peer reviewed project was something that I had originally thought to be a compilation of materials earlier learned that would have to be put together and peer reviewed. It turns out that the peer review project requires skills that have not been covered in any other lesson/lab. Specifically elements of the markdown language like creating bulleted point lists, links, and the like.

I feel like this course should be labeled as intermediate just because it's outdatedness in many aspects would require a person to have moderate experience with tools/troubleshooting in order to get from beginning to end of the course.

Given the cost of this course (40 dollars a month as of the moment), I would not reccomend anyone else take it if they are planning on learning and enjoying the learning process. Instead I would reccomend only those who know how to troubleshoot outdated materials and simply wants a certificate.

For anyone else, although not completely related, I would definitely reccomend you go through free courses with free certificates on Kaggle as it is much more hands on and intiutive, with a much more advanced grading system that makes it not just easy but FUN to learn.

link to kaggle courses with free certification:

By Léonore F L

Jan 10, 2021

This course was presenting students with some interesting and rich information about the tools they could use, but it should not be the second course of the certificate already.

It is dealing with concepts that are far too complex yet for students who just started to learn about Data Science. These concepts are not properly described and students have to go through the course with only a partial understanding of some core concepts they would need to understand what is further explained in the course...

So many things are still really unclear to me now that I have finished this course. It took me quite some time to complete it because I felt demotivated. Now that I have started the next course on Methodology, I feel much better and I see what it is like to have things explained in a pedagogical way! Analogies, repetition, examples... All this is very important to help students navigate a topic as new and sometimes as foreign as Data Science. I was not convinced at all by this course "Tools for Data Science" and I do not think that the little knowledge I gathered will stick, as it is not built on solid foundations. I cannot be able to remember what tool will be useful for doing what if I do not know what I can / would do with data science.

The labs were good! A nice way to get proper training!

NB: I know this class is designed by IBM but when it comes to tools, it feels like the company is really pushing their tools to the center of the stage. They of course mention alternative options, but they are not dwelled on at all, and whenever they can give limelight to their products, they did it. It can leave students wondering on the impartiality of the course.

By Zachary G

Jan 17, 2019

I have stopped going though the IBM specialization after this course - this review is for beginners (like me), who have no coding/programming background. Coursera disappointed me because instructors are not there to help - you post questions in the forum hoping that there is a more knowledgable individual who will help you with your question. And if there is no such person, then your questions will not get answered by anyone.

Secondly, it mentions that course is for beginners with no programming experience, but then some codes, syntax and computer science terms get thrown at you without explaining basics and then videos are rushed through, leaving student only confused and frustrated.

Thirdly, courses lack consistency, clarity and are overall are very sloppy - information gets thrown at you from all places with no specific structure (if you had taken courses on CodeAcademy, you will understand what I mean).

Lastly, I was disappointed by some videos from Zeppelin Tutorials where all that instructor did was just reading text from main zeppelin page! I could do that by myself.

I am reverting to learning with CodeAcademy which was my original choice, but I thought that maybe IBM will be a good name to showcase on social profiles. IBM here does not mean anything.

By David

Oct 8, 2020

A lot of information given about the different softwares (open source or commercial tools) and the different processing steps. The Jupyter Notebook section is fine whether used on the IBM platform, from Anaconda or from a bash terminal. I spent more time than necessary to get familiar with the tools as I found some explanations really bad. Thankfully I used a lot of command lines at work to navigate through our system so I was able to survive through some of the poorest tutorials.

The RStudio section is horrible and mainly useless with no explanation whatsoever on what is done (you just have to type what you have been asked with no questioning as anyway there is no answering). That was bad but wait to see the Data Refinery section. I wonder how a video like that could be published by IBM.

At the end, I will extract and use the information relevant to what I want to do and forget about all the rest. This course is about teaching people about Data Science not about mainly promoting IBM Cloud Pak and its suites of softwares. IBM should clean up this course by removing the poor quality tutorials and update the videos as their platform and tools have changed quite a lot. I am now hoping that the Course 3 gets better...

By James R

Mar 25, 2023

This seemed like more of a sales pitch for IBM products than a course. Also, it covered products such as IBM Watson Knowledge Catalog that have been discontinued. Overall the course seems outdated.

Many of the questions on the quizzes don't ask for actual knowledge, they just ask for knowing the correct names of different products. Questions are sometimes worded vaguely and almost impossible to answer (e.g. asking an "either or" question and then offering only "Yes" or "No" as the choices).

Finally, the final assignment was a joke. They require you to take, save and then upload eleven individual screenshots of individual cells in a Jupyter notebook. This takes forever and it's completely unnecessary since you also provide the entire notebook in a public GitHub repo. It's just a waste of time and disrespectful of the learner. They also don't make it clear whether you should screenshot the cells as raw code, or after they are executed. On top of that, the assignment itself is facile; you're just supposed to copy and paste some markup and do a few simple arithmetic operations.