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

4.5
stars
25,782 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

ED

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.

GC

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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3151 - 3175 of 4,181 Reviews for Tools for Data Science

By Angela W

Jan 28, 2020

The course videos need updating. I, and other students, have wasted a lot of time trying to follow the out of date materials, not to mention the confusion and frustration that it creates. If the materials were kept up to date, I would have left a five-star review.

By Karen M

Dec 18, 2019

First two weeks were to the point and good introductions to Jupyter Notebook and Zeppelin, but the third week tutorial on IBM Data Experience is so out of date as to be useless for being able to set up a new project and complete the assignment. Very frustrating.

By Sangeeta D ( P

Oct 3, 2021

Jupyter Notebook module was explained well however other tools like SPSS Modeler were a little difficult to understand for me. While explaining some of the examples in Watson Studio, it main objective / problem of the project wasn't explained in the beginning.

By Laila

Jul 15, 2020

The first two weeks of the course are poorly explained and don't have regard for total beginners. It gets really disappointing in week 2 where the quality of the videos and the structure of the lecturer is really poor. However, weeks 3 and 4 things get better.

By Reinhard H J

Oct 4, 2019

It's comprehensive enough, but should include more exercises for programming. I don't think it was necessarily the right decision to make this course come before programming, but it should accompany programming. It was alright with respect to content, however.

By Amy M

Dec 3, 2019

The videos and instructions on this class were terribly outdated. Despite the warning provided at the beginning that the videos were out of date, this is still unacceptable. It takes very little time to make a video of the quality and length in these courses.

By Evgeniy G P

Jan 17, 2022

Terrible experience with the IBM Cloud platform. An account is needed in order to achieve the final assignment.

At first they deactivated my account without any reason. Then, due to an error on their side, I had to spent 2 days in order to create a new one.

By Amanda C

Dec 18, 2019

This course has a good introduction to some online, open-source tools. It does not really discuss the drawbacks of these tools or their real use in industry. The test questions are detailed "gotcha" questions and not aimed at true comprehension of material.

By Varun V

Oct 17, 2018

Lots of videos are outdated as the tools (Both CognitiveLabs/Datascientist workbench AND IBM Watson Studio) have gone major updates and it was very difficult to follow the video tutorials. Unless the videos are updated, I cannot give a better rating than 3.

By Bob D

Sep 14, 2021

Production quality on the videos was not what I would expect for a professional qualification from a reputable company like IBM. Content was okay, but focused heavily on the IBM suite of services, making it feel more like an infomercial than a tutorial.

By Denzel J S

Jul 17, 2020

I was pretty disappointed with the weeks of this course. Not only it lacks 'on-hand' tutorials but the vagueness of video lectures, lack of instructions for beginners. A total downer for amateur beginners whose looking into the world of data science.

By Deleted A

Dec 23, 2019

Some material needs to be updated. Even though it has been clarified at the beginning of the course, many things have changed and the videos and reality are different. The concept is the same of course but it causes confusion among students.

Thank you

By Fernando R

Jul 14, 2020

A decent enough intro to some of the tools, specifically Jupyter notebooks. Week 1 just mentions a bunch of technologies without going into much detail. Week 3 is in my opinion a waste of time as it functions mainly as an infomercial of IBM services.

By Stephen C

Feb 22, 2022

Some issues with lab instructions not lining up with current version of the IBM cloud platform. First sections just kinda listed heaps of tools in way too much detail - later weeks were helpful in their focus on one or few immediately useful tools.

By Mandar V P

Apr 11, 2020

Last part is not updated. The videos and notes are of the old version of IBM Watson, hence the interface of the thing is just about completely different from the one shown and taught about in the lecture. IBM should change the videos and notes ASAP.

By Devon H

Mar 20, 2020

Technical challenges given differences between what was presented and what was found for exercises. In some cases steps didn’t render student getting the required options to complete all aspects of the assignments and/or took a lot longer to finish.

By Manish P

Dec 27, 2019

Multiple creation of logins was confusing. A lot of time was spent figuring out the links. Changing the name from Data Experience to Watson Studio probably led to some of it. Hope you guys streamline the steps and videos to match with what shows up.

By Haim D

Mar 13, 2019

I feel that I could have benefit much more from coding more with Python or R. I feel that all I know is how to activate the tools, and run scripts that are already written. I would have liked more time to practice the tools, facing real questions.

By Vincent Z

Jan 8, 2019

The course does a good job of showing the some available free tools for data scientists. However, I still haven't the impression of having learned any data science yet, after two courses in this specialization. I hope the best is still to come.

By Chris L

Oct 15, 2019

it is good to know there is a lot of free tools out there but it is not very practical. in reality, you will most likely use one tool and excel in one language, having tons of tool in the box does not mean having the equivalent in your brain.

By Juan D C G

Sep 20, 2018

The course is OK, the problem is that IBM tools seem don't work every time. I had to open 3 accounts with different e-mails to get to work with Watson Data Studio. The videos explaining how it works are outdated and don't correspond anymore.

By Christina T

Feb 6, 2021

A lot of information is thrown at you at once and really isn't explained other than that they are tools for data science. It would be easier to follow along if other random facts about them that aren't related to their purpose was removed.

By frank s s

Oct 1, 2018

I found some of the lessons hard to follow. The web page has been updated but the class has not. I still enjoyed the class and learned some valuable information but it would be nice if the data being taught was current with the webpage.

By Anas A

Feb 23, 2022

The course is rich in information, but in my opinion it shouldn't be the 2nd course in the IBM Data Science Professional Certificate. It should come later when students are more familiar with the different steps of data science projects.

By Henrique M

Jul 24, 2020

The course did not present didactics at the same level as others Coursera courses. The mix of IBM tools for training in the same space as the service sales environment makes learning confusing. The exercises on the tools were very basic.