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Learner Reviews & Feedback for Tools for Data Science by IBM

4.5
stars
28,855 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

FC

Invalid date

It would be nice if you could update the material since some tools have changed either name or the way they look compared to the videos/images. Very good material though, I enjoyed the course much.

FD

Invalid date

Some of the lab assignments had instructions that didn't line up with how the programs actually worked. This was particularly the case for modular flow where auto-numerics seemed impossible to use.

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4101 - 4125 of 4,730 Reviews for Tools for Data Science

By Chirag G

Feb 1, 2019

Course is outdated.

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Its a bit outdated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outdated content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Outdated guides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Videos outdated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.

By JM E

Apr 22, 2021

Needs update

By Abdullah A

Dec 26, 2018

not clear it

By RITIK K

May 26, 2019

good course

By Aditya G

Jun 26, 2024

not great

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 Aurobinda B

May 19, 2024

good

By Osama H

Jul 4, 2020

nice

By Chakradhar K

Apr 7, 2020

cool

By Omer Z C

Sep 30, 2021

By Humza A

Mar 1, 2019

A

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: https://www.kaggle.com/learn

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.