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Learner Reviews & Feedback for Tools for Data Science by IBM

4.5
stars
29,295 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.

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3726 - 3750 of 4,789 Reviews for Tools for Data Science

By Julia M

Feb 6, 2020

I think that this course needs to be re-engineered. The videos are outdated and the videos jump right into the programming without explaining why you are typing out this code. It is not a course for beginners.

By Nanthakumar N

Jun 23, 2019

This course needs update. The current IBM environment and Tutorial examples are not matching and confusing. It also leads to crate multiple account with IBM.

Otherwise good intro to the tools and environments.

By Felipe J

Feb 4, 2019

Interesante porque dan un panorama general acerca de Jupyter, compilación y lenguajes que soporta como Phyton y R. Al ser un curso ofrecido por IBM la herramienta para las tareas es de ellos, Watson Analytics.

By David H

Mar 29, 2020

A good overview of the various open source tools available. The videos, however, did not always match the material which made it confusing here and there. I am aware they are currently working on fixing this.

By Mitchell L

Aug 24, 2020

this course had a lot of items that I did not feel were beginner level. Most of the labs involved some coding, or language that was not discussed prior to the labs. I felt lost multiple times in this course.

By Md N

Aug 27, 2021

The resources are very helpful, but the commentary sometime does not always helpful. Sometime the commentator missed to announce the new slide title, or go goes not give pause while going in the next slide.

By aniss L

Dec 7, 2020

Good course and training however it gives huge information about many tools, beginners could be easily lost in my opinion, the course should focus on the main data science tools such as : Python, Sql, R.

By Zareef J

Sep 12, 2020

Please try to make more details lecture on specific IBM data science tools and short brief for others rather than short brief for every tool. Six to seven week video lecture will be better in my opinion.

By Eugene N

Mar 20, 2020

I think the tutorial for the IBM watson studio needs to be updated. The tutorial was on data science experience (DSX) which isn't available on the website. This made this part of the course hard to follow

By Eduardo d M R

Jan 3, 2020

Course needs an update: still working with the old platform. It gets you confused when you log in and see that they now work with IBM Watson on one screen and screenshots of the old platform on the other.

By João P P C

Aug 9, 2022

The weeks 2 and 3 serve more as a commercial catalogue for IBM than to learn Data Science. I'm keeping strong in order to claim the professional certificate, but this course was tough and disappointing.

By David C

Jun 20, 2019

The video lectures are outdated and are in dire need of updates. I found myself lost at times, as the current version of Watson does not match the version shown in the lectures. It was a bit frustrating.

By Collin P

Sep 18, 2024

Its a lot of good information, but it's a bit of information overload. Although I managed to complete the course, I don't feel like the setup enabled me to absorb nearly as much as I would have liked.

By SHAONI C

Sep 25, 2019

videos are someway useful. But I have faced difficulty to find IBM Watson Studio. The Link that was shared in the videos are not directing to the actual watson studio link. Please add the actual link

By Дарья Г

Jan 19, 2021

This course is announced as a course for beginners without previous background in programming but it contains information related to the list of programmes that we are supposed to be acquainted with.

By chand s

May 7, 2020

the course need to be updated. some of things are explained easily but as a beginner it takes lots of time for to understand things. It will be beneficial to the beginner's if the course is updated.

By Sanzio G N

Mar 2, 2020

It is just a marketing for IBM's cloud platform. Plain and simple. However they introduce someone who NEVER seen anything in programming to start looking for available tools. Very shallow knowledge.

By Miloš F

May 16, 2024

Too much info. Good for overview, but impossible to remember it all. Some quiz questions should be revised e.g.: Question 2 Is Keras a machine learning or deep learning library for Python? (Yes/No)

By Erik G

Nov 28, 2022

Instructions for IBM Watson are outdated. Would prefer more content on doing work in Jupyter notebook rather than watching videos and answering quiz questions. Learning in accomplishing by doing.

By Cristhian S

Aug 13, 2019

Sometime I feel that I am lost in those videos about R and Zeppelin. One video starts doing something like uploading a file and the next one makes the overview of the tool when it should be first.

By Xin W

May 31, 2019

Introductions are quite brief and assignments are not challenging. You may need to spend quite extra time to really get to know how to use there open source tools. But still a good way to start.

By Peter F N

Aug 28, 2018

Very useful course, great way for anyone to familiarize themselves with open source data science tools. The videos are outdated, however, which made it difficult to do the assignments at times.

By JOAQUÍN M

Jun 13, 2023

Se debería de facilitar documentación bien estructurada y editada, en pdf de todos los contenidos del curso, no sólo las transcripciones que además muchas veces están mal traducidas. Gracias.

By Ellinor G

Jan 28, 2021

This is supposed to be a course for beginners but the amount of advanced concepts and tools they throw at you with no explanation is staggering. A pity because otherwise this could be useful.

By RenRen4 M

Dec 5, 2020

I found the majority of the videos to be pretty boring. I think more practical exercises, with actual goals, rather than purposely importing or copying random code, would improve this course.