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Voltar para Tools for Data Science

Comentários e feedback de alunos de Tools for Data Science da instituição IBM

4.5
estrelas
21,550 classificações
3,329 avaliações

Sobre o curso

What are some of the most popular data science tools, how do you use them, and what are their features? In this course, you'll learn about Jupyter Notebooks, JupyterLab, RStudio IDE, Git, GitHub, and Watson Studio. You will learn about what each tool is used for, what programming languages they can execute, their features and limitations. 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. To end the course, you will create a final project with a Jupyter Notebook on IBM Watson Studio and demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers....

Melhores avaliações

AJ
15 de Set de 2020

Absolutely Loved this course!! Challenging at times to keep up with all the terms and processes. The course provided great insight into Data Science. Would highly recommend it as your first course.

RR
24 de Abr de 2019

To the contrast of other reviews, I find the content very well bifurcated and fed to the learners. The course very easily digestable and I have had a great amount of fun learning it.. Go for it!!!!

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2876 — 2900 de 3,304 Avaliações para o Tools for Data Science

por Siobhan S

22 de Set de 2019

Needs to be updated

por Arun K A

16 de Mai de 2019

Videos are outdated

por Chirag G

1 de Fev de 2019

Course is outdated.

por Suraksha S

2 de Abr de 2020

Its a bit outdated

por Anton S

8 de Jun de 2021

yaa mayan lah yaa

por m B

20 de Abr de 2020

old information.

por Ritik k

27 de Nov de 2019

outdated content

por lavesh b

5 de Mai de 2020

It is too basic

por Sandipan D

27 de Nov de 2018

Videos outdated

por Yadder A

23 de Fev de 2019

It's too easy.

por JM E

22 de Abr de 2021

Needs update

por Abdullah A A

26 de Dez de 2018

not clear it

por RITIK K

26 de Mai de 2019

good course

por Igor L

2 de Out de 2019

Too easy

por Farzan B

20 de Out de 2018

Too easy

por 손승건

16 de Jan de 2020

not bad

por Sanket B

10 de Jun de 2019

its ok

por Osama H

4 de Jul de 2020

nice

por Chakradhar K

7 de Abr de 2020

cool

por Humza A

1 de Mar de 2019

A

por Léonore F L

10 de Jan de 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.

por Zachary G

17 de Jan de 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.

por David

8 de Out de 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...

por Aakash K

11 de Jun de 2020

This is supposed to be a beginner level course. In the introduction, it was clearly mentioned by you that no-prerequisite knowledge is necessary. This course was taught to us as if we are already some professionals in this field. A majority of the explanations went above my head. Also while demonstrating the registration to the tools, please ensure you update your course. The current version we are using and the version of the tool at the time of recording are quite different. You need to literally scratch your head in trying to understand.

For example, while using the Python environment in Jupyter notebook in Watson studio, your tutorial clearly shows us to select the Free version of the tool. But when I tried, there was no free version of the tool at all. I was given 50 units of asset after which I would be charged. Please upgrade your tutorial.

By looking at this course, I am not sure if you would focus on one tool at a time. Assimilating this much information for a beginner level learner is something un-comprehendable.

por Sobhan A

6 de Mai de 2020

I can say overall it's a good program. However by reviewing the first few courses, you will get a headache, but the rest courses are very useful. Some parts are really useless for a data scientist and are more useful for programmers, which I recommend you do not put a lot of time on them and skip them as much as you can.

Apart from the material, I think this certificate is really useful for you to get a job. But, if you just want to learn new concepts in data science and do not need a certificate, I recommend you to take other courses other than IBM. There are very good courses on @linkedin Learning.

In this program, IBM pushes you to work only on its platforms which is really annoying and I think this a considerable drawback of this program.

If you spend at least 4-5 hours a day, you'll be able to complete it in 2 months. The subscription is monthly and it's around $50 CAD and you can unsubscribe whenever you want.