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

4.5
estrelas
22,741 classificações
3,570 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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3126 — 3150 de 3,571 Avaliações para o Tools for Data Science

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.

por Stephanie C

31 de Dez de 2020

There are a lot of inconsistencies here. The quality of the pedagogy is generally abysmal to merely lackluster, production values on some of the videos are very low (I'm looking at you, series of poorly organized screencasts with mumbled and heavily accented, rambling narration). The final certificate says the course is three weeks of work when it's actually four. In the end, I passed with full credit but other than the guides to connect Jupyter to GitHub and then Watson Studio to Github it was all by dint of what I knew before I entered the course and not because of anything I learned in it. But it is useful to have those tools connected so it's worth doing that. I find it hard to believe this is 1 of 4 courses in one of the most highly-reviewed specializations for Data Science, though. Hard to believe and disappointing.

por Karen P

23 de Mai de 2019

There are lots of technical glitches in this one. Quizzes in a video before you've gotten to that information, missing links, places that ask your thoughts on something that really doesn't need thoughts, etc. I think it's also misplaced in the series. It assumes that you know a lot more about data science than you do if you've just watched "What is Data Science?" They talk about some great resources for writing in Python, R and Scala, but you haven't yet learned them if you take this as the second class in the series. I think there's probably a lot I didn't pick up on, simply because I didn't have the base that knowledge needed to build on. It might be a great class (if they fixed the glitches), if placed elsewhere in the series.

por Mark V

26 de Mai de 2021

I did not enjoy my time taking this course. There is simply TOO MUCH information, and it rarely gets expounded upon. I often felt like I was just getting information dumped on me, such as listing the various Python or R packages we MIGHT use one day. Additionally, videos would often use data sets as examples but would fail to explain their context and don't seem to provide the data sets to work with on our own. This wasn't the case for the entire course. I enjoyed Week 3 where we spent a significant amount of time on one thing, such as jupyter notebooks or github. Instead of being told how something worked, we were able to play with these tools ourselves, and as a result I feel that I learned SO much more.

por Yousef K

25 de Dez de 2020

This course leaves you doubting whether you can become a data scientist rather than providing you with brief knowledge on data science tools. I think it needs quite a bit of restructuring because concepts are explained in videos as if they are being explained to computer scientists and engineers rather than newcomers to the world of data science. Nevertheless, I'm glad I was able to get through it and move on to other courses in the certification that actually matter. My advice for you: don't worry about the complexity of the material and don't waste your time trying to understand the details because it's simply not worth it. Just get a grasp of the essentials and move on.

por Aaron A

2 de Set de 2020

A good overview of tools that are common to the field. The videos are just plain horrible. The narrator does not explain anything that he is typing on the screen, he makes frequent mistakes, and parts of the screen are not even visible. One video shot showed the narrator recording the video from the driver's seat of his car! Quality needs more focus. Also, the explanation of some of the labs are confusing and many many many students encountering similar errors...but when looking at that discussion forum, staff just cut-and-paste same unhelpful message to everyone. I guess you either figured it all out and make it through the course, or give up in frustration.

por Jay Y K

3 de Nov de 2021

Part for Git was really great. It has provided me good overview what it is and how I'm supposed to leverage it at basic level, so it was very useful. Part about Jupyter Note was also good, part for R was alright, mainly because I'm not much interested in R anymore. But then too much time has to be spent for IBM tools. I understand that these courses are constructed by IBM and they would like to leverage it to advertise their tools. However, from learners perspective (presumably most of us are just beginner in this field), IBM tool part was just an overkill, way too much. I probably will prefer those courses provided by universities more moving forward.

por Polychronis ( P

20 de Out de 2018

Outdated lectures and low quality videos. Owful monotonous narration (puts you to sleep). It is as if IBM & Coursera are trying on purpose to put people off Data Science. :-)

The 1st course of this specialisation (What is Data Science) was truly educational, fun and easy to watch thus to understand and remember what you have learned. This course is the opposite.

IBM & Coursera people, the fact that someone is a super duper scientist doesn't automatically qualify to be a teacher nor a narrator, and please IBM, do improve the quality of the videos with better graphics and enriched material. We know that you can afford to do so.

por Daniel A

29 de Jul de 2020

The first course in the IBM Data Science Professional track was excellent. This one is not.

This particular course is dry compared to the previous one. It’s difficult to pay attention when many of the videos are a boring presentation of dozens of data science tools. Week two is less dry but is poorly organized and needs more explanation and refinement (poor audio quality, lacking descriptions). There are also videos which are essentially repeats (cover the same information) of the previous course but of worse quality. Overall, this course lacks refinement and organization, and is not worth paying for.

por Jose A C

29 de Abr de 2020

The content is a good intro into the tools that you are gonna use in a data career. However, I did have two major issues here where:

1) As IBM moved to Watson Studio from Data Science Experience, this did create some of the visuals and knowledge a bit outdated.

2) There was a massive disconnect when you have issues working Watson; especially with signing up and logging in. I see that this was a huge issue since then (judging by reading the discussion sections of the course) and this (along with my first point0 should definitely be discussed if you want this content to still provided.

por Monserrat R

23 de Jul de 2020

It is a very quickly course, the week of the open source tools it's seen really quick, you can barely understand anything and they put three different tools in one week, if you really want to learn them search another course; it is also a big propaganda for de IBM tools, and they put so much more effort on selling you the idea that their products are really necessary that in actually introduce you to the tools that a data scientist use, and its so hard to understand if you don't speak english as your mother language, hope that with time they can fix it.

por Jay J

5 de Set de 2019

This course is not good. It has taken me several times the amount of time specified due to the outdated videos that no longer represent the tool as provided. Struggling to get simple markdown commands to work in the notebook, but I successfully executed them in the previous toolset. Several back and forth's between the actual work and the videos is very aggravating. It would be nice if you at least provided some printable instructions. I feel that I have gotten off track and may not be able to find my way back to a normalized starting point.

por Rachel M

2 de Mar de 2021

Very patchy. Some of the videos were quite informative but the practical exercises were a real problem. Often the instructions were impossible to follow as the software must be a newer version than that shown in the instructions. I had to Google for the latest instructions. Also the practical exercises rarely told you *why* you were learning anything; it said "type in this code" but you didn't understand the code. I was able to finish the course but only through sheer perseverance (and Googling for instructions) - it was not enjoyable.

por Shawn G

7 de Abr de 2020

This course at one time would have been great. However, for myself and many others (based on numerous discussion posts during my time taking the course), there was a multitude of technical errors and outdated training. Zeppelin Notebooks was not a working functionality in the IBM Skills Network, and most of the walkthrough guides were unhelpful due to updates in the tools being showcased. The course is in need of some serious updating to catch up on many changes that have impacted the tools covered in this course.

por Tânia P

13 de Mai de 2020

Material in this course looked like part of something else. It's a beginner's course but suddently I'm faced with a lot of technical jargon with no explanation. I supposed to experiment with software and code I've never seen or know how to interpret and I'm just suppose to run it to see what happens. I have no idea what I was supposed to learn from it. Week 2 was demotivating and added nothing to my knowledge. This week was an absolute loss of time. I still learned something from week 1 and 3

por Gus D

16 de Abr de 2021

give one plus star with benefits of the doubt. If the course gets better in next courses but this is a shame. I can deal you promote IBM services and products, no matter with that, but you only give ALL the tools existing in the data science world and meanings, but with no knowledge is a none sense. Hope you improve, Basic stuff for analytics, statical or regression models, clustering I have no clue what they are. But well the name is tools for data science. No how to use them or what for.

por Shashank R B

11 de Mar de 2019

The course needs to be updated. Especially the IBM Watson Studio section is something which needs to be worked on again. The site they refer to has hanged completely. IBM site was not user friendly and caused a lot of confusion. It took a lot of time to figure it out. This problem is not isolated and there have been a lot of users who are struggling to figure out how to solve it. This causes additional problems as the final assignment depends on getting started with the IBM website.

por Jennifer S

30 de Jul de 2019

Overall intro for open source tools that could be four stars if updated for current layout and usage of its star tool, IBM Watson. The inaccurate videos for Watson make this course very frustrating, and moreso because the final, graded project is expected to be completed on Watson despite the course's acknowledgement that the lectures need updating for that tool. It's doable, thanks to the other students posting tips in the discussion forums.

por Davy D

17 de Mar de 2020

5 stars for the first two weeks, but the week about Watson is just terrible. The discussion board is full of complaints.

IBM should not promote itself this way.

Coursera should not spread this content and charge for it. It's a rip off.

The videos are totally outdated and it took literally hours and looking on the discussions on how to get to the point that I could do the application and the final assessment. IBM wasted my valuable time here.

por An N

18 de Mar de 2020

I am personally found it very difficult to create a notebook on IBM Watson because course take the tutorial videos from IBM Watson itself without checking whether there is any updates where the UX changed significantly. I have to research Google and forums to find out the ways to create a notebook on IBM Watson. I hope that this review will help the authors of the course find it easier to update the course content.

por Maulik M

7 de Abr de 2021

Too much lip service to too many tools. After the first course in the specialization sets expectation that no tech or programming skills are essential as pre-requisites, this course comes along and introduces in the briefest possible way a plethora of tools.

The course will benefit by focusing on only IBM tools and one example from the open source world rather than the mention of so many tools all around the place.

por Douglas M

3 de Out de 2018

Well structured layout and solid indications of what the knowledge necessary for a learning path to data science. Which is appreciated as there is a lot information out there and difficult to filter out the noise. The course however is very light and lacks some real educational information. The content would need to be 'beefed' up considerably. And more rigorous quizzes and questions needed.

por Vaughn C

15 de Ago de 2020

A lot of good information here which should have been rated higher, but everything took so much longer than it ought to have, because it was so poorly presented. The materials are outdated (or missing/difficult to find with the IRIS dataset) and difficult to follow. The course needs a complete update and overhaul by someone who understands online learning and user interface/user experience.