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Learner Reviews & Feedback for Tools for Data Science by IBM

4.5
stars
28,175 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.

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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4001 - 4025 of 4,596 Reviews for Tools for Data Science

By David

Oct 8, 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...

By Aakash K

Jun 11, 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.

By Guille C

Feb 17, 2023

Realmente el contenido es genial porque es progresivo desde un nivel de principiante, pero es muy frustante cuando quieres avanzar en un curso, y necesitas programas externos que son de pago, pero que para el curso se supone son gratis. Pues ahi es donde llega el problema, que cuando estas ya metido de lleno en el curso, te haces la cuenta para hacer los ejercicios que te mandan y ahora el codigo ese gratis que te dan para esos progrmas no es valido, y te piden la tarjeta de credito. Estoy en el curso a 96% de completarlo, y no me es posible poder mandar mi enlace de ejercicios a los demas compañeros, porque no me deja entrar en la plataforma a no ser que pague la cuota anual. Mañana se me acaba la suscripcion gratuita de 7 días, y obviamente despues de esto, no voy a pagar la cuota, porque al final no voy a tirar el dinero, para no poder sacarme nada. Imagino que a muchas personas les ha ido bien, yo lo he intentado intentdo repetir todo, y no ha sido posible.

By Sobhan A

May 6, 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.

By Hani H

Mar 9, 2022

The IBM cloud interface has been updated but the course material does not reflect that change.yet. It's a minor annoyance but this was my first introduction to IBM Cloud and trying to follow the steps was frustrating.

Also a lot of tools were quickly overviewed but there was hands on activities for only two of them. Some tools didnt load correctly for a while (couldnt edit Jupyter Notebooks for a couple of hours). The material felt siloed and unorganized and we were jumping from one topic to the other without spending time getting familiar with the applications.

It would have been a great idea to introduce a couple of data sets at the begining of the course, let the students get famliar with them, and run this data through the tools to see the impact of each one. The current approach made the tools seem disjointed and independent of one another

By Stephanie C

Dec 31, 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.

By Scott O

Feb 23, 2022

Good introduction to programming languages and useful development environments. However, the IBM Watson section felt like a long commercial for IBM products. That section makes you jump through a number of hoops to register for IBM Cloud, a service that requires a credit card to even register if you don't follow the free trial instructions that are only given after the video lesson telling you to sign up. If you follow the video instructions you can lock yourself out of getting a free trial because your email can only be assigned to one account. IBM/Coursera's advice if this happens is "use another email address". Beyond that the instructions for completing exercises using that tool are out of date and not generally correct. This one section was enough to almost make quit this whole course, really disappointing.

By Nichole K

Mar 1, 2023

I found the material difficult only because the videos were unorganized, often having multiple speakers in one video. Week 3 was a complete mess. I could not complete the lab exercises because IBM suspended my account (that had only just been created), but I'm not sure I could have followed along anyway because the videos did not match up to what the website looked like. Questions for the quizzes and final exam were extremely confusing, and I had to make multiple attempts to pass. The material just would not stick. I wish it had been presented more clearly. I am not sure of the relevance of the material, or how/where to use it. Weeks 1 and 2 seemed okay, but Week 3 as I said just went out the window. I was looking forward to learning more about the tools, but I still feel quite lost.

By Karen P

May 23, 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.

By Mark V

May 26, 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.

By Pimchanok W

Aug 21, 2022

In the Data Science Tools Chapter the content was poorly structured and I felt overwhelmed by the tool names thrown at me with no structure in the presentation. I even found that the tools given as examples are not actually relevant now and there are a lot more "popular" commercial tools that were not mentioned once in the chapter ex. PowerBI, Google Data Studio, AWS Redshift, Google Big Query. And the amount of times IBM Watson Studio had to be repeated in the course is pretty annoying. Like we already know what it can do, you don't have it repeat it 10 times. I think the content focused way too much on the IBM tool. You should've named this course IBM Tools for Data Science instead.

By Yousef K

Dec 25, 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.

By Aaron A

Sep 2, 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.

By Jay Y K

Nov 3, 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.

By Princess O

Jan 12, 2022

It was interesting at the beginning but along the way it became uninterestingly long and monotonous. Though the part explaining the IBM opening part was hard to follow as my free trial had expired and there were no more claim codes for the extended trial. Most of the reference points and labs were from outdated versions. So they didn't load as expected. I experienced multiple error messages while trying to open the IBM cloud account and navigating to the Jupyter notebooks. The IBM page was also glitchy. I was not able to get access to the extended trial claim code so I had to open a new account to do the lab works and exercises.

By Polychronis ( P

Oct 20, 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.

By Priyanka T

Jul 12, 2022

This course had several issues. First it was too much information for someone who has no background knowledge and therefore difficult to understand all the terms used without any examples to relate. Second, there were several audio related issues that were not resolved. I wasnt able to access IBM Watson Studio and even though I reported the issue I ended up losing marks on an assignment that required IBM Watson Studio which was no fault of mine. There were unclear instructions, graded assignments included content not taught the lab work (it wasn't mandatory to study the cheat sheet). Overall, disappointed.

By Matthew B

Jan 11, 2023

There are some very helpful parts of this course, such as those on using GitHub that helped me tremendously and were very easy to understand. That being said, there is so much of an emphasis on pushing IBM's products that it seriously hamstrings the course. Conditioning a point of your final grade on submitting through IBM Watson is a very silly thing when data science is such an open field with a multiplicity of tools. I understand this is an IBM course, but it's a cheap and slimy thing to make so much of the course basically an advertisement for IBM products. Our time is scarce; please respect it.

By Daniel A

Jul 29, 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.

By Jose A C

Apr 29, 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.

By Monserrat R

Jul 23, 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.

By Jay J

Sep 5, 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.

By Rachel M

Mar 2, 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.

By Shawn G

Apr 7, 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.

By Tânia P

May 13, 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