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.
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!!!!
교육 기관: Josep R C•
Some information is not updated and a huge amount of time is lost in trying to figure out how to do simple things just because of the platform they are telling you to use. However, you can find useful information in the forums as all students have similar problems. I would just recommend this course to users who do not know tools such as Jupyter notebooks already.
교육 기관: Shushu S•
a huge part of this course is in IBM products. I will not work with them but still have to learn for pass the quizes. To be honest, you should call it "IBM Tools for Data Sciense" in addition, IBM changed the UI and the course still has not been modifiyed, so somtimes it takes a long time to find what you need
교육 기관: Kathryn D•
The second week of this course is so confusing and difficult to follow I almost dropped it. The third and fourth week were much better organized. The second week should be deleted from this course, it was not helpful at all.
교육 기관: T C B T•
A clear explanation of every tool required. Too advanced for beginners in data science.
교육 기관: Hellman O•
These materials should be updated to the current Watson work environment
교육 기관: Shuang.W•
the videos about Watson lab are out of date.
교육 기관: Robert H•
A real disappointment, one of the worst courses. I don't believe IBM has released anything like that.
week 1 - introduction to Python, R and SQL are pretty good and interesting; second part is about other data science tools which is just a confusing list of tens of different programs without any further information thus you will hardly remember anything; the last part is a strange mix of technical details again with hardly any benefit and confusing for people without IT background
week 2 - here comes the best :-(
no clear structure; totally ignores the skills of learners
does not introduce the basic concepts but dives into technical details like a command shell
presenter uses tools that have never been introduced (Anaconda)
video is cropped so that you do not see which menu is clicked at the top
you are asked to use tools but no info about how to launch them
included scripts run into partial errors - there is no explanation in the videos whether it is OK or NOK
videos are recorded in a car as if this were a FaceBook motivation video, with the appropriate noise of cars in the background
quizzes asking questions that will be discussed far later (if at all)
presenter asking you for giving starts on GitHub for his terrific work :-)
hands-on lab is just like “copy this looong script and it will draw a map” - uff - and what does it give the student...
Sum up - week 2 is a total waste of time. You can learn this anywhere else and much faster. This part just disgraces IBM.
week 3 - well structured and interesting, if you accept that it is mainly promotion of IBMs products; and not much information is included; when there is something interesting (data refinery) it is so fast and misses further explanation, so that you will be lost again; btw - subtitles not matching the video :-(
Sum up - shame on IBM
교육 기관: Hakki K•
I completed entire program and received the Professional Certificate. On the Coursera link of my certificate "3 weeks of study, 2-3 hours/week average per course" is written. This information is not correct at all, it takes approximately 3 times of that time on average! I informed Coursera about it but no correction was made. It should be corrected with "it takes approximately 19 hours study per course" or "Approx. 10 months to complete Suggested 4 hours/week for the Professional Certificate".
Here is the approximate duration for each course can be found one by one clicking the webpages of the courses in the professional certificate webpage: (*)
Course 1: approximately 9 hours to complete
Course 2: approximately 16 hours to complete
Course 3: approximately 9 hours to complete
Course 4: approximately 22 hours to complete
Course 5: approximately 14 hours to complete
Course 6: approximately 16 hours to complete
Course 7: approximately 16 hours to complete
Course 8: approximately 20 hours to complete
Course 9: approximately 47 hours to complete
This makes in total approximately 169 hours to complete the Professional Certificate. As there are 9 courses, each course takes approximately 19 hours (=169/9) to complete.
교육 기관: Hoseok Y•
I'm very disappointed by these courses. I'm not sure if the other courses are going to be similar but so far the courses has been filled with unexplained jargon and lessons where the instructor is working on a dataset that isn't provided in advance. I'm not sure if I'm supposed to be finding these datasets on my own before but I have no idea where to find the exact dataset the instructors are using.
From my understanding, these are supposed to be introductory courses which should mean that they take the time teach you on a granular level about what they are talking about. Instead, instructors teach as if you should already know the technical terms and don't explain anything. They walk you through what you're supposed to do without explaining the reasoning or what the process is achieving. It feels like they don't really care about the depth of the education.
Feeling kind of ripped off. I really hope that the rest of the courses are not like the first two courses.
교육 기관: Aarushi S•
I appreciate the efforts that were put together in the course, and I have had very good experience with IBM courses in the past. However, was a bit disappointed with this one. The videos for IBM Watson Lab were outdated, which resulted in a lot of wastage of time to submit the final assignment*. Also, it does not make sense for students to compulsory learn IBM software and use it for assignments. Basically had to learn an extra software which we did not even sign up for. As part of IBM professional certificate, I think it was a bit redundant and can easily be made part of a Python beginner or Data Science beginner course.
*Faculty were helpful to point this out and point a step by step procedure for the updated version. But this was in the discussion section, and also immediately makes having watched the videos completely futile.
교육 기관: Carlo P•
The worst course of the IBM Data Science Certificate. It does not have the typical quality standards of an IBM course:
- The explanation is very poor, disorganised and very below IBM qualities (even below basic standards)
- Some videos have terrible audio because they are made in the instructor's car
- The teaching lacks consistency and logic: for example, (1) the instructor uses SHH keys but he explains how to make an SHH Key only 2 videos after (he says "I'll tell you how do it later"...); (2) Staging is not mentioned during the videos, but it is requested during the test for week 2 GitHub.
- The instructor takes way too many things for granted.
- Too many topics done in a very superficial way
Do not attend the course if you are not obliged (you are studying for the IBM data science certificate)
교육 기관: Ilkin A•
For the people who is interesting about taking this course , I will share my real opinions in order not to waste their time and money. 1) This course has not been designed to teach you something it is more about the IBM services. 2) Do not expect that something will be explained in more detial. 3) Especially who does not have any programming background will not understand anything at a specific part of course. 4) Especially during the second week, everything that a person explained in the videos were usefullness becuase if you do not know how to write a code there will be no meaning for you. Even if you know how do coding the sequence or the topics which explained during the 2nd week were just nothing ( no meaning). I can tell a lot about the course. BUT COMPLETELY NOT RECOMMENDED
교육 기관: Cecile•
HORRIBLE course. Outdated and boring tutorial videos where you learn nothing except to know the existence of IBM tools that I suppose IBM is trying to promote through this course. The videos were made in 2016 and are completely outdated so you can't follow any of the instructions. The tools themselves are extremely buggy: out of 10 clicks, 6 will end up in an error message. They are not intuitive either. There's no way those tools are used in professional environments.
The 5 stars reviews must be fake reviews from IBM staff. There is no way any genuine student would give 5 stars to such a crappy course.
Look at the forums' comments and complaints before paying for this.
Really shocked that Coursera allowed such bad courses on its platform.
교육 기관: Derek A•
I don't think this course is any good at all. It crams all the different workstations at you giving you tasks to do in each one. Without actually building projects or seriously using these workstations, by the time you need to use them for a project the retention on how do navigate and use them are going to be low. I have totally forgotten how to use RStudio and what Spark is and I am on course 5 of the IBM cert because it hasn't been used since this course. I believe in a stand-a-lone when I need to refresh, this will be good to go back to but seems kind of pointless in the beginning of the Data Science IBM cert.
교육 기관: Moritz S•
I have enjoyed the other courses in the IBM Data Science certficate very much, but this one was very poorly designed and it felt like a collection of resources from other courses that didn't fit the need of this specific certificate/course. First, there were sheer endless lists of data science tools, without much context, explanations and examples. Then, there were some more practical parts on basic tools, but the instructor rushed through them (seemingly) without much preparation. It still taught me a few things (by pausing and trying stuff out), but I feel like this could have been done much better.
교육 기관: Maciej M•
The only objective of this course is to push IBM Cloud and Watson Studio on the learners. The software is highly dysfunctional and user unfriendly. I can't submit my assignment due to unclear instructions and errors that come up when I try to do so. This is so far the worst part of this whole course. I have found a forum link with some troubleshooting which I have fruitlessly searched for an answer, maybe somebody will find something there: https://www.coursera.org/learn/open-source-tools-for-data-science/peer/xakrA/create-and-share-your-jupyter-notebook/discussions/threads/G7ITBorwEem4khKVBn768g
교육 기관: Andrew C•
I regret the low review, but this course needs A LOT of work. Instruction is poorly formatted and (seemingly) lazily and sporadically delivered. This is supposed to be a beginner level course with no prerequisites, however, I wonder if newcomers to the course (and this cert overall) should be equipped with some other courses or specializations/certificates before entering this one. Thank you nonetheless for your effort, and I hope you can improve your material in the future after the chaos of the pandemic (and all the pressure it has most surely placed on you) has subsided.
교육 기관: Radu F•
After a great Course1 i was really enthusiastic. Unfotunately, midway Course2 I decided to unsubscribe from the whole Specialization (after reading several other reviews matching my opinion).
Course 2 it's a bunch of bullshit with videos listing programs, tools, databases and a lot of jargon with no explanation. A lot of outdated stuff that brings 0 added vlue to anyone. Btw. I'm not really a newbie into data science, so it's not about difficulty. It's just useless! Don't waste your time on this!
I think Course2 is doing more harm than even brining something usefull to the table.
교육 기관: Karen N•
I enjoyed the hands-on lab work. Unfortunately, the instructions given in writing and in the videos are outdated regarding IBM Watson Studio, and this led to a lot of frustration and wasted time trying to click around and search for the correct instructions on my own. There were also many typos in one of the written lessons, and the quizzes didn't always match the material addressed corresponding lesson (or, in one case, the quiz question popped up before the topic was addressed in the video). While I'm grateful for the lab work, this was not a good educational experience.
교육 기관: Mukund N•
Unfortunately, a waste of time!
I write this with lo of pain!
This is nothing but PPT with voiceover, conveying the knowledge that is present in google if searched with common sense. I had to drop out of the program with a lot of pain.
Never judge a book by its cover! Just because it is IBM, it doesnt mean it teaches the content in the best possible manner. Human inclusion is necessary for a class to be interesting. And information overload doesnt mean information is rightly conveyed.
교육 기관: Gabriela G•
The course is way too basic to pay for it, you can get better value for your money somewhere else. I had too many issues with Watson Studio and the support I received from the tutor/assistants was repetitive and not helpful.
교육 기관: Seth B•
The sections on Jupyter, Python, and RStudio tools was very hard to follow and unclear why we were performing the actions. The presenter was very knowledgeable but was unclear how it would be applied.
교육 기관: Xixi Y•
You are forced to learn some of the Watson functionality, which is not useful for most students. Ridicules for paid study.
교육 기관: Yeimy C R B•
The videos about GitHub were lack of pedagogy. fast, not clear and the subtitles in most of the cases did not match.
교육 기관: 박영현•
Is it adv for IBM? I didn't learn, and I feel like I paid for an ad.