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Tools for Data Science(으)로 돌아가기

IBM의 Tools for Data Science 학습자 리뷰 및 피드백

4.5
별점
20,277개의 평가
3,093개의 리뷰

강좌 소개

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, RStudio IDE, Apache Zeppelin and Data Science Experience. 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 Cognitive Class 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 Data Science Experience and demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate....

최상위 리뷰

RR
2019년 4월 24일

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!!!!

AJ
2020년 9월 15일

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.

필터링 기준:

Tools for Data Science의 3,066개 리뷰 중 51~75

교육 기관: Nicole W

2020년 4월 14일

The section on Watson Studio had outdated content and was hard to follow

교육 기관: Vinit K S

2019년 8월 7일

Please update the videos, with new IBM Watson Studio interface examples.

교육 기관: Akhil K

2019년 5월 15일

Good course!!!

교육 기관: Alex S

2020년 4월 15일

The teachers were smart and funny, and I enjoyed trying out the tools (some new to me, others not). These people clearly knew their stuff and I got the impression they wanted everyone taking the course to know and use it as well.

The tests and labs were really lacking though. The tests simply required looking for verbatim quotes in the material and the labs were, somehow, both confusing and hand-holding. Baffling to me.

교육 기관: Paul M

2020년 4월 14일

Needs some updates to match new formats for IBM Watson Studio. Also, this course skipped over basic code theory and functions, and tried to overcome that by just describing buttonology needed to make the programs operate. Not even close to good enough.

교육 기관: Abdelkareem H

2020년 6월 15일

The course was overall OK. Several lessons were either too advanced and required previous knowledge about the subject or the audio was terrible. Nonetheless, one learns a few things in this course. But definitely not one of the best.

교육 기관: Rona S

2020년 4월 14일

Useful overview of tools. Following the tutorials was frustrating as the demonstrations did not match what is now available. Got there with a fair amount of frustration and swearing! The assignment was fun though.

교육 기관: Dmytro P

2020년 4월 3일

courseware is outdated, I was having issues understanding how to create project in IBM Watson, while video explains how to do it in IBM data science experience.

교육 기관: Daniela P

2019년 1월 10일

The course in watson studios contains videos the were too outdated and didn't really help understand how to use the platform as it is nowadays.

교육 기관: Diana T

2019년 1월 14일

Some of the Watson Studio videos are confusing because they are recorded on the previous version and they don't match anymore.

교육 기관: Keyun R

2020년 4월 14일

The material seems out of dated and it takes a lot of effort to try to find a region that finally accepts registration.

교육 기관: Declan C

2019년 9월 12일

Videos and instructions do not sync with new IBM Watson Studio.

교육 기관: Eshita G

2020년 6월 17일

Very technical, difficult to follow properly

교육 기관: Reed M

2020년 12월 20일

Not a very good course at all. Part of it is dedicated to memorizing the names of a bunch of data science tools for tasks that are defined in one or two sentences. Much of the rest is dedicated to basic-to-the-point-of-triviality "Hello world" style tutorials for Jupyter Notebooks, RStudio, and IBM Watson Studio. Speaking of the latter, there's a disproportionate emphasis on IBM products - a bunch of advertising that IBM will help your data science workflow, directed towards learners who have never experienced that workflow at all. Even as advertising, it's bad advertising. And how is it that we've gone through two courses and still haven't learned anything of substance about programming or math? I learned a few new bits and pieces of Markdown from the final project, but that's about all I'll retain from this course.

This course convinced me to jump ship from the IBM data science professional certificate path. It's possible that things get better later on, in the courses with actual substance, but I'm not going to bet $40+ on that possibility.

교육 기관: Edo v d Z

2020년 4월 13일

Very meager overview of tools. No explanation of what you are doing, videos are outdated, no explanation of the differences between the tools (when do you choose which tools), system was down for a long time, links are not working correctly. It looks as if this module was made years ago and then systems developed but the course was never updated. Course leaders is not working anymore for IBM already for more than a year. IBM you can do better!

교육 기관: Josep R C

2020년 4월 13일

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: Kathryn D

2020년 6월 18일

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

2020년 6월 15일

A clear explanation of every tool required. Too advanced for beginners in data science.

교육 기관: Hellman O

2019년 9월 12일

These materials should be updated to the current Watson work environment

교육 기관: Shuang.W

2020년 4월 15일

the videos about Watson lab are out of date.

교육 기관: Robert H

2020년 11월 4일

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

2020년 7월 9일

Hi,

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.

(*): https://www.coursera.org/professional-certificates/ibm-data-science?utm_source=gg&utm_medium=sem&campaignid=1876641588&utm_content=10-IBM-Data-Science-US&adgroupid=70740725700&device=c&keyword=ibm%20data%20science%20professional%20certificate%20coursera&matchtype=b&network=g&devicemodel=&adpostion=&creativeid=347453133242&hide_mobile_promo&gclid=Cj0KCQjw0Mb3BRCaARIsAPSNGpWPrZDik6-Ne30To7vg20jGReHOKi4AbvstRfSbFxqA-6ZMrPn1gDAaAiMGEALw_wcB

교육 기관: Hoseok Y

2020년 12월 4일

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

2020년 3월 23일

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

2020년 8월 31일

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)