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学生对 IBM 技能网络 提供的 Tools for Data Science 的评价和反馈

4.5
25,753 个评分

课程概述

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....

热门审阅

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.

GC

Apr 12, 2020

It serves perfecty its aim that is giving a first glance of the open course tools for data science. Of course each tool is briefly touched and it hands over the student the duty to deepen each tool.

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26 - Tools for Data Science 的 50 个评论(共 4,176 个)

创建者 Jyothika J

Apr 3, 2020

Actually in this course the videos which are provided are of older version and now the version has changed its getting difficult because its the first time learning new tools and accessing the tools.Try and provide videos for the present version of tools.

创建者 Fares A G

Mar 20, 2020

This course is embarrassing to take, the level of education is so that a highschooler would understand it with ease, it does not teach you how to use the tools claimed. Advertising this course as a learning tool to open source tools for DS, is akin to someone advertising a course for programming languages then teaching you how to write hello world in two or three languages. A more apt name for the course is "An outdated advertisement to IBM tools for data science". Why do I suddenly mention outdated? Because the videos, labs, and readings use the IBM skills academy website as is at least a year outdated, the tools they use (specifically adding data to the skills lab) are no longer available, and the instructors have done nothing about this on the forums. You're better off learning from youtube or google or anywhere else, even if this course was free, it'd be a rip-off.

创建者 Michael K

Apr 7, 2019

Imagine that you weren't particularly handy, but on a whim you decided to build yourself a dog house. You go to the hardware store, and the guy behind the counter tells you to start with the hydraulic maintenance manual for a multi-million dollar crane used on skyscrapers. That is the best analogy I can give you for the utter uselessness of this course.

I'm plunging ahead with the next course, but I have to say my opinion of IBM is diminishing with every step forward.

创建者 Robert B

Aug 3, 2020

Terrible course. I hope the other courses in this certificate program are better. If they are anything like this I would certainly expect people to start asking for their money back. Romeo Kienzler might be very knowledgeable, but he clearly cannot teach well online. The videos were low quality, with bad audio, and taught you next to nothing. Very disappointing.

创建者 Ebenezer O D

Aug 15, 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.

创建者 John G

Feb 21, 2021

Poorly designed course.

Week 1: While the first section was ok, after the section on “Data Science Tools”, it was more or less just a list of tools for data science. I have 5 pages of notes that are mostly useless. The only reason I wrote so much was that the quizzes often asked about such useless details, that I learned to write more than I usually would. Whoever designed the course/tests obviously has no real teaching experience. In addition, do not expect any feedback from the quizzes. There is no attempt to help the learner learn from wrong answers.

The quality of most of the “instruction” was poor. The woman reading the script often did not logically pause when a slide was changed or more information was added to the slide, as if she didn’t know what was on them. For most of it, it was just a PowerPoint presentation. For IBM being so advanced with technology, it seems for most of the teaching they simply used 20-year-old technology to demonstrate some of the most advanced technology that currently exists. ☹ At least they could have used a split screen to show a person AND text/screen shots.

Week 2: Better information. Same woman reading slides…who is not convincing that she actually understood what she was actually reading. However, the information was more useful and the tools introduced were better. Now I’m registered on some sites and we’ll see how useful that is.

Week 3: A big mix. Again lots of tools. Different people speaking, but again they are just PowerPoint slides with no interaction with people (unlike in the first course in the program). When there are screen captures, sometimes they just jump and it is difficult to follow as they are quite quick. Often the screen shots don’t have high enough resolution, so many of the tabs in the programs are either difficult or impossible to read, or they don’t capture the whole screen, so it’s pretty useless as we can’t really follow how it gets from one place to another.

Sometimes poor English pronunciation. Why doesn’t the person who actually create the presentations/work with the programs actually do the speaking?

Week 4: Labs are useful and it’s great that there was some kind of output. Unfortunately, many of the things that you have to do are not actually taught in the course and you have to use other sources to find out how to do things.

创建者 Josias B N

Nov 26, 2020

I have done a few courses online and this is by far the worst I've ever encountered. The structure, contents and even the audio (sometimes impossible to understand without subtitles) were very below average. I never thought IBM would offer such a product. To make it short, I had the impression they put together a few videos from IBM trying to promote its products. And to make things even worse, the tool provided by Coursera (IBM product) was a let down. Slow, many times it didn't load, confusing to find your way around. Very, very disappointed with this course. For me it felt like a waste of my time and made me feel frustrated. I would strongly recommend NOT TO TAKE THIS COURSE.

创建者 Kevin C

Dec 13, 2020

Learned very little to nothing. Bias was very clear to get students to just use IBM products. Information and teaching method was unorganized and jumbled, seemed like it was cut and pasted from previous versions, and left out all the context of the original. Stressed me out and quite frankly made me consider quitting all together. This course was not worth the money I paid and I think I'd like to request a refund.

创建者 gabriela

Apr 2, 2020

The videos aren't updated. They are using an old version of the IBM cloud and IBM watson studio. It is extremely difficult to follow the tutorials based on. You should find the recent information through the forums and Google, which is ok. But, why is the idea of having a video that is not useful with the current platform?

创建者 Mikhail P

Jun 7, 2020

Really bad narration as well as unclear instruction. This course makes me rethink if I should continue.

创建者 Vladislav S

Jun 10, 2020

It's terrible, useless and boring

创建者 Giulio C

Apr 13, 2020

It serves perfecty its aim that is giving a first glance of the open course tools for data science. Of course each tool is briefly touched and it hands over the student the duty to deepen each tool.

创建者 Reza J

Oct 8, 2021

Great course with practical approach to tools that come handy beside data science with python such as git and github, Some basic R coding and a great introduction to IBM Watson studio and cloud.

创建者 Mian M A

Nov 29, 2019

This course helped me finding open source tools. I knew about Jupyter Notebooks, but I also got to know more tools. Further, I got IBM subscription too, it would definitely help me in my work.

创建者 Naveenchandra M S

Jun 30, 2019

This course is very nice to understand Python, Zappelin and R Studio basics on code and concepts, in which you will get hands on along with creating a free IBM Cloud and Watson Studio account.

创建者 Чернова И Р

Mar 3, 2019

Brief overview of the open source tools such as Jupyter and RStudio.

. Pretty good for beginners

创建者 Emily W

Oct 5, 2021

This course was jam packed with technical information and the quizzes and assignments often prioritized small, random details over general understanding. This was frustrating for me because I am new to the field and everything in the class was foreign. Also, it often felt like so many tools were being introduced to balance out the focus on IBM. This had the effect of making the class feel cluttered with information and didn't really diminish the overall feeling that the class is an IBM marketing product. It would have been less confusing and more meaningful to have a contextualized introduction to all the IBM components we are using in this course or that data scientists can use.

创建者 Takamasa H

Jan 6, 2022

Overall I wasn't satisfied with this course, and I hope this review catches the eyes of those who are thinking of enrolling in this course.

I have 3 main issues with how this course was handled.

1. Contents are outdated: As many people commented in the discussion forums and reviews, some of the contents regarding Watson studio is outdated, as the website went through updates. Instructions are not to be trusted in such cases, and it was difficult to navigate the course. 2. Full of Watson studio propaganda(ish): When going into this course, I was not expecting nearly half of the content to be focused around IBM's own platform. Seems a bit biased towards its own product, and I felt a bit annoyed with this.

3. Content is incredibly easy/ shallow: Completing this course proves almost nothing about your abilities for knowing tools for data science. It merely scratches the surface of the tools involved-- for example I really don't need this course to teach me how to create a markdown cell in Jupyter. If you are a college student or a working professional, this is something you can teach yourself through Google. It could be good as an introductory course for high schoolers interested in Data Science. (I felt like, personally, it was more about how to use IBM's Watson studio, and what IBM offers, more than learning about Data Science)

创建者 Reed M

Dec 20, 2020

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.

创建者 Jennifer F

Sep 5, 2021

This course felt more like an advertisement for IBM products than an overview of tools for data science. It's so obvious even just looking at the quizzes, 3 questions each on the open source tools quizzes and 10+ questions on each of the quizzes for the IBM products. The quizzes, by the way, are awful. I find myself having to write down everything that's said in the videos to do well on the quizzes because we're being tested on whether or not every little thing is memorized. I would prefer to focus on the overarching concepts and focus on the tools I know I'm going to need (Python, R, SQL) rather than IBM products. The construction of the quizzes really takes away from learning everything else because you have to pass the quizzes to get the certificate so you have to focus on that content instead of what's useful to you.

创建者 Angela S

Dec 11, 2018

The Coursera videos to IBM Data Science Experience (now IBM Watson Studio) are outdated and therefore lead to unnecessary confusion and, to a point, obstruction of completing the course. The end-of-course project was 10x easier than figuring out how to set up a Jupyter Notebook in IBM Watson Studio. I guess you could say it's a sadistic way to weed people from the course! Please make the updated videos an immediate priority. Otherwise, the obtusely simple (enter code "1+1" to represent addition) videos are irrelevant.

创建者 Shushu S

Dec 30, 2021

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

Thank you

Yehoshua

创建者 Anupama K

Nov 24, 2020

Toooooo much theory in the beginning. Talks about way too many tools and their features. And its not on informative basis, The quizes are based in these. It is hard to keep track and answer the quiz. And also practically do we need to know about so many tools?

Jupyter Notebook part was good.

创建者 Robert H

Nov 4, 2020

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

创建者 Hakki K

Jul 9, 2020

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