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返回到 什么是数据科学?

學生對 IBM 提供的 什么是数据科学? 的評價和反饋

4.7
51,303 個評分
9,670 條評論

課程概述

The art of uncovering the insights and trends in data has been around since ancient times. The ancient Egyptians used census data to increase efficiency in tax collection and they accurately predicted the flooding of the Nile river every year. Since then, people working in data science have carved out a unique and distinct field for the work they do. This field is data science. In this course, we will meet some data science practitioners and we will get an overview of what data science is today....

熱門審閱

MS
2020年9月17日

very useful. i liked and enjoyed the journey of learning in these five weeks. the instructor is very clear and taught very interestingly. Thanks to her. she looked poised and cheerful and professional

BB
2019年2月21日

Excellent quality content! It's a great introductory course that really gets you interested in Data Science. I would highly recommend it to anyone curious in learning about what Data Science is about.

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9526 - 什么是数据科学? 的 9550 個評論(共 9,711 個)

創建者 Sean M

2018年12月21日

very basic introductions.

創建者 Brandon M

2020年7月20日

Correlation = causation

創建者 Chaojie L

2019年10月11日

Maybe shorter is bet

創建者 Xingyi

2020年7月30日

wordy, wasting time

創建者 Michel M E

2020年12月7日

Not useful at all.

創建者 Shubangini N

2019年6月20日

It was very basic.

創建者 Felipe S

2019年5月9日

Very poor content.

創建者 Adrian L

2021年10月1日

Not very useful

創建者 Alpana T

2020年4月21日

It's too basic.

創建者 Gurjeet

2020年6月2日

waste course

創建者 Rushan N

2020年3月18日

Way too easy

創建者 VINAY C

2019年6月11日

Well curated

創建者 Syed A A A

2018年10月12日

Very basic

創建者 Manu k

2018年6月1日

Too basic

創建者 Harindu h

2021年9月25日

good

創建者 Julian W

2020年1月12日

Really disappointed with the whole specialisation... I am leaving this review here because probably you might not check the others courses before you start it.

Specialisation is short and it is the only good thing about it. It took me I think 10-12 hours to do it.

So first of all the whole thing is not really informative. A lack of videos - Most of the time there is only "power-point"presentation with code written on it. I don't really understand why they have narrator who just read text - no emotions almost like a machine.

Courses:

1. You will spend a lot of time learning listening to videos about how sexy is to be data scientist... and that parents start sending their daughters for data science (sic!), and that it is a new science... Plus some rather simple information which you rather know taking into consideration you want to study it online. At least it is nice to watch - there is life in it.

2. You will spend the whole course watching different notebooks like jupyter R studio etc . without really learning any useful stuff. In the end you will just click run to create some already written commands in python. Yeap that's it. I know it is intro but adding 1 +1 third time in different console...

3. You will learn some methodology - A lot of complicated knowledge read by narrator who is not making it easier or more interesting. Almost like somebody reading you technical book...

4. SQL - you will try to learn it from presentations. I think there are no proper videos just images in narrated power point presentation. I watched some coursera lectures about sql before but still I had problems with following it. To make it worst you will have to use IBM products which are FREE - other reviews are probably outdated. The problem is that materials from this course are also outdated. So they are presenting you IBM tool-set which is already different. It is a problem because they are not even trying to show how they work just where to click.

I managed, you will too but, IBM, please do better.

創建者 Hakki K

2020年7月9日

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

創建者 Laurie A

2020年8月15日

The course content is exciting and high level. In this course the student does not do any hands on data science, except the occasional introduction to an IBM tool. Instead, they are introduced to a broad range of topic, tools, and perspectives on data science. It is a good introduction to the subject, and I would likely have given this course three stars, maybe four, had there not been so many large bugs, that at the time of this writing, almost two weeks since posting in the Discussion Forums and contacting Coursera Help several times, has not been fixed.

For anyone going into the course, please take screenshots of all quizzes and assignments you complete. If you experience the same issue I have, and hundreds of others are having, than your progress data may get erased. I should have received my badge for completing this course two weeks ago but it is still saying I have "overdue" items and that I've completed everything at the same time.

I am sad to give this one start rating, but so it goes. I hope they fix this as soon as possible, and it may end up affecting people's billing.

創建者 Svyatoslav A

2021年2月11日

Has too rigid an understanding of a complicated field. The track would be better off without this class, as it's just confusing. Videos of "real people talking" are a big waste of time. Videos and material contradict themselves multiple times. Quizzes test memorization, and not actual understanding of the material (as in, only ST types will do well on MBTI typology spectrum, but SF, NF, NT that have better understanding will achieve worse grades, at least give challenging questions that apply knowledge learned, not just ask people to define terminology), peers literally copy paste answers for the final exam portion. Basically, just horrible and a waste of time all around, so at least make it just one hour.

Final project being in academic format is the worst, as data science projects in the real world are usually in the form of dashboards, presentations, or products... so this academia bs is literally useless in preparing people.

創建者 Fabien M

2021年2月21日

This course is overall very vague and too long. The whole content should be summarized in 3 pages of text. It is also a bit confusing. For example, it gives two different definitions of big data. There is also a whole paragraph about regression without defining what it actually means.

The risk is that this course gives the impression that anybody can become a data scientist, just by imagining some vague concepts and it will all be ok. The course could emphasize that data science is actually a science. It requires a tremendous amount of very detailed work, with some very difficult tasks.

This course would benefit from reducing the number of interviews and introducing data science concisely. Or, if the authors wanted to actually keep as much detail as there currently is, every concept should be defined properly.

創建者 Angel Z

2021年8月10日

BUYER BEWARE. You will have to pay coursera, then you will have to provide your credit card number to IBM to do any assignments. IBM is charging you to use their cloud services to complete assignments for this course. Once you PAY COURSERA, they WILL NOT refund you after you find out IBM is charging you again immediately upon signing up for the course. Double-dipping SCAMMERS on BOTH ENDS. There is ZERO warning or disclaimer that they will be charging you again to do your assignments. Report them to the Department of Justice for charging you a subscription fee for a class you cannot use without supplying your credit card info to yet another company on a link inside the coursework. IBM obviously just provided the class to get people onto their cloud services platform. It's BS.

創建者 Ivan K

2020年8月25日

A complete waste of anyone's time who knows anything about data science and would seek the data science specialization on this site. Further, the course material thus far appears to be a paid-for repackaging of free instructional materials offered by IBM at bigdatauniversity.com. Why I had to sit through this material is beyond me in the context of a data science skills tract. Please, stop wasting professionals' precious time and money with this material. This material took me merely a weekend to get through, not 3 weeks, the framing of which seems questionable at best. Please remove this from the overall specialization. My experiences thus far make me feel that I may not continue with this set of courses if this is the level of quality I can expect.

創建者 Nishant

2021年9月11日

Why do I need to know which publication said a particular thing about a topic. Why do I need to remember in what year something happened? Why do I need to remember who quoted a particular thing. The course was amazing. The quizzes were set by some idiot who had absolutely no understanding of the course. Rather than testing the knowledge they chose to test unnecessary details. Frankly, the quizzes were not enough, they needed more questions and all needed to be relevant and not pulled out of a hat at random. Absolute trash questions in the quiz. This is my first IBM course and if this is the kind of questions being asked I am very sorry to say that the course is way below average in the quizzes. However, I did like the actual course and videos.

創建者 Garrett G

2019年5月26日

I am subscribed to and paying for the IBM Data Science Professional Certificate and when I attempt to submit a quiz within the "What is Data Science?" course the submit button displays "Upgrade to submit". When I attempt to go through any of the customer service or chat windows which themselves are hard to find, the chat window does not display properly or function in the slightest. This was also the case when I attempted to submit a support request or create a ticket within the mobile app. Terrible and frustrating experience. At this point I'm unsure as to what to do besides cancel my subscription and give up on the money I have already payed as they seem to be instant on not allowing you to contact any customer service representatives.

創建者 arafat i k

2020年6月28日

There should be an option to rate zero stars !

I am CS graduate, and also has deep understanding of learning algorithms. Isn't it's a huge waste of time, spending three weeks to recite the definition of data science and data scientist ? I believe most of the students in this course are somewhat from CS or equivalent background. And for them its just a trash!

People, maybe high school kids may say oh no its such a good course, i never knew data can be such impactful bla bla bla, they might find this course little bit useful than just googling : "what is data science ?"

And the quizzes, lol that's just joke. You have to recite salary figures from supplementary pdf so it might make you feel good! who knows !