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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
53,950 個評分
10,166 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....

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PD

2018年7月18日

I thought this course introduced the topic of data science very well. I think I have a much better idea how to describe data science and common terms associated with the field (like machine learning).

RS

2020年5月11日

Very learning experience, I am a beginner in DS, but the instructors in this course simplified the contents that made me I could easily understand, tools and materials were very helpful to start with.

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9576 - 什么是数据科学? 的 9600 個評論(共 10,000 個)

創建者 Shivank S

2019年10月17日

Showing the only expertise talks not the live tutorial how it works but overall it good if you are beginner then go for it you can better understand how can you start your career in data science

創建者 Danny T

2019年2月21日

The initial course was ok but you should provide more real world examples. Such as several real "reports" and their contents. Just providing report sections and descriptions is not good enough.

創建者 Yannick R

2019年11月7日

Very basic, a lot of very generic "let's talk about X" videos, reading interesting but not very in-depth. Does answer the question "What is Data Science", but left me wishing for more details.

創建者 Sven T J

2021年1月12日

Course contained interesting information, but could be condensed to probably one week. There is a lot of repetition and information not directly needed, e.g., info about courses at Stern.

創建者 Takako S

2019年2月28日

It is a very basic intro course that provides a general understanding of what is data science. It doesn't teach technical skills but it is a good course to learn about the whole industry.

創建者 Francisco B L

2019年2月1日

It is ok, but not great. It gives you a vague idea of what it itake to be a Data scientist, but reains very anecdotical and the provided definitions are not as sharp, as I had expected.

創建者 Frederic R

2019年11月10日

Videos and reading are informative. Final testing of course is rigid though. Requires students to have a verbatim definition memorized rather than an actual understanding of concepts.

創建者 Jimmy G

2019年6月20日

Too non-technical. Could include more concrete project examples ("case studies") even at the beginner level, to really allow students to gain an appreciation of what the field can do.

創建者 Ruben T

2019年9月30日

I didn't like the emphasis given to the money you can make by studying data science, I understand most people are just chasing the money but it was totally frivolous and unnecessary.

創建者 Grzegorz S

2019年9月10日

This is not really a course -> rather some videos about what Data Science is. So if you are looking for some knowledge (for which I believe we in Coursera do) just watch it through.

創建者 Edna R M G

2022年5月13日

They say that they offer extra material and you open the page and the information is not found. The course is a good mouth opener for all the opportunities that Data Science gives

創建者 Eepsita S A

2019年10月28日

The course was very informative.

The time sensitive locks on the teaching material were very inconvenient and should have been relayed to the student before enrollment.

Thankyou

創建者 Kris K

2018年12月13日

Several English and grammatical problems in the questions and quizzes. This made it confusing at times. Also, some of the questions to the videos need to be reviewed for errors.

創建者 Sheen D

2019年7月25日

Not sure what is the purpose of this course... just to read articles about definition of data science or data scientist? Or something about the sexist job of the 21st century?

創建者 Pavel P

2019年8月25日

Very good for start. On the other hand topic could be said in shorter way. But it is subjective. Therefore I can recommend with this course your journey through data science.

創建者 S. U

2020年4月16日

A decent overview of the field of data science and the type of work involved. Not at all academically challenging, but a reasonably interesting, short intro to the subject.

創建者 John R

2022年1月20日

Not really that helpful. Maybe if you come from a completely different background. But if you are trying to learn data science. I imagine you know what data science is.

創建者 Sebastian D R

2020年4月13日

The course is very basic and is not taught in the most efficient way, it's very theoretical and does not provide very detailed examples of what data scientist really do

創建者 Oliver H

2019年3月2日

Needs to be updated to match the online environments used. Quite confusing when you have to really struggle to find the right section of Watson and nearly put me off.

創建者 Karolina V

2018年9月27日

Nicely done, but it could be more condensed. I would be unsatisfied I was paying just for this course, but probably good introductory for the rest. Maybe too general.

創建者 Tyler G

2020年1月27日

Great to hear from professors, but not helpful to hear from random students. I discount their opinions out of hand, they are not experts, so it's just distracting

創建者 Hugh B

2020年7月5日

Did not think this much background was needed. I would argue only 30% of the video material was necessary. However, it still informed me of what data science is.

創建者 Anokh P

2019年9月25日

solid for beginners, but a little buzzwordy and some of the questions/answers felt cheap and based on memorizing what was said instead of applying new knowledge

創建者 PETER M

2021年4月8日

Its a theoratical course, i had earlier thought it would be a practical one but still am excited to know the background information of data science as a whole.

創建者 Riccardo R

2019年11月30日

Good to give you an idea of what data science is but nothing really that you can't find elsewhere. It's a nice set of video lecturer, interesting conceptually.