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데이터 과학이란 무엇인가요? (으)로 돌아가기

IBM 기술 네트워크의 데이터 과학이란 무엇인가요? 학습자 리뷰 및 피드백

56,421개의 평가

강좌 소개

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....

최상위 리뷰


2020년 6월 26일

I throughly enjoyed the course and the fact that everything was explained thoroughly. I always enjoyed Dr. White's personal experience with Data Science as well as other Data Scientists point of view.


2019년 9월 9일

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.

필터링 기준:

데이터 과학이란 무엇인가요? 의 10,000개 리뷰 중 51~75

교육 기관: Preston K

2018년 10월 1일

Utter waste of time

교육 기관: Andrew F

2019년 1월 3일

Great introduction to Data Science!

교육 기관: Vincent Z

2019년 1월 7일

This is really an introductory course, and there is not much to be learned, not a single line of programming or a single chart generated. But it can all be done in a single day, so it is a necessary evil to reach the good stuff in the specialization, I guess.

교육 기관: Nicholas B

2020년 2월 2일

Extremely basic introductory course. Unfortunately you don't learn much about actual data science methods. Quiz questions tend to require you to memorize word for word quotations of supplied text, as opposed to challenging you to think about concepts. I would recommend this course for someone completely new to the idea of data science, but not to people who already know a bit.

교육 기관: Shelley

2018년 9월 23일

The course provides a good overview of data science in general. I particularly liked the definitions of a data scientist and data science. Mr. Haider's definitions are inclusive, broad and encouraging, He says one of the most important traits for a data scientist to possess is curiosity and that tools and techniques can be learnt.

The course also touches upon hot topic areas that people have heard of but most do not understand - i.e. Machine Learning, Neural Networks, Data Mining and Big Data. I have a much better idea what these terms mean now along with the tools of the trade. The course was quite short and concise. I found it the perfect pace for me. The quizzes matched the content and there was nothing extraneous.

I am looking forward to the other courses in the specialization. A quick glance has shown me that the difficulty level increases quite a lot in the other courses and I would definitely have to invest a lot more time in them. The start has been gentle and encouraging, thank you!

교육 기관: Enas J k

2020년 7월 22일

This course has very detailed information on data science and data scientists. The real-life examples and applications of data science presented by different data scientists are also amazing. Overall an excellent course for anyone who wants to venture into this amazing field.

교육 기관: Abdul W

2020년 5월 31일

After completing this course you can easily understand and define what is Data Science and clear your doubt about Data Science.I recommend this course to all beginners.

교육 기관: longmen

2019년 5월 6일

I have learnt about what the data science is and it's basic knowledge. I am glad I took the course. I will continue finishing the rest of the courses.

교육 기관: Kanchan P

2019년 1월 3일

This is a very good introduction to what actually is data science! Lot of people gets really confused with the definitions and area!

교육 기관: Sergi

2019년 1월 1일

Direct to the point. Increases one's passion to study Data Science by summarizing the main topics. Simple and brilliant

교육 기관: Amarjot S

2020년 3월 7일

This course equips a person with all necessary knowledge required to get started in this field with confidence.

교육 기관: uzair k

2020년 3월 7일

A very brief and complete introduction of Data Science from industry experts highly recommended course

교육 기관: Mahesh K

2019년 1월 3일

It encompasses fine details to introduce data science and explore data scientists as a career.

교육 기관: Harsh R

2020년 6월 1일

Amazing course to a roadmap to data science

교육 기관: Ferry T

2019년 8월 20일

Great for introduction!

교육 기관: Irfani K

2020년 11월 25일

Very good thank you

교육 기관: Chan H D L

2019년 1월 3일

Very informative and presented by respected individuals with a passion for the field. The only critique is that the material might be a little outdated as it seems to have been created around 2014-2015.

교육 기관: Dwight F

2019년 1월 1일

It does in fact answer a basic, fundamental question; what is Data Science?

교육 기관: Surawut P

2022년 5월 10일

The content is good and easy to follow.

What I hate about this course the most is all test, quiz and examimation.

Most of their questions are not fair. They require to recite inconsequencial minor detail, such as who or which book said what.

I expect the test to recall about main concept, such as "What is different between AI, ML, and deep learning?", "What is properties of big data?", "what is application of regression". These kind of questions recall things much more important than minor detail I mention above, but they are non existent.

This happen possibly because the questions emphasized too much on module articles, which is full with detail, rather than clip videos, which present important concepts.

I hope you to revise examination questions to be more appropriate. I feel frustrate when doing them because asking minor detail feel like you are cheating upon students.

교육 기관: Steven G

2021년 5월 23일

I genuinely enjoyed this course, but the quizzes are absolutely irrelevant and petty to the point of absurdity. How is attributing a quote to Hal Ronald Varian going to make me a better data scientist? How is know the specifics of one person's research about houses relevant in the massive field of data science? Your quizzes need to focus on key concepts instead of minutiae

교육 기관: K M

2021년 7월 29일

It's a decent course if you don't know why you want to go into data science but if you have an idea, then it's just listening to other people talk about why they like the field without teaching you much.

교육 기관: Anna R

2021년 2월 17일

Broad review of the definition of data science. Can easily get the same information from a quick Google search. Week 3 was the most useful.

교육 기관: Roger A

2020년 7월 26일

Many interviews, nice chats, but not so much content. I was expecting some more theory/practice, not so much documentary.

교육 기관: Ross E

2020년 3월 25일

Most of the transcripts of the videos were from old or different versions of the videoes. This fails the basic principle one of the core of the five Vs: Veracity. None done.

There were countless errors in the IBM voiced-over, animation videos. For example saying that data mining is "automated" when it was just explained that data priming - which is often highly manual at the outset - is an important part of the first steps of data mining. It is absolutely NOT inherently an automated process from end to end.

The final "capstone" assignment which was essentially regurgitation was graded incorrectly. Especially with respect to the final reading. Students were asked to list the "main" sections of what should constitute a report to be given to stakeholders following data science based research. Firstly, dictating sections is stupid as you need to customise to your audience and NO, doing it that way should never be prescribed as universal. Secondly, even adhering strictly to what the reading said and ONLY what the reading said, the grading criteria was WRONG. How on earth did you list Appendices, CLEARLY stated as OPTIONAL as one of the 10 main sections? Not only that, you listed sub-sections as whole sections. For students that got the answer correct, I graded them as such and commented that I'm doing this because the criteria was in fact erroneous.

It's one MOOC. How hard is it to get the basics right? What happened to the IBM culture that used to make software engineers write all their code without a compiler to MAKE SURE what they were building was as correct as possible before compiling because of a focus on quality?

Amateur hour over here. Not inspiring.

교육 기관: SHANNON L H

2019년 9월 12일

Was pretty upset that the answers on the final assignment were incorrect according to the course materials. I am an OCD person that is very by the book, who studies and seeks my answers directly from the materials. I am hear to learn and depend on you to have accurate learning materials and tests that follow the course materials.

I create procedure manuals for staff. One of the first things I do when I finish a new manual, is go through each thing, step by step, to make sure it is accurate. My manuals are for a handful of people, your learning materials are for thousands of people, many of which have language barriers, as English is not their first language. So this makes it even more important for your assignments/tests to be extremely clear in their questions and the answers correct according to the course material. When you have a tremendous amount of complaints about this on the discussion forums and no one of power is doing anything to correct this, this is a major issue.

I had started a specialization with Coursera a few months before and quit near the end of course two due to extreme frustration with these same issues. I love the idea of these specializations, and would love to take many of them. I hope and pray that the rest of this course will be a vast improvement over the last assignment in Course 1 week 3.