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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
43,010 個評分
8,024 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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KK
2020年2月23日

Terrific introduction to the Data Science course. Never expected but was extremely excited with the quality of content, speakers and a very honest attempt to making this course interesting.\n\nKrishna

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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7701 - 什么是数据科学? 的 7725 個評論(共 7,970 個)

創建者 Naman P J

2019年6月1日

basic

創建者 Muhammad N A K

2020年10月24日

Good

創建者 Arti k b

2020年8月11日

Good

創建者 Sai S L . J

2020年7月10日

GOOD

創建者 Jakub K

2020年5月25日

soso

創建者 Yannick L A

2020年5月8日

Good

創建者 Sudarshan R P

2020年4月29日

Good

創建者 Shaojia W

2020年3月24日

good

創建者 Ashish D

2019年12月22日

Good

創建者 POULOMI S

2019年5月11日

good

創建者 Catherine L

2019年9月30日

V

創建者 Ross E

2020年3月25日

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.

創建者 SHANNON L H

2019年9月12日

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.

創建者 Krishna B

2020年5月5日

Honestly, I just expected too much from this course. It ended before I could even fully realise it had begun. Grading seemed to be less along the lines of "We want you to understand this" and more along the lines of "We want you to memorise a specific quote from a puzzlingly long video that you won't feel like watching throughout, and will follow up with a reading which is more or less a transcript of the video."

Take up the course if you've never come across the terms "data science" in your life. Otherwise, it's just time and cognitive effort down the drain. This course is basically clickbait that claims to need 3 weeks of your time, but can be completed in a single hour if you're a fast reader and have a long lunch break at work.

創建者 Greice d F K

2019年5月15日

- Texts have poor quality so they are hard to read and the references are not available.

- No extra materials are available.

- The quiz are pointless: you can answer without understand the text or the videos. You just need to find the key words on the text, no need to comprehend it.

- The videos are very boring. They are sometimes contradictory. Some questions are not answered and others are answered over and over again.

Finally, I thought the course poorly structured, boring and with low quality material. I could find better material on the internet for free.

創建者 Tiago F V C L

2019年6月20日

The course itself is too general; you complete the course and it's hard to say you actually learned something new. The exercises are extremely easy, you could easily skip all the videos, open the text for each assignment and answer. Furthermore, the testemonials appear to be randomly picked students who say what they think they're supposed to say, or just give their own opinion; this contributes very little to the viewer's actual learning. An introductory video to data science would've had the same outcome as this entire course.

創建者 Renan M d C

2020年2月27日

The course has a very basic approach. It's much more basic than I have imagined and to be honest it is not worth paying for. Everything taught here could be learnt on youtube in 1 or 2 hours. I was expecting basic exercises using data science tools, I mean, the same approach used by academic books: first you learn some concepts and then you make some exercises, then you proceed to the next topic. I'm not saying that what was presented was not good, it was great. But it could have been much deeper.

創建者 Priya A M

2020年1月6日

It would have been more time-effective for me to read the Wikipedia page on data science than spend the time watching these videos. The videos are much too basic with absolutely nothing technical and a fair amount of repetition of the themes across all weeks, for example, needing to be a good storyteller. The entire three module course could have easily been condensed to one module and something more substantial could have been added instead.

創建者 Kenneth I

2020年5月28日

Mostly awful. The majority of the videos are just college professors talking about "curiosity, and passion for data analytics" No concrete examples, just a lot of fluff. Actual verbatim: "A data scientist does data science" The quizzes are a joke. This honestly felt like a waste of time. I'm no closer to learning the "hard skills" necessary to become a data scientist than at the beginning of the course.

創建者 Sima S K

2019年11月27日

I wouldn't spend much time on this course. Although it is informative, it is filled with marketing for IBM and lengthy and sometimes repetitive interviews with people who work in this field. I'd rather skip these and jump to the real learning, software and analytics skills. Most people who are taking these courses already know this stuff and plus all this information is available for free online.

創建者 Oedhel S

2019年4月14日

Very thorough for anyone who is interested, but doesn't know what data science is. However, it is mind-numbingly basic and most of the reading is more theoretical application than instruction. Way too long of a course for how little information there was. The quizzes were frustrating, as well, as they simple referred to the reading, but didn't reinforce concepts.

創建者 Justin S

2019年12月12日

Very basic introduction. Would have liked a little more substance than just the QnA section with some people in the field and a couple short readings. This entire course could have been the first week in a real course. I also think the quizzes could have been better. They just copy paste sections of the reading to make sure you read the reading assignments.

創建者 Joe W

2019年10月29日

After working as a data scientist looking to add "credentials" based on these certificates, I didn't learn any new concepts. If you have never heard of data science and are in high school or just starting to learn about the field, this course would be useful. Otherwise, if you already have experience I would recommend against taking this course.

創建者 NITYANAND R

2020年6月1日

really very it is very basic thing to understand, what is data science, but it has been very lengthy process to understand this and unnecessarily time was engaged on IBM Cloud Platform, a person who's going to pursue the entire course will definitely use the tools but to introduce the field it should be very short and precise thing

創建者 Lawrence L

2019年7月14日

While I appreciate the talks given by these experts, the way this content was spread out with very little substance was demotivating for me and not an efficient use of time, in my opinion.

It could be much more concise.

I liked the final assignment as a recap and way to interact with my classmates.