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IBM による データサイエンスとは何ですか? の受講者のレビューおよびフィードバック

4.7
37,840件の評価
7,011件のレビュー

コースについて

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....

人気のレビュー

PD

Jul 19, 2018

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).

BB

Feb 22, 2019

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.

フィルター:

データサイエンスとは何ですか? : 6751 - 6775 / 6,974 レビュー

by Allan W

Jul 18, 2019

bit slow

by sanket g b

Jun 11, 2019

thik hai

by Abdelmalek N

Feb 17, 2020

I

l

i

k

e

i

t

by 손승건

Jan 16, 2020

not bad

by Luca A

Mar 01, 2020

Basic

by Antonio S A

Nov 12, 2019

Basic

by NAMAN P J

Jun 01, 2019

basic

by Sai S L . J

Jul 10, 2020

GOOD

by Jakub K

May 26, 2020

soso

by Yannick L A

May 09, 2020

Good

by Sudarshan R P

Apr 29, 2020

Good

by Shaojia W

Mar 24, 2020

good

by Ashish D

Dec 22, 2019

Good

by POULOMI S

May 11, 2019

good

by Catherine L

Oct 01, 2019

V

by Ross E

Mar 25, 2020

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.

by SHANNON L H

Sep 13, 2019

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.

by Krishna B

May 05, 2020

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.

by Greice d F K

May 15, 2019

- 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.

by Tiago F V C L

Jun 20, 2019

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.

by Renan M d C

Feb 27, 2020

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.

by Priya A M

Jan 06, 2020

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.

by Kenneth I

May 28, 2020

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.

by Sima S K

Nov 27, 2019

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.

by Jeremy S

Apr 14, 2019

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.