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Отзывы учащихся о курсе Что такое наука о данных? от партнера IBM Skills Network

Оценки: 56,248

О курсе

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....

Лучшие рецензии


15 янв. 2022 г.

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.


21 февр. 2019 г.

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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76–100 из 10,000 отзывов о курсе Что такое наука о данных?

автор: Krishna B

5 мая 2020 г.

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.

автор: Greice F

15 мая 2019 г.

- 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.

автор: Tiago F V C L

20 июня 2019 г.

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.

автор: Renan M d C

27 февр. 2020 г.

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.

автор: Tim R

21 февр. 2021 г.

The course was very generic and high level. I learned a few things, but the information is generally only useful to someone who is coming into the topic of Data Science with zero knowledge. Rather than having this course as part of the specialization, it would make more sense as a recommended prerequisite for those looking for a general overview of data science. Quizzes felt like busy-work, testing arbitrary facts from the reading in many cases.

автор: Priya A M

6 янв. 2020 г.

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.

автор: Kenneth I

28 мая 2020 г.

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.

автор: Sima S K

27 нояб. 2019 г.

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.

автор: Konstantinos K

27 мар. 2021 г.

Extremely basic and introductory course that does not really give very much valuable information.

Also, the peer graded assignment format is not suited (is not optimal) in my humble opinion for self-paced courses, as i do not want to have to wait for another person to review my work in order to receive the certificate... Just take a look at the discussion threads...

автор: Oedhel S

14 апр. 2019 г.

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.

автор: Justin S

12 дек. 2019 г.

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.

автор: Ka H W

2 мая 2022 г.

T​his course proves a general introduction to the field of data science. The information is not particularly useful. The quizzes questions are trivial and irrelevant.

автор: Gerard K

2 мая 2022 г.

Mostly opinions about what data science is, rather than exercises to develop hard skills and deep knowledge.

автор: Karl H

15 июля 2022 г.

All the quizzes had nothing to do with data science and more to do with reading comprehension ability

автор: Abdullah T A

26 дек. 2021 г.

Huge wast of Time To be honest

автор: Georgi K

21 авг. 2020 г.

[Reviewing the entire IBM Data Science specialization but points are applicable for each course]

I signed up for the IBM Data Science specialization and I was genuinely excited to start it for some 4-5 weeks (I had a GCP exam coming up). I eventually started the specialization beginning of August `20 and started making my way though it and I was amazed … amazed of how much a pile of bullshit this specialization is. I made it though the first 4 courses and at the end of the SQL for data science I couldn’t take it anymore. Here’s why:

1. First and foremost, the entire specialization (all 4 courses I have taken at least) were full of typos and broken URLs which a lot of other students confirm as well. This does not speak professionalism to me but whatever, lets move on.

2. The in-video quizzes and following tests are simply ridiculous … you are expected to have memorized content word by word rather than understand thing for your own and be able to explain them. Some of the question were so far away from tech courses it is not even funny.

3. The final assignments are a total joke. We are asked to review each other which IMHO is a terrible idea since we are all just starting up. Nothing stops you from giving top marks to a bad assignments and vice versa.

4. We eventually got to the more techy part and even got code snippets and jupyter notebooks to look through but they were still bad. There was no proper order in which information was presented i.e. you would read python and seaborn code in the SQL course’s tasks even though python and matplotlib/seaborn are discussed in the following courses.

5. And my final and biggest problem with this whole specialization is that it all feel like an extended advertisement of this piece-of-dodo tech inbred excuse-of-a-software called IBM cloud. There are constants up-sells here and there how almighty IBM is and how great their cloud and IBM Watson Studio are … they are not. I had to spend 2+ hours fixing problems with jupyter notebooks and their cloud just to complete my assignments which both took me 30ish minutes. They mention open source and even though there are open source equivalents to jupyter they insist using IBM cloud. I kept having the feeling they are more focused on promoting IBM products than actually bringing quality content.

6. Now after finishing the SQL course there was a 1min survey which I gladly filled in basically letting them know their specialization if terrible and is doing more harm than good in my opinion. I even sent them a quick challenge because I do not think IBM maintains this course at all or even reads the reviews. You can see my challenge to IBM here:

I was very saddened by the quality of the specialization and the content and was wondering whether I should even try and finish the remaining courses but after reading some reviews on the remaining courses I figured out it was just more of the same. If you are in the same boat I would recommend the kaggle micro-courses which I will focus on starting next week.

In conclusion, I got this whole specialization for free via financial aid and I have to say even though I did not pay a dime I feel I need to be compensated by IBM and refunded real money for torturing myself with their courses.

автор: Stephen L

17 авг. 2020 г.

Be warned!!

I took this course and completed then got my 'digital badge'. However, for me and 100's of other students (according to the forums) our grades and progress disappeared. Coursera, are telling students to report the issue but after 2 weeks and hundreds of complaints nothing has happened.

The course itself is OK but when you are PAYING it is very poor support.

автор: Sujatro G

30 апр. 2022 г.

Repeats the same thing over and over again. Great as an indroduction, but needs to cut down on the number of repetitions. The length of the course can easily be halved or made 1/3rd the original.

автор: Zahid S

15 июля 2022 г.

Very verbose, time consuming and basic. This specialization could have done without this course or a shorter version of this course.

автор: Shuvo S

24 мар. 2020 г.

More like a marketing stint than an actual data science course

автор: Rubin Q

25 февр. 2020 г.

Just a lot of talk. Might as well have youtubed that question.

автор: Brian P

1 мая 2022 г.

t​here is nothing to be learned from this course

автор: Karla E C

17 мая 2022 г.

Really not that usefull very easy to pass.

автор: Ashmini G K

17 июля 2021 г.

This was a great introduction to the field of data science. Having videos interspaced with readings made it easier to maintain focus. The speakers in the videos were super engaging and I liked the upfront warning that data science involves continuous learning, and a willingness to look up stuff and practice until you understand how to do new developments in field. As a researcher who writes reports for shareholders, I felt like students could have benefited from a warning that after you figure out 5 possible solutions to a problem, and detail them in your conclusion and recommendations section, few of the stakeholders will actually read or implement the recommendations. But, hey, at least you'll have fun doing the analysis.

Although the e-note format was great in theory, I found the traditional technique of writing stuff down while watching the videos and reading the material to be more useful, as I didn't need to be logged into the site to study my notes. It's great that both options are available and learners can use the option that best fits their learning style.

автор: Deleted A

9 июля 2019 г.

I do not having any background of Data Science but after go through this course I am having a good understanding about what is data science,what skills are needed to become data scientist etc.Additionally, clear all my confusions .Now I am aware about the correct path to learn data science,also what qualities are required to become a Data Scientist i am also aware about that.

A very good experience i had about data science after go through this course.All real life scenarios are discussed and real life experiences are shared by various data scientist.Excellent course with a very good content for beginners who do not anything about data science.

If anyone is having a little bit knowledge about data science then after going through this course you should know what are the areas in which you can improved, a correct path to build a carrier in data science.