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Avis et commentaires pour d'étudiants pour Qu'est-ce que la science des données ? par IBM

4.7
étoiles
41,855 évaluations
7,802 avis

À propos du cours

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....

Meilleurs avis

MG
26 juin 2020

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.

PD
18 juil. 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).

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26 - 50 sur 7,747 Avis pour Qu'est-ce que la science des données ?

par Meseret G

26 juin 2020

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.

par Rick N

27 avr. 2018

I did not learn much from this course. I did not enjoy seeing the young data scientists talking about their jobs. I was not too impressed by Dr. Haider or the professor from NYU.

Dr. Haider misused some words, such as "judgmental" and "argumentative". Without any evidence or examples for support, he claimed that it was more important for a job applicant to have a sense of humor than technical skills.

This course should have named specific techniques used in data science, and how to acquire the knowledge. Regression was mentioned, but the explanation was inadequate. Perhaps the explanation should have been omitted. K-nearest neighbor was mentioned.

Many students want to know what courses to take next, what computer languages to study, etc. What are the computer programming languages of the future?

Students cannot learn everything. Would it make sense for someone to skip some things, and to focus on others? Should everyone learn Python? Does everyone need to learn SQL? What about Tableau? Is that worthless?

How should students set their learning priorities in order to achieve a basic or minimal skill set within 3 or 6 or 12 months?

Remember that most Coursera students already have a college degree.

The course was created several years ago, so I think it needs to be updated regarding developments of the last three years.

par Mateusz K

31 déc. 2018

Quite vague and repetetive, I didn't feel like there is a structure in the course, more like a collection of random thoughts by various people. It's more an introduction to what data scientists think about data science than an introduction to data science itself.

par Reinhard H J

9 oct. 2019

I'm sorry to give a low rating, but this course is condescending. Some of the statements are also opinions that contradict things you will hear in other courses, not to mention that a great part of the course is obvious, academic approaches and even how to structure a report like a thesis.

This course added absolutely nothing to my knowledge. You're better off reading a recent blog post, or simply an introduction from a good book on applied ML/data science.

par Yaron R

2 janv. 2020

This course is borderline insulting!

The entire course content could be summaries on half A4 page.

The video clips are interviews with people working in the field. the reading material either reiterate the video clip content or presents a new concept in an elementary school level.

par Ankit S

30 juil. 2019

I dont appreciate the Peer-graded assessment part. It is simply not acceptable to be reliant on other students for assessment. This is just lazy.

par Weishi W

21 oct. 2018

For what?

par Dharmendra K S

14 août 2019

Descriptive picture of data science. Videos are short but nicely presented which gives an student a clear idea of the subject. Even Documents at the end of the course presentation are well explained.

par Linda T

14 déc. 2019

It is my first time to take an online Coursera course. I am badly grateful for your financial support. too many thanks seem not enough to express my happiness to finish this course about data science

par Akshay B

3 avr. 2019

This is a great course for anyone willing to start exploring the field of Data Science. It starts with basic definitions with proper examples that helps one understand this field with a greater ease!

par Krishna V K

23 févr. 2020

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.

Krishna

par Nathan S

3 janv. 2019

This was a nice and easy course, but the material was quite obvious and not new and could be included in one week lessons of another course.

par Dafydd J

17 janv. 2019

i thought a lot of questions were subjective at aimed at the academic field. It neglected to refer to real world situations and jobs, which is where the majority of learners will surely be coming from. Probably a little bit my own perspective, but I dislike when Data Scientists big them up to be so much better than every other profession and separate themselves from statistics so much (it's part of statistics and should just be considered a branch of such in my opinion, not a separate profession). There was too much of it here.

par Angelique B d l F

27 mars 2019

Very very superficial, most of the course material is about the profile, job and prospects of a data scientist. Hardly any of the content is about the actual science and technology. A few sketchy minutes are spent on Hadoop and deep learning, the rest is fluff. Waste of my time. Too bad, IBM is such a forefront player, I expected a lot more.

par Patryk W

10 mai 2019

Little value in terms of knowledge or skills for somebody paying for this course. Single Wiki document will cover the entire course content.

par Jan D

5 oct. 2018

Don't take it. No Course Instructors, no help. Not worth the money...

Even the Working Platform is always timing out or has a gateway error.

par Clayton B H I

12 déc. 2018

This is literally just hype for data science with no substance, include coding from day one or get real, I'm here to learn.

par Tian Q

15 oct. 2019

In the peer graded assignments, there are always students intentionally click on the lowest score!

par Joel L

22 oct. 2018

Didn't really learn anything but I guess it was a good gatekeeper.

par Sebastian S

28 mars 2019

IBM Cloud advertisement and nothing more.

par Preston K

1 oct. 2018

Utter waste of time

par Andrew F

3 janv. 2019

Great introduction to Data Science!

par Nicholas B

2 févr. 2020

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.

par Sobhan A

6 mai 2020

Completely waste of time! Very Disappointed with this course. This teaching method is completely inefficient. Some professional people will be interviewed and then you should answer quizzes after each video. It takes more than 3 hours to complete this course, however, all useful information could be provided in 5 slides and discuss them only for 20-30 minutes.

par Mahendra s

18 sept. 2020

very useful. i liked and enjoyed the journey of learning in these five weeks. the instructor is very clear and taught very interestingly. Thanks to her. she looked poised and cheerful and professional