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

4.7
étoiles
41,694 évaluations
7,766 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

SB
9 sept. 2019

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.

BB
21 févr. 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.

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51 - 75 sur 7,721 Avis pour Qu'est-ce que la science des données ?

par Abdul W

31 mai 2020

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.

par longmen

6 mai 2019

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.

par Kanchan P

3 janv. 2019

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

par Sergi

1 janv. 2019

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

par Amarjot S

7 mars 2020

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

par uzair k

7 mars 2020

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

par Mahesh K

3 janv. 2019

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

par Harsh R

1 juin 2020

Amazing course to a roadmap to data science

par Ferry T

20 août 2019

Great for introduction!

par IRFANI K

25 nov. 2020

Very good thank you

par Chan H D L

3 janv. 2019

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.

par Dwight F

1 janv. 2019

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

par Roger A

26 juil. 2020

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

par Xueting L

27 déc. 2019

This course has only maximum 20% useful content that could have been covered as an executive summary in 10 minutes instead of a whole week. A lot of the content is either fluffy socializing or irrelevant secondary information that has nothing to do with data science. As a toxicologist I'm interested in applying data science to my aggregate exposure estimation, and I have absolutely no interest in knowing the base salary of a data scientist working in North America, or which organization says what (facts do not care about opinions!) but unfortunately this was a mandatory question in the quizzes and was a waste of my time. And I find the self-introduction part of the final assignment a bit surreal and again irrelevant. I come here to learn about data science, not socializing. We have facebook, twitter and instagram for that. What my name is or what I do is irrelevant to others who take this course; where others come from is irrelevant to me; we're wasting our time saying something irrelevant and being forgotten by others in 5 minutes. Hoping to see more tangible content in the next courses.

par Vincent Z

7 janv. 2019

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.

par George O

21 août 2020

[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: https://bit.ly/3geOyfb

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.

par Stephen L

17 août 2020

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.

par Shaili P

23 sept. 2018

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!

par Deleted A

9 juil. 2019

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.

par Miguel A I B

23 mars 2020

Very good course to understand the environment that encompasses the area of ​​Data Science and data Analytics

Good to understand the objective of this carrier, the scope, objetives how it supporting the different verticals industries business, an the role it plays in building the strategy, also provides indication on what it takes to be a Data Science, good introduction to key related tools or solutions supporting the Analitycs evolution Artificial intelligence neural networks.

closing with key elements to be taiking into account at the moment to elaborate and provide Report & results by Data Science, never the less providing the relevance and demand that Data Science carrier in having at this moment due to the key results that provides in different scenarios of the day by day activities Industries, Science , marketing , sales etc

par Elzbieta K

16 sept. 2019

This course offers a great introduction when you heard about data science, but cannot really relate to it nor give your own concise answer to what "Data Science" is or what a "Data Scientist" does. I loved the interviews with the different students at the beginning, inviting different disciplines and backgrounds to the "Data Science Table". Professor Haider and Professor White give a thorough outlook on data science and career possibilities as well as skills that are necessary to succeed. The readings cover subjects like "Data Mining" and "Data Science Project Report Writing" and give a great introduction as well as guidelines to use later on the job. Great job they have done putting this course together! And I am looking forward to the next modules of the "IBM Data Science Professional Certificate"!

par julie c

27 sept. 2018

As a novice to Data Science this course met me where I was, at the very beginning, and provided an organized, overview of this evolving career field. The balanced mix of types of media used kept my interest and periodic comprehension checks along the way provided reinforcement of key concepts. As a visual learner I enjoyed the option to print out transcripts of all videos and reading assignments for note taking and highlighting. It was refreshing as well as encouraging to discover that 'soft skills' are highly prized in a good data science team member. I was energized to learn that I will be able to develop the skills and experience necessary to pursue a career in Data Science or Machine Learning and am eager to get started on the next course required to earn my Professional Certificate.

par Fatima G

21 avr. 2019

Even though I can not pass the quizzes and final assignment*, I have watched the videos and read the readings and answered the questions and I found this course very very very useful, because I am new at Data Science and this course give me the overview of what is data Science really is and How can someone become a Data Scientist. I really thanks Coursers and IBM. :)

*P.S: I am in Iran. Unfortunately there is a lot of problems being an Iranian. There are sanctions and limits against Iranian "People". But it is very sad that these people were not be able to use these free educational material. I passed courses in Coursera but I Can not get certificate because the name of my country were not in the list. We are also a human being.

With respect :)

Fatima Ghaffaari

par Caitlin L

25 mai 2019

I must have missed it but there were more than ten components in the final deliverable as far as the reading exercise went. More specifically, the differentiation was not clear as to which of those components were the ten main components. So, extra clarification would be good. Sometimes the content seemed to contradict itself, being that there were so many lecturers, so maybe a recap as to what the definitive answer is would also be really nice too. Maybe another lecturer could be added separately at the end of each section to recap what you expect the student to understand or to summarize everyone's answer into a more definitive answer.

par Suzanne L

31 mars 2020

The instructors and course material do a great job in covering the field of data science and explaining why data scientists are and will continue to be of immense value in the future. As someone with an operations management background and no formal academic education in Data Science such as PhD/MS in Statistics, Mathematics, CS etc., my initial decision to learn DS was serious, yet I still had a feeling of uncertainty in making this shift. Jumping into a new field and gaining quant skills can be daunting, but this introductory course really helped me to lay a foundation and solidify my intentions in pursuing this career track.