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Avis et commentaires pour d'étudiants pour Data Science Methodology par IBM

4.6
étoiles
16,947 évaluations
2,066 avis

À propos du cours

Despite the recent increase in computing power and access to data over the last couple of decades, our ability to use the data within the decision making process is either lost or not maximized at all too often, we don't have a solid understanding of the questions being asked and how to apply the data correctly to the problem at hand. This course has one purpose, and that is to share a methodology that can be used within data science, to ensure that the data used in problem solving is relevant and properly manipulated to address the question at hand. Accordingly, in this course, you will learn: - The major steps involved in tackling a data science problem. - The major steps involved in practicing data science, from forming a concrete business or research problem, to collecting and analyzing data, to building a model, and understanding the feedback after model deployment. - How data scientists think!...

Meilleurs avis

AG
13 mai 2019

This is a proper course which will make you to understand each and every stage of Data science methodology. Lectures are well enough to make you think as a data scientist. Thank you fr this course :)

JM
26 févr. 2020

Very informative step-by-step guide of how to create a data science project. Course presents concepts in an engaging way and the quizzes and assignments helped in understanding the overall material.

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1976 - 2000 sur 2,065 Avis pour Data Science Methodology

par SG

6 janv. 2020

Complicate course with poor valuation system. It contains a lot of basic information but without detail clarifications. I read external resources for a complex understanding of the material.

par Katarina P

15 juin 2019

The peer review system is just awful. It takes ages to get graded/be able to grade others and the peers might not demonstrate language level required for grading an essay-type assignment.

par Alejandro C

22 oct. 2019

"Ungraded external tools" are not avaliable. For me, the applied example using medicine was hard to follow. Perhaps something less complicated could help explain better the problem.

par Xinyi W

7 janv. 2020

Too theoretical and the medical example was such a bad, hard to follow one for the course!

It could be content for one week instead of making it to a full-length 3-week session.

par Nuttaphat A

4 juin 2019

Well, I would say this course has been disappointing so far. I hope it gets better soon. Otherwise, this will be the worst online course I have ever taken in my entire life,

par Sergio R R

19 avr. 2020

It is a bit too basic and vague. The methodology they propose and the supportive material is useful and interesting bur there are many gaps on the hands-on training.

par Iago T P

20 avr. 2020

The course is quite theoretical, I would appreciate more reading material. I don't think that the best way to explain the concepts are by using video lessons.

par Jake Z

21 janv. 2020

The quizzes focus too much on the nitty gritty details of the case study, so it is easy to get lost in that and forget the big picture of the methodology.

par Phil C

21 sept. 2020

The videos were very monotonous and frankly quite boring. The content was clearly delivered, but the assignments did not reinforce what was being taught.

par Magdalena R

6 nov. 2018

The course is interesting but I don't like robotic teaching. I think is missing some human interaction like other coursera courses I've done where you

par Erin

25 mai 2019

The course materials need updating. The IBM platform has changed which has made it hard to maneuver the website and follow the directions given.

par Neice M

27 févr. 2020

This needs to be revised. Its very confusing, you need more assignments between lessons so that we can show we understand what we have learned

par Devraj S

5 juin 2019

This course can have an easy example to explain the methodology for Data Science but there are hard ones and I really don't like it that much.

par Dhanush R

17 sept. 2021

The case study was too difficult to understand. I wish a more easier case study was picked to elaborate the datascience methodologies on it

par Elvijs M

17 avr. 2020

Maybe of interest to people who have no clue about any sort of methodology or problem solving. Too boring and repetitive for everyone else.

par Saumitra P

20 nov. 2021

Not good for beginners, the CHF example was complex and I think this course should be updated with better examples and explanations.

par Jennifer M

16 mars 2020

Terrible. Very basic. The tool tasks didn't work- timed out. Has no one to grade when it was over. I hope these get better.

par Georgios G

5 nov. 2019

I felt that the course was ill prepared. Also I did not like the explanation using the food example. It was not clear

par Dina K

22 sept. 2019

I would have liked for the course to go more in depth of the statistical tools. It was confusing and hard to get.

par Aymal K K

4 déc. 2019

The case study should have been a general case bit specific to health its difficult to get around the course.

par Taha S

8 sept. 2020

This is the 3rd introductory course in this professional certificate. I am yet to learn something useful.

par Amit K

18 avr. 2020

Examples are not clear. wasnt able to understand the methodology so well. Please use lay man examples.

par Fábio S V

2 mai 2019

The methodology could be more explained, with different examples and the steps could be better explored.

par NEHA W

13 avr. 2020

The case study in the video is quite boring and it was very time consuming to understand the it.

par Aviv H

15 sept. 2018

Very high level in most parts and in some is to detailed without any noticeable reason.. (IMO)