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

4.6
étoiles
16,942 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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1801 - 1825 sur 2,065 Avis pour Data Science Methodology

par Kazi M R

26 avr. 2020

The concepts discussed in the video lectures are not clear enough. Also the case/example used in the video lectures have complicated terms and requires some subject matter knowledge. However, the labs are very well designed which helped in the understanding process.

par Patrice J E

5 avr. 2020

There were issues with Jypter notebook not working. I also felt for some of the steps such as Data Understanding, Data Preparation etc the descriptions of the stages were too similar which let to confusion. See Week 2 Forum messages. Overall i enjoyed it nonetheless

par Mak C Y

26 avr. 2019

Grateful if more explanation or more cases can be given. Also, I found that the final assignment has a mistake, making the total available scores changed from 10 to 9, which force us to make a "perfect answer" to get almost a full mark (the passing mark is 8 marks).

par Firda S

26 janv. 2020

I think the case study is too hard to understand. The analogy using cooking it's good, however, the case study using hospital problem it's really hard for me to understand. Maybe it could improve if it's using like general case study that everyone would understand.

par Marvin R

19 mai 2020

The examples were confusing at some point. The videos could've expanded the concepts more so that the differences between each stage of the Data Science Methodology becomes clearer. The case study in the video is also confusing for someone in a non-medical field.

par Ellen H

17 févr. 2020

Pretty good course, but could have been a little more challenging. I'm glad I learned the process, but I'm ready for some more hands-on work. This was getting close- I think the final projects, especially for week 3, were good practice to apply what I learned.

par Suyog J

9 oct. 2019

Appreciate the content so far. This can be though made more in-depth when it comes to hands on. Including graded level hands on practice can enhance the learning experience the students get from this course.

Thanks for enabling us with all through the course.

par Chaojie W

26 oct. 2019

I understand that this video want to give a full image of Data Science. But its case study including too much low-frequency vocabulary / terminology, which is an obstacle to beginner. And some reading material 's exercise is not very necessary...

par Alina T

27 juin 2019

I found this course to be a little bit too vague and theoretical, and hence, difficult to understand sometimes. I personally prefer to study and work with hands-on and applied aspects of Data Science instead of theory and vague definitions.

par Arunmozhi P

5 juil. 2020

The Videos provided a good overview of the process. But felt like they were extremely short for the concept they were covering. I would have liked them to be a bit longer and illustrated like the ones from the What is Data Science? course.

par Linh T

9 mai 2021

There's a lot of reading. If there's more hand-on training, that would be great, The tools provided to do exercise sometimes didn't work. I have to loaded several times to complete my work. That delayed my time to complete the course,

par Myles A S

9 août 2020

I had a few issues with the IBM cloud that could not be addressed quickly. As a result I completed the course without being able to do the all the assignments, so I missed out and did not get all the value I should have from this course.

par Amit K

5 avr. 2020

Videos are somewhat confusing. They are not target to the current topic but also states about other topics as well in the same video, which makes it difficult to understand and easy to loose track of what is being taught in the video.

par Daniel T F

16 mai 2019

Presents you a good overview according the main topics of data science methodology. The case study is a good example to illustrate to content. But with respect to my experience the labs are very limited concerning the learning effect.

par Ivo M

13 déc. 2018

The narrator was quite fast and I could not engage with the video lectures so well on this course. Consider review the Hospital case study too, which is quite complex when trying to understand the new concepts on the methodology.

par MUNIB U R

22 juin 2019

The course is a bit confusing for a beginner, the concepts should be clearly explained, the prediction model and the descriptive model should be taken in different videos.The learner should understand the difference clearly.

par Ashwini K

4 juin 2020

It would nice if case study and lab example would be same to follow more deeper understanding between video class and example .The web scraping example is nice and should be in presentation for understanding purpose.

par Roy R

3 avr. 2019

Difficult being able to apply the final test to the complete module objectives. Though it was good foundation, felt it should be split into several workable modules/stages instead of all 10 methodology steps at once.

par Munkhbolor G

9 mai 2020

All example and cases are related to hospital. Every single subject with different case would be highly appreciated and helpful to others. Hospital case were kind of confusing as i am NEW BEE for data science.

par Yves J

14 août 2019

Methodology course should be done at the end of the whole certificate course or at least when the student has a better understanding of all the statistical methods available (regression, machine learning..)

par Roshan P

17 avr. 2019

This could be little bit more in detail. The content and the methodology was introduced but could be more in detail about all the analytical approaches available and why we chose decision trees for the CHF.

par Jason L

24 juin 2019

Good intro, but I felt the introduction to python might have been better before this subject. Could have spent more time on the Labs, seemed more complicated if you didn't have any background in coding.

par Louis C

27 mars 2021

The course has very little material, it feels like it could be a chapter in a course. I learned a valuable and good methodology though. So the content is good, it just feels like very little contents.

par Erik P

29 mars 2020

Rather open ended. The main points should be crisper. For example, why is feedback not part of the final assessment , where the keywords repeated in the training and in the final assessment?

par Aman R

8 mai 2020

The last course jumped to python notebooks which has a lot of coding,while Python language is yet to be covered,I feel the notebook assignment should have followed after the Python module.