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Data Science Methodology(으)로 돌아가기

IBM의 Data Science Methodology 학습자 리뷰 및 피드백

4,249개의 평가
395개의 리뷰

강좌 소개

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! LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate....

최상위 리뷰


May 14, 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 :)


Aug 09, 2018

This is my favourite in the series, the 10 questions to be answered were mind opening. The repetition after every video makes easier for important points to stick to the brain. Very good indeed...

필터링 기준:

Data Science Methodology의 545개 리뷰 중 1~25

교육 기관: Clayton S

Feb 02, 2019

This one is fairly painful to sit through and needlessly complex. Other sites have explained this much simpler and clearer than here

교육 기관: Ozge I

Jan 24, 2019

1) This descriptions in this course are very dull. They need to be supported by better examples which do not include a lot of terminology specific to the topic.

2) The questions in the videos can be better designed to evaluate the students' knowledge about the topic, e.g., letting them apply their knowledge in new examples. Some questions are redundant such as the name of the person who designed the data science methodology or questions specific to the case study and does not necessarily provide insight into general concepts.

3) Simply reading what is in the slides is not a good use of videos and cannot keep the focus of the students for a long time.

4) This course might be located after the Python for Data Science course or even later so that the students could have a more meaningful final assignment, actually applying what they learned on a small data set.

5) Knowing a subject and teaching a subject are two different things. I hope you consult a university professor in the field about how to teach these courses. There is a lot of room for improvement in terms of the pedagogical perspective.

교육 기관: Jianfei Z

Jan 20, 2019

Nothing is discussed in details. For people know nothing about data science, many topics are not explained and they won't understand anything valuable; for people already have a background in data science, the topics are useless and too shallow.

교육 기관: Husain B

Jan 29, 2019

Instead of CHF the case study should be change to something which everyone can understand.

교육 기관: Lauren J

Apr 03, 2019

This was a good course. It was an overview of the entire data science process, which was helpful for me since I didn't really have a good understanding of what data science meant before this class. Now I have a much better understanding of what people mean when they say data science. Also, this class gives a good orientation for other courses; for example, I would see "data mining" courses on Coursera and not understand how that fit in with data science. Now I do. I would recommend this course for people very new at programming and data science, like me.

교육 기관: Jiayang Z

Feb 17, 2019

The example should change to a easier one. This example is hard to understand.

교육 기관: Kristoffer H

Feb 05, 2019

Quizzes quiz on material not covered in the course or directed to externally. Most of the quizzes are word games and do not apply concepts covered in the material. Everything from how disconnected the quiz questions are compared to available information provided in the course to the peer-graded final assignment show little or now effort was put into composing this course.

교육 기관: Sasha M

Jul 27, 2018

Really difficult content to digest without much written information. This course needs to provide more readings and the videos need to provide more text, as opposed to relying on voice instruction.

교육 기관: VIJAY K N

Jul 18, 2019

The base concept for every Data Scientist and taught excellent here in Coursera.

교육 기관: Ponciano R

Feb 04, 2019

Fine for an introductory course

교육 기관: Johannes

Jan 16, 2019

this course should be a little later in the IBM sylalbis

교육 기관: chong c c

Jul 22, 2019

Clear and simple to understand.

교육 기관: Aniket R

Jul 21, 2019

It was a good course with very easy to understand material and methodology.

In my opinion additional optional reading resources or case study links is required for this to be a 5 star course.

교육 기관: Yau W K

Jul 21, 2019

Very informative process of how Data Science is practiced in industry

교육 기관: ranjeeth

Jul 21, 2019

Some times are not easily understood for beginners content needs improvement. There are some missing threads

교육 기관: Padmanabha K

Jul 20, 2019

This course gave a clear step by step methodology to deliver a successful Data science project.

교육 기관: Sayak C

Jul 20, 2019

Too complex of a case study to understand stuff. Also, too boring and theoretical and very less interactive.

교육 기관: Lawrence L

Jul 20, 2019

A good overview of data science methodology, with appropriate emphasis on the fact that it is a continuous process with many repetitions that involves stakeholder feedback, thoughtful planning ahead and constant adjustment.

But, I felt there was too much time and emphasis on the details of the specific examples given, and not enough focus on the actual concepts and methods, which could be better explained and their importance better illustrated. The python lab in particular is a well-made example but not very educational from the student perspective.

교육 기관: Emilio C

Jul 20, 2019

Great experience

교육 기관: Esteban P

Jul 19, 2019

I think that they should define more the specific concepts of all the states of the methodology, and then make references to "hypothetical" cases. Personally, I lost more trying to understand the examples and I had to go to find more specific information in other sources.

교육 기관: Abdullah A

Jul 19, 2019

Content should be explained further!

교육 기관: Aleix C T

Jul 17, 2019

good content, surprisingly weak delivery and teching

교육 기관: Inggriani W

Jul 17, 2019


교육 기관: Akash V

Jul 17, 2019

This course gives a detailed outline of data science methodology and approach of a data scientist.

Thank you so much for offering this course.

교육 기관: Djan d A M

Jul 16, 2019

Excellent course!