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学生对 IBM 提供的 Data Science Methodology 的评价和反馈

4.6
4,249 个评分
395 个审阅

课程概述

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....

热门审阅

AG

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 :)

SJ

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...

筛选依据:

1 - Data Science Methodology 的 25 个评论(共 445 个)

By 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

By 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.

By Husain B

Jan 29, 2019

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

By 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.

By Jiayang Z

Feb 17, 2019

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

By 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.

By Ponciano R

Feb 04, 2019

Fine for an introductory course

By 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.

By Johannes

Jan 16, 2019

this course should be a little later in the IBM sylalbis

By 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.

By A L I S O N

Jun 15, 2019

The final assignment had me ham strung. You are supposed to do each of the 10 steps at the end, with very little guidance on HOW. The there are specific methods shown but what if they don't fit your final assignment example?

By A.S.M. E H Q

Jun 15, 2019

Awesome!

By Katarina P

Jun 15, 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.

By Hadi S

Jun 14, 2019

This course helped me to get to know data science methodology.

By Robert T

Jun 14, 2019

I thought that the material was certainly important, but felt that the quizzes were more memory of the videos rather than an intuitive understanding of the material. Maybe more case studies, or a less complex one might make the material more easily digestible.

By Juan D P

Jun 13, 2019

This is a great course in which we learn all the steps, one-by-one, to face a problem using data science methodology.

By Sameer M

Jun 13, 2019

very nice way of explaning the course

By Rahul K

Jun 13, 2019

Best Course, If you want to learn how the data science applied to the business or general problem

By Anjan S

Jun 13, 2019

good knowledge gained

By Philipp K

Jun 12, 2019

too much information on slides. Use more pictures for visualization.

By Ivan B

Jun 12, 2019

Not a useful course overall. The basic premise is fine and logical, but this course did not do a good job differentiating between the different steps involved in the Data Science Methodology and the terminology chosen and used was not explained very clearly or consistently.

Very dry and wordy videos. Example cases used were not straightforward and did not help me understand the concepts that were being conveyed. Good concepts to learn, but this course could have done a much better job at explaining them.

By VIKRAM K P

Jun 11, 2019

it' s a good course

By Pritam D

Jun 11, 2019

One peer gave me fewer points in my final assignment.

By Manthan M S

Jun 11, 2019

The material is greatly informative and clearly explained. I'd some trouble understanding the case study. A simpler one would be really entertained and helpful. Thanks.

By Govardhana

Jun 11, 2019

Very nice course with full of theory but has hands on lab practical