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Data Science Methodology(으)로 돌아가기

IBM의 Data Science Methodology 학습자 리뷰 및 피드백

4.6
11,517개의 평가
1,186개의 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

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 :)

JM

Feb 27, 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.

필터링 기준:

Data Science Methodology의 1,178개 리뷰 중 26~50

교육 기관: Jianxu S

Aug 24, 2019

I would probably give 4.5 stars if there is such choice. Overall, it is good and fun to work through the material but there are places where the message was not crystal clear. For examples, the analogy between data scientist and cook is not always helpful. One of the quiz question described model 2 but was associated with the wrong cost ratio (4:1 instead of 9:1). If Receiver Operation Characteristic (ROC) curve is an important concept then perhaps a little bit more explanation is warranted.

교육 기관: Guilherme P d C

May 06, 2019

For the case study presented, specially during modeling and evaluation phases, more elaboration would make the course better. Specially during modeling evaluations and ROC.

Also the course being conducted in a recorded slides is not appealing for student engagement. Would be great to have some videos with people explaining, like in the in course 1 of this program.

교육 기관: Jason K

May 21, 2019

This course made me realize that people tend to jump to execution mode without even understanding what the business really want from them, and by not having a proper understanding they either produce a system that adds no value to the business, or they waste unnecessary time. The tools from this course is very helpful in any field that you are working in.

교육 기관: Mark L

Jan 27, 2019

While the course is brief, exploring only one methodology in depth (predictive), it is well done. I could understand the exercises well. One fix would be a quiz asked what percentage was on a previous table. I did not take the time to memorize the values in the table as I don't see how that is relevant. A better quiz question could be been formulated.

교육 기관: Varun V

Nov 12, 2018

This is a very nice course since understanding this course has helped us in thinking deep about various stages of a Data Science project. Moreover, the author has taken a case study and used that for explanation of all the concepts which made it look more like a story rather than just boring lectures. Very helpful and nicely organized.

교육 기관: Leonardo R

Jul 10, 2019

This course provides the perfect explanation of what goes into the data science methodology. The course guides students through an in depth analysis of each stage with examples and labs so they can follow along. The course also uses the data science method to solve a real world problem that one may encounter in their career.

교육 기관: Gideon R

Nov 03, 2018

Having a structured methodology is an essential part of one's work. Nothing is more tempting than shortcuts but we always end up regretting them. The Rollins approach to data science, when properly understood, really clarifies the sequence of steps involved in achieving a result that will satisfy the organizational needs.

교육 기관: Jason J D

Jul 30, 2019

Good course. Very important when it comes to implementing Data Science in real life. The instructor explains the life cycle and flow of the Data Science methodology along with an example scenario. Understanding and differentiating between the different phases of the methodology is much easier because of this.

교육 기관: Baris E P

Dec 13, 2019

Due to its approach to methodology, the course as a whole looks intimidating, but actually what it does is great way to teach a methodology, which is useful in both data science working space and academic environment. The course is quite easier than what it requires to fully understand the methodology.

교육 기관: Jose J D

Sep 24, 2019

Absolutely Amazing Course. Clear, providing useful plug and play methodology. One of the best courses I have taken. One suggestion is to improve the quality of Slides on the presentation, I should have to evaluate with four stars due to this, but the quality is so high that I would go with five stars.

교육 기관: Sofia L

Dec 29, 2019

This course has completely blew my mind. I now see how data science can be applied to everything and can help find solutions to anything! from social issues to business. I thrilled that i have gained new insights from this course that I will put in practice from now on in every day in my life!

교육 기관: Matthew L

Sep 08, 2019

This course was very helpful in putting the whole concept of data science methodology together. As someone currently working in data science, I found the methodology excellent, as it clearly laid out the conceptual reasons for how and why to successfully complete data science projects.

교육 기관: Patrícia P A

Jan 17, 2019

Maravilhoso! Quem trabalha com análises e/ou relatórios já tem uma ideia dos passos, mas ainda assim é válido porque estrutura conhecimento, entra mais a fundo nas etapas e traz muitas informações interessantes. Pra quem não trabalha pode conhecer como fazer uma análise desde o início.

교육 기관: Ramiro B

Oct 10, 2019

I think this is an amazing coruse, because it gives you the skill for organizing the entire data science process as an organized sequence of strategic stages which are coherent between themselves and together give a way to transform a problem to a real solution in a step-by-step way.

교육 기관: Nita A

Dec 12, 2019

Was a fun and interesting course. Got to learn about all the stages of the Data Science Methodology from problem question to be answered to modeling to evaluation to deployment to feedback. Enjoyed the case study, labs, and final assignment. Can't wait to start the next course!

교육 기관: Jurom N

Jan 21, 2020

The course on Data Science Methodology was sufficient enough to understand this lesson given its examples, scenarios, explanation in each methodology stage, etc. The expectations of learning were also clear and personally, my memory retention is high after taking each course.

교육 기관: Benjamin S

Mar 25, 2020

This course is simple yet important for data scientist wannabes. It provides you with important stages of a complete project. Personally, like the effort in the extra lab material, deepening what we have learnt. To improve, I hope to get more toolkits in analytics approach.

교육 기관: SHUBHAM K

Mar 07, 2020

This course introduced me to the Data Science Methodology in a very good manner. The best part was hands-on lab experience. And the last assignment really helped me to collect all my learning and implement it. It was really a very good experience. Thanks Coursera and IBM.

교육 기관: Zhari C

May 06, 2019

I am learning so much! Glad to have the opportunity to learn at my own pace. This course is laid out beautifully. If I could change one thing it would be to have updated slides and photos of IBM Watson, not the Data Science Experience. The screens do look very different.

교육 기관: Ruhul A

Mar 27, 2020

Awesome, just what is need for a good and strong background for a perfect Data Science project methodology, need not be only data science this is universal in nature for all kind of business problem. Very well drafted and made topic with good list of course flow

교육 기관: Leanna W

Oct 17, 2018

Excellent course! The approach is easy to following and has a proven track record for solving business solutions. I highly recommend this approach for anyone that want to learn more about Data Science or for anyone interested in becoming a Data Scientist.

교육 기관: Евгений Г М

Mar 29, 2020

The course is useful primarily for its systematization of all approaches in data science. A step-by-step development of research is demonstrated, starting from the statement of the problem and ending with the found solution to the problem. Useful course.

교육 기관: Jeff L

Jan 23, 2020

It's really a lot of information than I expected, but it is certainly helpful for helping me to further understand data science. My only suggestion is to include more explanation to the code in the labs to make it easier to interpret for the students.

교육 기관: Bibhu A P

Nov 05, 2019

The methodology was really great. Though this is somewhat a modified version of the CRSIP-DM methodology being used in Data mining. The labs were wonderfully set up to understand the topic. The case study was the most interesting aspect of the course.

교육 기관: Raphael N

Mar 04, 2019

This was one of the trickiest courses I have taken yet. I have had to re-read the documents and watch the presentations to get the concept clearly. I highly recommend it to anyone willing to be patient to understand the under-workings of data science.