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Data Science Methodology(으)로 돌아가기

IBM의 Data Science Methodology 학습자 리뷰 및 피드백

4.6
stars
9,945개의 평가
970개의 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 :)

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...

필터링 기준:

Data Science Methodology의 961개 리뷰 중 601~625

교육 기관: Ritwik G

Feb 20, 2019

NA

교육 기관: Abdulah H A

Jul 14, 2019

Some terms are being assumed to be known for the students. It would be better if the videos are more interactive in which a real person is being shown while explaining with supporting graphs and pictures and numbers. Some methods are being used in the case study like the decision tree which to some extent is not fully explained how is it the best method and what would happen if another method had been selected instead. Some graphs and pictures presented in the videos should be available in a different section for later used such as the diagram of the Data Science Methodology under a section designed to provide the students with additional materials.

교육 기관: E. R " A

Sep 19, 2019

The Data Science Methodology course was exceptionally well done. It was served up in bite sized morsels that were easy to ingest. In fact, they were so tasty, one would often find oneself going back to take another bite or two! Delicious and cognitively nutritious!

I believe the Data Science Methodology is crucial to leveraging the advantages of Big Data, Artificial Intelligence, and Automation as we driver ever headlong into "The Age of Cognivity!" Not a lecture, just an observation!

교육 기관: Amber B

Nov 25, 2018

The videos for this course are a little tricky to engage with and the examples are messy and difficult to follow. Perhaps there is a better strategy to teaching the methodology. At the very least for this particular course in the IBM Professional Certification it might help to include a summary video that puts the entire methodology into use in a single video from start to finish so that visual thinkers can have a better handle on the concepts.

교육 기관: Amy H

Jul 01, 2019

Very good course on the methodology behind Data Science. Some of the quiz questions were worded strangely and were slightly misleading, based on the information from the videos. Overall, it's really great to have a course like this that shows you why data scientists do what they do and why each step is important. I also really liked the case study used, which helped to highlight how these methods would be used in real world scenarios.

교육 기관: Carlos S Á

Jun 10, 2019

I think that the course was kinda hard to understand. I don't know if the Case Study is an ideal one to understand how the Data Science Methodology, specially when you have differente backgrounds such as the way the health systems may work in different countries, I rate this 4/5 because I found the course really important to learn but it is way too challenging to understand in contrast with the other courses.

교육 기관: Ankur G

Jan 03, 2020

A great course to get insights about methodology used within Data Science to analyze and visualize data to make effective decisions. I thank the professors to make this course interesting and worth it. Only thing is, videos can be made in a better way so as to facilitate people with non programming background. Maybe some basics of programming would help.

교육 기관: Dylan H

Mar 07, 2019

Much better / more useful than the prior two classes in the IBM Data Science track. The methodology described is a tad "big company" / slow-ish, but ok with it being used as a model for completeness, and am sure it will be of help to a lot of people, (who hopefully took notes to remember it! ;) ) for a long time to come.

교육 기관: David C J

Jan 02, 2020

Course really explains the Foundational approach clearly, The final project was really important to actually apply the methodology was were I learned the most. However, the case study showed in the modules was, sometimes, hard to understand due to technical vocaulary. A glosary would be good to have since the beggining

교육 기관: Jess M

Jan 30, 2019

The information is useful and relevant. But the labs are limited in their utility, since the student isn't actually doing any of the work, just following along in the example. The lab information could just as easily be presented in the video, and vice versa. So it isn't really a "hands on" activity for practice.

교육 기관: Jeffrey R

May 01, 2019

The access to the data source from the Jupyter Notebook kept giving me a 403 Forbidden error so I was unable to see the results of the Python codes in the .ipynb files because the I don't think I had permissions or the link is/was outdated. Otherwise, very informative and exciting to learn.

교육 기관: Steven P M

Feb 02, 2019

It is refreshing to see a data science course that clearly talks about the methodology (which is fundamental to thinking about the process) rather than the technology (which, while useful, but the lure of technology is often used sloppily without real underlying thinking and reflection.).

교육 기관: Antas J

Dec 04, 2019

the course was very particular about the hospital example i think it could have been more generalized or templated so that it could fit with other industries' understanding.

Rest was okay enough, although not very interactive since there is only presentation on screen and no instructor.

교육 기관: Victor(JingFeng) X

Aug 13, 2019

Extremely powerful framework, good case study, mediocre analogical explanation. I am really impressed that IBM put heavy emphasis on the methodology before starting off with anything else. Having the mindset and the framework for execution is the most critical thing of any endeavor.

교육 기관: Ariana L

May 17, 2018

Good for those just getting into data science/analysis that don't know the full circle process beyond the number-crunching. For those that have produced full-scale deliverables, not entirely necessary, although you could get through it in a relatively short amount of time.

교육 기관: Muhammad S H

Jan 13, 2020

Good course. However, I think the concepts are a little tough to understand at this stage. Maybe this course can be provided at a later stage after other concepts such as Python development are covered. Also, the content of the videos should be made more easy-to-digest.

교육 기관: Berkay T

Aug 30, 2019

Overall content of the course is good, but I think a clearer, more common example could have been selected over congestive heart failure. Also sometimes there is a confusion between the elements of methodology, so a reading to complement videos could help a lot.

교육 기관: 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.

교육 기관: Chaoyu P

May 31, 2019

Important overview to the systematic methodology of data science that can easily be overlooked. Interesting case study provided, along with another example in the assignments, showing that this methodology can be applied to all types of problems and domains.

교육 기관: Carol L

Aug 26, 2019

I really like this course! I would like to know more about techniques a model statistics to understand more the processes in Analytic approach, data preparation and modeling and apply correctly in a specific situation in a data science project. Thanks!

교육 기관: Djaber B

Jul 13, 2019

Even though I used to work with data, I found the data science methodology a must course for a future data scientist. I like how each stage of data science workflow is summarized to a wheel where each stage communicates with others in an efficient way.

교육 기관: Girish B

Jul 10, 2019

I loved doing the peer graded assignment but i thought it would have been better to put the course a little later as for newbies they tend to loose interest for the simple fact that the cant understand the codes at times put up in the notebooks

교육 기관: Jesus C C

Dec 28, 2018

The course is good and the content but I, as non native english speaker, would have preferred a clearer Case Study and avoiding questions in the Qualification Tests around it, as many term were not clear to me and some issues were quite subtle.

교육 기관: Yongda F

Jul 16, 2019

I think this course is quite brief, some of the terminologies are not well explained. But overall, this gives some insight into data science and is a pretty good introductory course. I hope this course can have more detailed knowledge.

교육 기관: Siripat W

Nov 01, 2018

I think this course need more resource to teaching a students, It's so difficult to understanding but I received a lot of knowledge from searching a resource, However if it possible to attached more resource that/s be great. thank you