Great course except for the quizzes. The quizzes sometimes focus on arbitrary moments from the videos, to make sure you were paying attention, rather than asses the practical, applicable information you have retained. And then you can take them multiple times which defeats the purpose of even making sure we are paying attention! They should either get rid of they quizzes altogether, or make them better and place a more strict limit on the number of attempts.

This is a great course with many lessons presented in videos that are easy to understand. The course provides the framework for data science methodology. Although easy to understand, moving from concept to practice can be challenging. For me, the challenging part was finding more information and examples of the descriptive (diagnostic) models. To maximize one's learning in this course, one must be prepared to do some searching to find appropriate examples.

My honest review: This course has a lot to teach, really. Personally I had to watch videos and read the articles, practice the labs more than once (Maybe because I didn't do it all at once). There is a serious stuff going on in this course at least in my POV. And yesss after having completed this course, I now have a better idea of how to proceed for a data science project.

Although I'll have to go through it some more times just to master it fully.

This course Data Science Methodology is definitely very important and useful part for becoming a Data Science but the content used in the module were a bit complex as the case study (Hospital related case study) used in the module was a bit difficult to understand because of its technicality. Maybe a normal FMCG company or a Fast Food outlet related case study would have been easy to understand. However overall the course was very good and useful.

The course structure is good. But please fix IBM Watson Studios' issues. It always doesn't load correctly and you always have to waste hours checking forums on how to fix it. The fixes don't usually work correctly. Even if you clear cache, cookies, use incognito, it still doesn't load correctly. Also, please fix issues in the labs, some codes that you're not meant to change are showing errors, so again, you have to go to forums to look for a fix.

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.

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.

It was a very informative course; in this Course, the instructor has how one should solve problems with data science while collaborating with stakeholders and why Data scientists should take it slowly while finding the solution. Still, the voice and Explanation of the instructor is very robotic and not pleasing for hours of listing and understanding. I had to look into the course comment section for the proper notes.

Very well structured and thought out with great real world studies (both in videos and in python notebooks) to help understand each stage of the data science methodology introduced. Videos could be a tad longer, i feel some of the graphics on the slides were busy and could be better explained. Overall though, great introductory course! Makes you hungry to learn more to execute these stages, especially with modeling.

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.

Very good content regarding the 10 stages of data science methodology and good case study examples. Only problem is the lab part; some statements/directions such as type "Shift + Enter" makes no sense to me. While I was able to download the data, I don't know how to run them according to the directions. I feel the directions need update to meet beginners or people with no much experience.

The course is good but there are so many things unexplained properly. I have to use so many other resources to fully understand the important issues such as modeling. It needs to be improved and there should be other external resource reading suggustion. The presentation is excellent. I will not forget the points because they are presented in a nice and easy to remember way. Keep it up!

Really loved the course! Few problems though. First of all, the instructor is very hard to understand. English isn't my first language so it's kind of hard to keep up with his speed and exactly understand what he is saying due to his advanced vocabulary. Nothing wrong with the course though. Although I think everything could've been explained more simply and easily.

It's very useful to be aware of separate steps in the activity of learning how to answer business questions with data. A concern, however, is that the contents of this course do not clearly distinguish between the steps. I appreciate that in real situations these steps are not distinct, but the purpose of the exercise is to conceptually distinguish them.

Excellent introduction to the data science process. The videos could have made use of a simpler example however, and there could have been more specific explanations about the kinds of models that data are used but the lab activities made things a bit clearer. The flow of the discussion was very clear though, so overall I'm very satisfied with the course.

My only suggestion will be to more clear on the lab session. Lectures , sometimes are hard to follow in lab or have difficulty to open files. Maybe , an update of lectures so we can follow lab easily. However, I learned on e important lesson, practice through lab , delete and try again it helps you to be familiar with the subject of the lecture.

I loved actually getting to see a practical example of how DS could be applied with the notebooks. It helps thinking on ways on how one could start their own practical projects in DS, and it increased my genuine interest in DS beyond just for job reasons. For sure it's more interesting than learning about tools I probably won't even use yet!

I will say since it is an online course and there is no physical lecturer present, plus there is no real time doubt clarifying options, the videos should be a bit slower, some times you are still thinking about a part and the next thing you realise is the video is near to its end.

rest i liked the content of the course its very good.

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.

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

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.

This course is like a novel: too much words to explain a few concepts. I consider that you can compress a lot the length of the course. As a comparison I found here https://www.upgrad.com/blog/data-science-methodology/ an article called "Data Science Methodology: 10 Steps For Best Solutions". Straight to the point!

The final assignment was, in my opinion, too open ended and did not seem to be sufficiently conducive toward an in-depth application of the course material. A step-by-step walk.through project exercise on a pre-determined topic/scenario with specific questions at each stage, would have probably been more useful.

I think the course material was perfect. The final assessment could have been better, though. The way of giving answers and feedback can be improved. If you divide each phase of the project in a separate question, and enable peers to give feedback on each answer it would be better.

Thanks! Keep up the great work.

I enjoyed this course very much and appreciate the systematic way that the material was presented. The case studies were fantastic and I am taking away a structured methodology for completing data science projects. Special thanks to the professors for creating and teaching the course material. Well done!