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.

Less than a minute after summiting my Final assignment it came back with peer review that was disappointing. I describe every data science methodology stage and the feedback for that section was that I describe some of the stages but no all.

Need to repeat some of the videos. Also I have to find different case study since at first you can't really digest some of the case study. But after tried different sources of case study, I managed to grasp what's the author trying to tell.

Gostei muito, achei muito bom pra introduzir conceitos básicos e ir se ambientando ao pensamento de data scientist, mas um problema foi não ser mais explorado alguns conceitos e tecnologias. Acredito que o curso poderia ser mais longo.

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.

The case study in the video was pretty complex to understand. Thankfully the case study taken in lab ( japanese dishes) was very simple and easy to understand. Overall a good course to understand the methodology used in data science.

Slides needs to improved , text spoken should be presented in text form in Video as well. Over coverage is comprehensive very informative , for learning purposes text should be presented. over exercises and tests are very high quality

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

I believe this course is key to have an overall understanding of the Data Science Methodology, however found that it was a bit un-organized and some stages werent fully clear, so had to look for additional information in other sites.

This is a good course - I would have given 5 stars for the course if there was a hands-on lab to build a Supervised Regression model with some data sets and introduced the learner to normalization and fundamentals of statistics.

Doing it for the IBM data science certificate, definitely liked this course more, as what is taught is linked in an excellent way with the interactive Notebooks, letting you experiment with the code to learn their inner workings.

Great walk-through of the general steps of a data science life cycle! My only complaint is that the materials often spoke of more than one step of the ten in a video, making it easy to confuse what things belong to each step.

The instructor's speaking pace was quite fast so had some difficulty understanding the lecture because of that. The case studies should be kept simple. Congestive heart failure case study was quite difficult to understand.

Well explained and concise. The test questions were at times hard to understand and the answers to some were in the following videos. The practice questions should be related to the video just watched not the next one.

Capstone project is a bit limited on 3 topics to choose from.

Why not more creative or even let the user come up with his own problem !!

Still you do learn a goo methodology to handle a problem with datascience approach

This course through the explanatory videos of each stage of Data Science Methodology and a case study provides you with the mindset a data scientist needs against real-world problems. Would definitely recommend it.

Overall great, maybe the most critical knowledge when starting out with data science. However, videos tend to be too short, could go more in-depth and provide better explanations and maybe more practical examples.

Good overview of the process overall. Lecture style, not a project based course. Some of the videos don't always completely convey the information as expected in the quizzes, but still overall good information.

The course is an expository one that has helped me understand some other vital areas of data science. The effort I have put into the course is not wasted at all. I am a changed man when it comes to data science.

I would have liked more explanation on what the code was performing, however I assume that also comes later. Otherwise, it was a good overview of the workflow leading to answer questions with machine learning.

Good course, very well explanation of the concept in the course. But the case study that was taken in the course was a little typical for a beginner and could be explained in detailed for better understanding.

It was a course with a good structured focus on each stage of the methodology process. I found very interesting the Lab in Jupyter notebook, providing a coherent application of the described methodology.

Great course by IBM. Would like instructors to have better communication skills. As the instructor in week 2 and 3 did not have that strong communication skills as compared to week 1 . Overall 8/10

Great course for understanding data science and data related methodologies. Some parts that included machine learning algorithms confused me a little bit, but a little google search made it clear.

The final assignment should be rated by the instructors, becuase of the comlexity of the methodology.

The best way to assimilate the methodology is by OJT. Try to assign students to companies.