Informative but assignments could be more demanding and questions could be more about understanding the topic rather than simply recalling what is said in the videos

Quite nice, really lets one follow the methodology - good mixture of videos, labs, tests. Final assignment is great to develop a full concept for a specific problem.

The content needs to be updated and better align with the lab work. I was expecting more functional lab tool examples like RStudio, Zeppelin, and Jupyter Notebooks.

This course assumes that the taker has taken statistics and remembers a variety of terminology from that course. A refresher/terminology reference would be helpful.

I 've learn a lot from the good course and resource, but too many medical terminology make the video difficult to understand for a non-native English speak learner.

The assessment and the review method for this course need to be improved. I would suggest the passing rate would need at least three person review instead of one.

The lab often dose not work properly, and the vedio of lecture is a little bit confusing to understand, it should be well oganised. The course is helpful anyway.

Good lectures on the data science methodology including an understandable case study. The peer review procedure is a bit strange, but it worked out at the end.

The course introduces some basic ideas of the methodology practice of data science, which gives a general picture of the typical workflow as a data sciencetist

This course was indeed very helpful as it help me understand the need for data science methodology as i build up my career as a data scientist in data science.

Overall a solid course with a good overview of many data science concepts. Some of the exercises need to be updated to reflect the current IBM Cloud tooling.

I found this course a bit difficult to understand and had to view the videos multiple times to get clarity, probably due to lack of knowledge in statistics,

The content of the course is good, but how the videos are made produce me sleep, because the content is not expalined in a natural way, but it is only read.

Quite complete. I recommend it. It didn't get 5 stars, because too many concepts were just brushed over, but it is an excellent review of how to handle data

It would be even better if we are provided with the slides to review by ourselves before the final exam instead of needing to go through the videos again.

Very well designed! Some of the best courses! Good videos with illustrative images and quality sound. Would be nice to get some help with the lab exercises

Great content and clearly explained. I would just add more practical exercises to consolidate all the information provided. But I really enjoyed. Thank you

This gives a basic knowledge of Data Science and explains neatly in every steps. Appreciate your efforts in putting this course in neat and expressive way.

Some concepts are difficult to understand, probably because I am hearing them for the first time. Hopefully, next section of the courses will address this.

Great course with lot of good information.. but a bit over the head stuff for non technical people due to all the Python language included in the course.

Good overview of the data science methodology. However, to fully understand the topic, need to do more practices and hand-on on the real world project.

Teaches you how to think like a data scientist within the business context. Instructor could do a better job at explaining things the quiz tests you on.

great course but hard to understand using heart failure situation as example, that i think most of the people hard to imagine it because its not common

Very structured content which is easy to understand. A case sudty with less medical terminology would be easier to understand for non-native speakers.

The case study used in the course was too complex to understand, choosing different case study to explain the concept is more beneficial for students.