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 course is well structured but the case studies were not well elaborated, felt like I was struggling to understand. Also, Data science methodology should be taught after a course in Python.

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.

I like the way they provide sample with food preparation on each of the stage of data science methodology. Need to give more sample for the study case to give more insight and understanding.

A bit more complex than what I would have hoped, but the material is still digestible. I think this course could be improve if the lecturer slow down a bit and spend more time on each topic

It is a good course, teaching about the general process and life cycle of a data science project. Excellent tips are provided. Overall, I feel it was lacking a bit in content for 3 weeks.

It was good to be able to learn the cycle of data science. The learning materials were helpful. This lecture is recommended for those who want to learn the whole flow of data science.

More real examples will be very useful to get more understanding of the methodolgy, but the course was so good that now i know how data scientist think and handle the problems they face

It is self paced giving a good grounding on the subject provided you are an inquisitive & enthusiastic learner. It does not provide a deep dive but gives a road map for self learning.

The course introduces us to the data science methodology. However, if the examples used for explaining the concepts have to be changed for better understanding of the concepts.

Although we can gather a lot of knowledge from this course, many of the lessons didn't have the transcript and many others only offered Turkish transcripts instead of English.

It is a very good course for the beginners as I got all the basic - basic information about the process in data science and machine learning which would be used in the future.

This course finally gets into the nuts and bolts of data science. The very specific examples with Python code shown make this the right introduction to the rest of the course.

It is great introduction for someone who has no idea about data science. The methodology is clearly explained. However, the example discussed is a little difficult to follow.

I'm very thankful to this course because it neatly explain the step followed in the data science project.Also the quizzes help me to avoid misunderstanding of the concepts.

A good introduction, but as you learn you also need to further explore and read more. I would have loved to see a list of readings providing more examples and case studies.

The methodology seems a bit arbitrarily devised to give 10 parts though the 10 are sometimes not meaningfully distinct.

Still a well structured approach to breaking it down.

This course compresses much material about approaches and modelling, and describes only a few of the concepts in any real detail. Though, what is presented is done well.

Case study isn't suitable for all categories of student ... i didn't understand the case study because i have no medical background plus there was hard expressions for me

It was exceptionally good, with case-study driven content and accurate explanation of the different terms and condition before moving to a data science specific problem.

This course is great except that it has problem of labs which are not working correctly too many times. It is really challenging because too often it seems it is offline

Interesting course, although some very "thick" notions. It looses 1 star because of the final assignment, which is very vague and open to all kind of interpretations.

Very informative. The case study discussed was not very interesting to me, but everything was very easy to follow. The interactive labs helped with hands-on learning.