Was very good although I was expecting something more advanced

Learn new concept in this course .Thanks to IBM and coursera.

Very good course with helpfull assignments.

Very Difficult to finish..big last project

The detail of the course is quite limited.

Good introductory course on Data Science.

please update the practice notebooks

very long to get anything reviewed.

Kind of difficult for beginners

Interesting projects included!

Useful course for starter

Little bit hard

Good exposure.

真的难，对我这个初学者来说

great course

good course

Fun course!

Average

Good !

As much as I would like to recommend this course, I was really disappointed by the poor quality of the videos in this lecture. They contained a lot of spelling mistakes and were not aligned with what you find in the corresponding notebooks which made it very cumbersome to take notes while watching the lectures. Also the capstone project, while being interesting and challenging, was not properly motivated by the course itself.

I think the extend was good and concept fine but it needs a lot of fine-tuning to be an outstanding course which wants you to continue an do the next one immediately after.

The assignments were interesting especially when we had to think of our own problems to solve. It would've been really helpful if the course was regularly updated, specifically when it comes to the first assignment where a lot of students experienced challenges with their machines and the course was designed with old operating machines in mind. the discussion forums would help a lot if instructors actually answered the questions and not directed students to links that were of no assistance at all. The course material could really do with an upgrade.

I think I was a tougher critic of my own project than anyone else was going to be; the rubric for peer-grading was almost entirely about presentation with little emphasis on the data analysis itself. The requirement to use Foursquare's API was a limitation on the possible topics for the project, and Foursquare's documentation of endpoints fails to disclose that some fields such as Rating are the result of proprietary, unusual calculations that are unlikely to correlate strongly with any simple data.

The github guide was very helpful and informative. I wished there would have been more explanations how to interprete the results of evaluated models and about machine models in general, when to use which model for example. Also some details were missing like how to balance imbalanced data, should the data be balanced and then visualized or vice versa? Fitting a model is easily done, but it's the details that make the difference.

The course gives the learners a perfect platform to practice the concepts learnt throughout the Data Science specialization. Final assignment is unique and interesting and the course makes sure you practice enough before taking it up. A good experience, but issues with Foursquare now and then makes it a little hectic to get done with the course.

A nice course though. Liked it!

The journey was very informative but at the end of the course and submitting all of my assignments before the deadline , i got my course certificate with no instructor signature . A very disappointing fact as I worked very hard to complete the specialization within my 7 day free trial which is till 8 pm today I.S.T

Never expected such kind of irresponsibility