LD
Oct 23, 2019
Its was great experience in completing the project using all skills that we learned in the course, thanks to coursera and IBM for giving me an opportunity to update my selft and also to test my skills
CS
Jun 15, 2023
It's a great course to get a comprehensive background on Data Science (including ML) and lays the foundation for more advanced courses. It touches on all the areas that are required for data science.
By Napattarapon P
•Sep 11, 2019
Useful course for starter
By Muhamad H R
•Oct 10, 2023
Good for beginner
By Shahid R
•Jul 13, 2023
Too Much PPTs....
By Hardik R S
•Feb 24, 2019
Little bit hard
By Robert B
•Apr 20, 2022
A great course
By adetunji p
•Feb 23, 2022
it was awsomee
By Deepak N
•Aug 12, 2019
Good exposure.
By YIFAN H
•Nov 10, 2019
真的难,对我这个初学者来说
By Praveen A
•Sep 15, 2019
great course
By Ernesto C M P
•Jan 16, 2022
good course
By zoubair a
•Jun 2, 2020
good course
By Magnus B
•Jun 10, 2019
Fun course!
By Mustafa M M E
•May 28, 2023
very good
By Abdulla M
•Nov 6, 2020
very good
By Amanullah K
•Oct 31, 2020
Excellent
By Satishkumar M
•Jan 9, 2020
Average
By Prayag P
•Jul 30, 2020
Good !
By Romero R J Y
•May 25, 2024
nice
By Narmeen i
•Sep 10, 2021
good
By Andrian R N
•Aug 15, 2021
Cool
By Khalid h
•Oct 21, 2024
ok
By Ben G
•Aug 6, 2024
Let's start with the good: The activities. These are great reviews of what we have learned in other IBM courses, with some new stuff thrown in. I learned a lot. So why only 3 stars? The course has several basic problems that caused me to waste a LOT of time. 1) Unintelligible instructions/materials. There are so many grammar spelling errors, things copy/pasted into the wrong place, etc that it can be quite hard to follow. This is common in IBM courses but in this one I really felt it. 2) Technical issues. Labs crashed several times for me. In the Dash lab, it was particularly annoying, as the work cannot be saved in the lab itself, and so I lost all progress every time there was a crash. To make things worse, the staff moved several of my labs to different locations, forcing me to redo several hours of work (hopefully this is just a once-off problem though). 3) Some strange activities. For example, how does finding everything that starts with 'CCA' help us to answer the research question? Yes, it might be good practice in it's own right, but why can't we get practice by working towards the stated goal instead of by doing random time-filler activities?
By Tania D
•Aug 21, 2020
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.
By Thøger E R
•Sep 14, 2022
The curriculum and project work was fine. Notebooks to complete were OK, although not flawless. The final presentation format was... bad. A written report in the form of a 50 slide PowerPoint presentation is *not* a good habit to be teaching future data science professionals. Plus the instructions regarding what was expected were either ambiguous, confusing, or absent. The curriculum is great and I learned something. The testing procedure was extremely tedious and poorly thought out and in dire need of a major overhaul.
By John F
•Sep 14, 2022
Very prescriptive and guided. Everything I have come to expect from Coursera. Little room for critical thought or original content. Designed for begineers. I am surprised this is an IBM course beyond building the user base for its tools. The marking Rubik's are too prescribed to provide accurate marks which matters little given the way in which they are applied. The final powerpoint assignment should be replaced with a report and a ten slide deck.