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 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 Angam P
•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 Narmeen i
•Sep 10, 2021
good
By Andrian R N
•Aug 15, 2021
Cool
By Jon R
•Jul 12, 2023
The whole course desperately needs a proof read. There are sections where sentences don't make any sense. The scripting and dialogue can be really clunky as well - phrases are repeated over and over . There are also parts where the exam section or final coursework has been updated with new content but the rest of the course has not been. For example one section you are asked to construct a pie chart the help links it gives you are for a bar chart. The videos are much more of an introduction and the real practice takes place in work sheets. I would like to see more videos explaining the processes in the worksheets as well as intro videos. Also Watson is pointless you make us sign up for a free account but nothing is really done with the programme, it is all jupiter or dash. Make everything in Watson or take the whole thing out.
However, there is a lot of information in the work sheets and it is a good starting point for Data Science. The writers are clearly passionate about Data Science and that comes through in the course. It gives you a very good start point for a career in Data Science.
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.
By Marius S
•Oct 14, 2020
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.
By Paulo R M d C
•Oct 17, 2022
I went through many problems to complete the Plotly Dash labs which puts up a small HTTP server on a non-standard PORT. I had to setup an entire environment in my personal computer to work around them. Also, due to the lengthy labs of this course, many of my colleagues reported problems running out of CUH in IBM Watson environemnt. I believe 50% more CUH would suffice for this course.
By Deleted A
•Jul 31, 2020
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!
By PRANJIT G
•Jun 2, 2020
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
By Shane W
•Nov 18, 2020
The capstone content needs to be thoroughly edited for clarity, especially in the instructions on what exactly the instructors are looking for in the final deliverables. Some of the peer-reviewers seem to be confused, and I'll admit I was a little confused myself reading through the instructions the first time.