5 de mai de 2020
I started this course without any knowledge on Data Analysis with Python, and by the end of the course I was able to understand the basics of Data Analysis, usage of different libraries and functions.
19 de abr de 2019
perfect for beginner level. all the concepts with code and parameter wise have been explained excellently. overall best course in making anyone eager to learn from basics to handle advances with ease.
por Aaron C•
15 de jul de 2020
The videos really are not very engaging (relative to any other course that I have completed here on Coursera). The concepts are not explained very thoroughly. Thanks anyway guys.
por Berkay T•
27 de set de 2019
Too much content, so less practice. This course doesn't teach anything that you can make use of in the long term. It only gives an idea on what you have to work on in the future.
por Sheen D•
11 de ago de 2019
This is by far the worst course in the specialization. So many mistakes in the lab session, including unclear instruction, or syntax is not uniform across each module, and etc.
por Cláudia S B•
16 de jul de 2021
The artificial voice used over the video is truly awful for learning. I enjoyed the jupyter notebooks where I actually could learn what was bla-bla-blaed in the videos
por Michael M•
20 de dez de 2019
The IBM Developer Skills Network (at labs.cognitiveclass.ai) is very slow and doesn't work most of the time.
It doesn't allow to finish the course properly.
por Ismael S•
2 de jun de 2019
Content is thrown to the student with too much information and videos of only 3-4 minutes. Too much to absorb and too little to practice properly
por David K•
28 de abr de 2020
Too many errors. Please renew the course asap for the future learners. These errers are distracting and make the learning experience less fun.
por Archana B•
28 de abr de 2021
Model Development and Model Evaluation & Refinement Concepts are not explained properly neither in Videos nor in Lab!!Really disappointing :(
por Tarun S•
10 de mar de 2021
Concepts of the algorithms are unclear. In the notebooks as well, it is not in a flow. Very confusingg for a beginner to learn from this.
por Malcom L•
11 de jan de 2019
more hands on, project based/game based learning. Mindlessly watching videos and regurgitating code in the labs can not be the only way.
por Santanu B•
16 de abr de 2019
Not a great course. Sometimes it is too fast and the explanations are very short. More hands on exercises would have been more helpful.
por Rajesh W•
17 de out de 2018
There are plenty of mistakes in the videos and in the lab session as well. Hope you guys can clear out those.
por Wayne W M•
2 de out de 2019
This was a very challenging course. Some concepts were difficult to grasp and required additional research
por Mark F•
8 de abr de 2020
Frustrating when the peer reviewer doesn't actually understand Python and deducts marks for correct code.
por Hunter I•
17 de abr de 2020
Leaned some, but not a whole lot of real-world application, I recommend people take Python courses more
por Ashwin D•
29 de abr de 2020
Not enough hands on problems, including variety and volume. Expected more from an IBM program.
por Nathaniel S•
29 de mar de 2020
Don't spend your money on IBM Data Science Cert. Course labs are full of bugs and not working.
por Katherine L•
5 de jun de 2022
coursework was easy but that damn final assignment was absolute hell for no reason whatsoever
por Edwin S J•
25 de mai de 2019
Suddenly introduced complex codes and statistical functions. Videos were way too fast.
por Somak D•
30 de out de 2018
moderators do not respond to questions raised in forum. leading to incomplete learning
por Syed I B S A•
10 de jun de 2021
Worst course in the IBM Data Analyst Professional Certificate. Very badly explained.
por Sahar A•
3 de out de 2021
it was too fast and I didn't understand a lot of things
por Jen E•
31 de jul de 2019
So many problems with the lessons and the final project.
por Rasmi D•
18 de jun de 2019
very high level... topics not covered in depth
por Ahmed E•
8 de ago de 2020
some commands are not fully explained.