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.
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.
por Brahmrysti A B•
A lot of mistakes here. Clearly rushed and not given the care and attention it needed. Some assignments REQUIRE you to go to the discussion board to figure out what the author intended and why your code isnt working.
por Ashish D•
Does the job of a good introduction.
Very limited and restrictive practice and assinments.
For a true learning experience one needs to do a lot of external research and work to show a measureable benifit.
por Steve H•
The content is good but there are a lot of mistakes and typos in the material. The peer review is extremely vulnerable to errors - only one person reviewed my assignment and gave me the wrong mark.
por D W•
Useful course but riddled with typos & inconsistent questions and answers. Needs a proper review by someone (probably not the people answering on the forums, who didn't seem especially clued up).
por Aaron C•
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•
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•
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 Michael M•
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•
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 Malcom L•
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•
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•
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•
This was a very challenging course. Some concepts were difficult to grasp and required additional research
por Mark F•
Frustrating when the peer reviewer doesn't actually understand Python and deducts marks for correct code.
por Hunter I•
Leaned some, but not a whole lot of real-world application, I recommend people take Python courses more
por Ashwin D•
Not enough hands on problems, including variety and volume. Expected more from an IBM program.
por Nathaniel S•
Don't spend your money on IBM Data Science Cert. Course labs are full of bugs and not working.
por Edwin S J•
Suddenly introduced complex codes and statistical functions. Videos were way too fast.
por Somak D•
moderators do not respond to questions raised in forum. leading to incomplete learning
por Jen E•
So many problems with the lessons and the final project.
por Rasmi D•
very high level... topics not covered in depth
por Q B M•
some commands are not fully explained.
por Hakki K•
I completed entire program and received the Professional Certificate. On the Coursera link of my certificate "3 weeks of study, 2-3 hours/week average per course" is written. This information is not correct at all, it takes approximately 3 times of that time on average! I informed Coursera about it but no correction was made. It should be corrected with "it takes approximately 19 hours study per course" or "Approx. 10 months to complete Suggested 4 hours/week for the Professional Certificate".
Here is the approximate duration for each course can be found one by one clicking the webpages of the courses in the professional certificate webpage: (*)
Course 1: approximately 9 hours to complete
Course 2: approximately 16 hours to complete
Course 3: approximately 9 hours to complete
Course 4: approximately 22 hours to complete
Course 5: approximately 14 hours to complete
Course 6: approximately 16 hours to complete
Course 7: approximately 16 hours to complete
Course 8: approximately 20 hours to complete
Course 9: approximately 47 hours to complete
This makes in total approximately 169 hours to complete the Professional Certificate. As there are 9 courses, each course takes approximately 19 hours (=169/9) to complete.
This course is too hard. This should be go on more slowly and explain more about meaning of each value described. The course is not for beginner and not for a person who doesn't have enough statistics background.