SC
5. Mai 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.
RP
19. Apr. 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.
von Usman A
•29. Juli 2020
AN excellent course. Hands-on training on the cloud makes an individual really involved. So far the best online course I have ever taken, and I have learned Python programming a lot from this course.
von Oana M
•22. Mai 2019
Thank you so much! - Oana
von Aditya J
•18. Mai 2019
None
von William B L
•20. März 2019
The techniques, methodologies, and tools presented here are essential parts of the data analysts tool box. The coverage was, in general, well done. I am glad I took this class, and look forward to the next.
That said, there were problems:
1) The meta parameter, Alfa (or is is Alpha) is never explained, except that it helps. To be useful, the student needs to know a bit more. Also, the spelling should be consistent between the training texts and the lab.
2) The lab needs maintenance to keep up with changes in the Python packages. I received warnings about using deprecated functions and values.
3) The text needs grammar/spelling checking, for example, the end of the course exam is labeled "Quizz"
von Karen B
•25. Mai 2019
Does an excellent job in providing the Python commands needed to do data analysis, along with some descriptions of what the steps actually involve. Has quite a few typos and minor issues -- looks a little sloppy.
von Matthew A
•13. Apr. 2021
During the 4th week of the course, lots of important information and explanations are over summarized and in some cases skipped over. Learning tools outside of what is provided in the course or a decent understanding statistics is required in order to be successful in this course.
von Thamarak
•22. Aug. 2020
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.
von Sobhan A
•6. Mai 2020
Low quality.
Do not recommend this course at all.
Boring teaching method.
Full of errors.
No IT support for problems.
von Titans P
•17. Aug. 2020
worst ever
the greatest thing i have learned here is patience and searching online
von Shashank S C
•6. Mai 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.
von Hakki K
•9. Juli 2020
Hi,
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.
(*): https://www.coursera.org/professional-certificates/ibm-data-science?utm_source=gg&utm_medium=sem&campaignid=1876641588&utm_content=10-IBM-Data-Science-US&adgroupid=70740725700&device=c&keyword=ibm%20data%20science%20professional%20certificate%20coursera&matchtype=b&network=g&devicemodel=&adpostion=&creativeid=347453133242&hide_mobile_promo&gclid=Cj0KCQjw0Mb3BRCaARIsAPSNGpWPrZDik6-Ne30To7vg20jGReHOKi4AbvstRfSbFxqA-6ZMrPn1gDAaAiMGEALw_wcB
von Vincent L
•17. Sep. 2018
Ton of errors, both minor and major, in the videos and the quizzes. For example, saying the a difference between two variables is significant because p > 0.05. I report them all and I've stopped counting.
Not professional at all.
von Anastasiya B
•22. Sep. 2019
Low technical quality of the course with lots of typos, errors and comletely mess in final assignment.
Low quality of material, bad structure, and you can get your certificate just by clicking shift+ enter
von John K
•7. Juli 2019
Poorly put together course - especially the labs. Frequent misspellings, incorrect links and confusing instructions. The technical problems are a greater challenge than the course material.
von Uygar H
•14. März 2019
I have really learned many things in this course which are meaningful and helpful in real life. It is not just lines and numbers , it is exciting how you can apply these methods to find solutions in your real life problems. Combined with strong Python skills , you will enjoy more..Thank you
von Daniel T
•9. Apr. 2019
This was a great review of stuff math I learned in high school and college. Of course it's all easy now because it's baked into Python. We used to do it by hand and with slide rules back in the early 1970s
von Firat E
•4. Juni 2019
It is really a good course, simple to understand and very complete. Thank you !
von Ashirwad S
•21. Mai 2019
Recommended course to understand the how to do data analysis using python
von Jim C
•20. Mai 2019
Well organized, good explanations, and very good labs.
von Aditya M
•21. Mai 2019
Overall apt content for beginners and naive learners.
von Vineet M N D
•20. Mai 2019
Great experience
von Shernice J
•30. März 2019
Instead of having a lab after each topic, this course one lab per week encompassing all of the topics. Some might find that better than having smaller labs but to me the information was assimilated better when i did a lab right after the topic. That being said, you can open the lab first and follow along with/after each video. You just need to be mindful of what works best for you. Taking time to understand the code is a must and some more documentation would be helpful. I wasn't a beginner with Python and it took some time and work out what was happening at times.
von Akiru J C
•12. Apr. 2022
I really enjoyed this course. Few things to suggest:
- Go over Statistics in more detail. Had I not studied Statistics in university, I may have found this topic confusing.
- Felt like I could have learned more if the labs were not filled-out halfway
- Too many multiple choice questions in the quiz and final. These should be more interactive with lines of code we would type insetad of clicking a bullet.
- The math covered in this course was very high level. I.e., Chi-square and linear regression require more hands-on practive in order to grasp.
von Itshak C
•13. Apr. 2021
Loved the labs. Hated the Videos. The amount of information that is thrown at you in a 1 min video is very unsettling as it makes you think you haven't understood a word of what they say and then the labs immediately clear everything up and then you feel like the smartest person alive. It's an uphill battle at times but the end result is pretty helpful regardless of the reason you're perusing the course.
von Devansh N
•5. Mai 2020
Was a bit tough to keep up at the week 4 and week 5 but overall a very good course