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.
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 Mahvash N•
4. März 2019
Course was great but it had number of errors and typos, that per my experience and other attendees caused some confusion.
I am sharing so it could be improved as it is a dream come true for myself to gain this valuable knowledge as conveniently as possible.
von Denis M•
21. Sep. 2020
A very comfortably created course - no stress at all. However all that you can get is become familiar with the data analysis tools. May be that's the point.
von Ruchir V•
19. Dez. 2018
I think few more practical exercises or at least references of the same would help better understand the overall fundamentals.
von Rebecca V•
5. März 2019
Material covered is useful, but there are a lot of typos and mistakes in the lecture slides and labs.
von Rene P•
24. März 2019
There could be links to functiones libraries in the lab for a fast check of a function if needed.
von Ugur S O•
21. Dez. 2020
I think the quizzes can be in the format of programming required questions.
von Charles C•
5. Feb. 2019
Some mistakes/ typos in the exercises and slides, but great overall
von Yogish T G•
30. März 2019
An assignment should have been included
von Miguel E M•
15. Apr. 2020
There where some typos in the labs that could confuse most learners. I didn't feel like the course prepared people for real applications. The final project was quite hard because of this .
But it does give you a wide vision on hoy pandas work and some basic but apparently often used tools.
I see this course as a complement to a more detailed data analysis resource or perhaps as simply as an introductory view.
von Jaime V C S•
22. Feb. 2019
in this course there were some errors on the slides, and some quite complicated topics (almost every time related to statistics) was given in a very over-viewed way. Also, some of the python codes were not explained very well, with some terms of them seem to be kind of arbitrary for those who are beginners in the language. My impression is that this course should be longer and more detailed.
20. Nov. 2018
Overall I benefitted the course material as a beginner in python and data analysis. The questions were too trivial but maybe that helped me remain engaged with the course and complete it in a short time frame. There were some bugs, typos and minor quality issues that did not really effect my overall experience.
von Katarina P•
27. Juni 2019
Many typos in videos, stats explained on a very rudimentary way (and often inaccurate), Watson environment is awful as it takes ages for some simple regression plots to be made, it freezes and the interface is not user-friendly, yet we have to use it.
von Sadanand B•
7. Feb. 2019
Seems like there are quite a few errors in the labs that confuse the heck out of a student. The labs need to be fixed else the material becomes useless.
von Ravindra D•
11. Mai 2020
Course content does not give proper understanding of the different approaches. For the person who is not from mathematics background it is confusing.
von Bhuvaneswari V•
9. März 2019
The statistics background needed for the course need to be better explained. or at least reference to related learning materials to be given
von Russell K•
26. Apr. 2020
Too many errors in the lab examples can be rather confusing.
Also, the Seaborn code was not working in IBM Watson Studio
von Mariam H•
2. Mai 2020
Great course but some of the concepts are not explained very well. I got lost towards the end but overall i like it.
von Andre L•
10. März 2019
Lot of information, but offered in a very choppy manner. Was hard to follow, will need to review many many times
von Abdulaziz A•
11. Apr. 2020
the course content is excellent but some Technical issues occurred in doing the lab exercises
von Nguyen C N H•
29. Jan. 2020
The lesson need more explanations on Polynomial Regression, Pipeline, Ridge Regression.
von Fayja H•
19. Jan. 2021
too much content all at once
von Alex H•
4. Okt. 2019
Begins relatively clear. The practice labs were coherent and straightforward.
Around Week 4, things started to get convoluted. Small things, things that you don't notice at first.
Week 5 was where it really started to fall apart. You could tell whoever made this course lost interest or just did not have the capacity to teach the information effectively.
A great example of the lack of understanding or knowledge of how Coursera works is something you can view yourself.
Week 6 is the Final Project
Week 7 is one statement about your certificate.
Usually in most courses, the final project will be in end of the final week. That week having multiple modules that you have to complete leading up to the final. It was worrying for me as I thought the approach to this was on accident, but it seems likely that it was just due to ignorance.
Just as well, the Final Project was botched, the software and questions were depreciated and even written wrong by the creator. And when you would upload your pictures in the end to show you had worked out the problem, one of the upload buttons was missing in lieu of the letter "Y"....
Y indeed. Y was the ending of this course so terrible? A little more investment in the people you are teaching would go a long way. Very disappointed.
von Philip P•
9. Jan. 2021
Course lacks thorough rigor or genuine assessment.
Labs are training on copy/paste and using the Shift+Enter command in the Jupyter notebook.
Assessments are multiple choice. No assessments on ability to write scripts to undertake data analysis to seek solutions.
von Brandon S•
7. Jan. 2021
Again, the use of the IBM cloud is a useless buffering of site traffic for your own products and does not provide anything for the course. Little to no 'challenge' questions that push the student to go beyond the hand held procedure of the labs.
von Elvijs M•
18. Apr. 2020
The course makes you aware of some Data Analysis techniques, but you learn very little. The explanations are very superficial. And since nearly all the code is are already there, you are not forced to think about the concepts and methods.