A very complete course of Data Analysis.

Tough but useful.

The course content is definitely interesting, but the approach is superficial. You will get a broad overview of the keyword to search for, and what is available in popular Python packages. However, the quizzes are way, way too easy. The course needs a final "open" assignment, where you have to use the tools without being guided along the way. This is the only way to truly learn.

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.

Thank you.

Mahvash Nejad

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.

I think few more practical exercises or at least references of the same would help better understand the overall fundamentals.

Material covered is useful, but there are a lot of typos and mistakes in the lecture slides and labs.

There could be links to functiones libraries in the lab for a fast check of a function if needed.

I think the quizzes can be in the format of programming required questions.

Some mistakes/ typos in the exercises and slides, but great overall

An assignment should have been included

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.

Hello,

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.

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.

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.

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.

Course content does not give proper understanding of the different approaches. For the person who is not from mathematics background it is confusing.

The statistics background needed for the course need to be better explained. or at least reference to related learning materials to be given

Too many errors in the lab examples can be rather confusing.

Also, the Seaborn code was not working in IBM Watson Studio

Great course but some of the concepts are not explained very well. I got lost towards the end but overall i like it.

Lot of information, but offered in a very choppy manner. Was hard to follow, will need to review many many times

the course content is excellent but some Technical issues occurred in doing the lab exercises

The lesson need more explanations on Polynomial Regression, Pipeline, Ridge Regression.

too much content all at once

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.