Really great! Tons of information complemented with exercises. To deal with the amount of material, I suggest following the labs very closely and doing a bit of research in the Python documentation avalaible online. I have to say you really hit the core of the matter in this course!

I liked so much that I solve more short test because it helps me to remember information easily and guess it allowed me to perform better. It's the first time I get 100% three times in final tests of each week.

I have been looking for a very non-complicated course on data analysis and I hit the Jackport with this course! Very simplified and explanatory. You should definitely take the course

Great course. I had fun having a kick start in the field of data in machine learning. I understood the concepts related to how to improve the model.

Thank you

Great Course. Amazing Work By the team. Concepts explained clearly, followed by the week end quiz to revise. The Labs Do a great work in helping out

Covers a lot of ground but the Python Labs are great at bringing everything together.

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

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.

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

Quizzes are too easy. No evaluation of actual code.

An assignment should have been included

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.

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

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

Thoroughly appreciate the effort to put this course together, however there are several problems (I think this is the worst quality course I've seen on Coursera so far .. or maybe all other ones have just been great!) -- a) the instructional videos contain many errors in both code syntax, and, worse, in logic; b) questions on Forums take a long time to be answered, and staff member who responds to most of them appears to be a bot/only provides vague general info; c) course material has ups and downs, for example Inferential Statistics are blazed through within 15-20 minutes, and there is very little discussion of, say, how to identify the distribution of your data, how to decide on parametric/non-parametric tests and so on.

i was following nicely until week 4 but halfway there it got really difficult. To a point in week 5 when all i could do was copying code and adjusting it. I have no idea what i was doing, i totally lost the bigger picture. I'm sure i could never replicate any of it outside the course or explain what i learned.

Too many mistakes in the lectures and the main lab. Confusing for new learners when the math is wrong or the python syntax is wrong. Anyone who rates this above 3 stars you are simply not paying attention to the myriad of mistakes.