Excellent high level introduction, would have like the assessment to be more challenging. The additional materials are just amazing for most of them. The notebooks to practice are also excellent.

Really enjoyed this course. Looking forward to the next part of the specialization. I thought the quality of the lectures was excellent and made the topic interesting and digestible

The course was slightly harder and longer than I had expected, but the statistics concepts were well explained. However, the coding was not as hands-on as I would have liked.

To pursue your dream career in Data Science statistics is a must. And this course is one of the fun and easy to understand statistical courses I have found on Coursera.

Great course with a great deal of meaningful content. Coursera failure on the Jupyter notebooks made wk 3 a bit more challenging, but overall its worth your while.

It is very complete course, you need to have a good background of Statistics, for the week for there is a lot of text but not enough practice or hand on projects!

This course is really a general overview. The focus seems to be laying a foundation which I hope we build on in a more technical way in upcoming stats courses.

I would have preferred lesser time in Week 4 on Sampling. Those lessons could have been moved to the next course as they don't strictly relate to Python.

It is a good course to start with python and statistics, the part of sampling distribution I think should improve, personally I don´t like large speeches

Pretty good introduction for using Python for statistics. Some of the lectures were a little dry, and the test material could have been more challenging.

Generally useful, not entirely sure what the peer review assignment was, and could have done with more python assignments to help with consolidation

The high-level theory was well explained. It would've been awesome if there would be more hands-on labs, and if the theory would go more in depth.

The assignments could be made more interactive,like assigning us problems on which would have to visualize the in jupyter by us to get the answer.

Python exercises can be more interactive and the examples for sampling could be explained by taking a small data set for getting a realistic idea

some of the materials in this course was not very clear but I think there will be more explanation in the upcoming courses in this specialization

Nice course, there are very good explanations, but I thought there was going to be some mathematical background, I think it is important too.

It is really good course for professional data scientist as mostly explains how to visualize data and graph and make an conclusion out of it.

Great class for beginners. Would have loved to learn the material in smaller python notebook snippets throughout. Instruction was excellent!

It's a good course to learn the statistics fundamentals with some python pratices with Pandas, Numpy, Matplotlib and Seaborn

Very high level introduction to pandas and visualization. It is a good resource for finding different pandas functions.

Great guidance and lesson videos! :) Easy to follow and I love the fact that I learnt something new here - Numpy!

The course is really good.The explanations are in detail but the assignments should be tougher.

Coursework is great and so are the teachers , concepts are taught in a easy to understand way.

More examples could have been used to explain concepts in the 4th week of the course. Thanks

Excellent course. Wish I had had more feedback, or someway to interact with an instructor.