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!

Concepts are very well explained, using interesting data sets and examples. Only area for improvement would be additional videos to accompany more of the labs.

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.

Good course if you have learned the foundations of statistics already and want to review it while learning how to use Python for your statistical analysis.

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.

Content is great. Would be a great learning experience for those who have some idea of stats and python. Definitely, not for entry-level python and stats.

Generally, it is great! It would be better if examples were provided to illustrate the concepts of confidence intervals and hypothesis testing in week 4.

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.

A lot of thoery. It was a challenge to grasp all of the statistical terms. Not really much of a python or practicum course. I guess that comes later.

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

great course - the labs were very helpful. Only suggestion, more practical / relatable examples when explaining certain areas, especially Inference

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.

Es un buen curso pero sería bueno que los videos fueran más cortos, hay unos que duran más de 20 minutos y a veces cuesta seguir concentrado

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!

It will help if you have some basic knowledge of Quantitative, so could only focus on the Python learning part.

The interactive lab is awesome. But data sampling and inference videos are very dry for beginner.