Overall, this course is good to expand my horizon in CS and Statistics area. But some content may be a little bit vague, like those in the labs. though accompanying with explanatory videos, a lot of points regarding the lines of code are still not very intelligible. This is the only one thing that I'm not quite content with in this course, but other parts are really beneficial.

This is a tactfully curated course for getting your legs wet in statistics with python, I personally was not completely comfortable with the statistical explanation and had to refer to multiple sources but hey a splendid job in other crucial things such as working around a code!! 10/10 recommend!! I wish to connect with the tutors via Linkedin

Having no prior knowledge of stastics and it's terminology, i felt more number of practice question should have been given to understand the concepts in a better manner. The assignments with python could have more number of questions and bit more complex as well. One should refer extra material to understand the concepts well.

At times I felt as though the content could have been delivered on a longer timeline. Some of the Python was very dense if you aren't already skilled with Numpy and Pandas. Coming from Python Basics, they took more time to explain programming concepts. Overall I enjoyed the content and the instructors. Thank you!

Has a lot of theory, so any non statistics student can go along with it. Statistical theories are explained very well with a lot of references and cool website, articles and link. If anyone wants to get the most out of this course he/she has to spend time learning to code by himself.

It was ok. To be honest, I expected somehow more from this course, but I cant say that something was bad. I would like to have more practice in python, because the exercises are made more for watching or just repeating, not really for practising and applying new skills.

This is a good course for people who do not have a strong background in programming. The videos and lectures are extremely well planned, . However, there is not much practice you can do, the assignments are super easy and they do not cover much of what is taught.

A fun and easy course for someone who wants to start knowing what it is about to analyse and visualize data, but it did not provide enough in detail, to the extent I would like to learn, about the visualization packages of python (i.e. matlibplot and seaborn).

Great starting point for getting into statistics. Covers some good fundamental areas which other courses may skip over. Designed well for the online delivery. Assessment sections were a little varied e.g. some were great, others felt far too easy or limited.

Video lectures and suplemental material were put together very well. I enjoued the class and learned a few new things in the process. If I had to make a sugestion it would be to include more practice opportunites however there were enough to be effective.

So far the best statistics course I have taken on Coursera! High quality lectures and wonderful lecturers. The only thing I didn't like is the order arrangement of the homework. It started too hard, but once you overcome that, the rest is pretty doable.

the overall structure of the course is good and right to the point but I gave only four stars as the statistical concepts are confusing without understanding the jargon, in my personal opinion, I feel a video explaining the jargon would be very helpful.

The teachers are all enthusiastic and very professional. Videos are great! But I cannot give a five-star since the assignments do not seem very effective, and there are some old codes that are only applicable to python 2 (rather than python 3).

It is a great course to learn statistics. The lectures and teachers are excellent. I think they should change the way they teach Python programming and should use other tools for students to practice, like the tool to learn R (R labs).

The classes and content are great. It has fixation exercises, which helps a lot. I would suggest as an improvement to put more examples in unit 4, because there were times when the concept was not very clear, especially complex samples

Great Course. Week 4 material is a bit theory heavy. Course Era Notebook has some inconsistent behaviour. I used colab.google.com. Overall , Great Experience!

I need the certicate for completion of the first out three courses!

This course is a good begin for statistic learning, especially sampling and visualization ideas. The content is quite long, there are so many lectures as well as reading material.

It is better if the summary reading is provided.

Very thorough introductory course to data understanding with a clear presentation of probability and non-probability sampling, probability of selection, and sampling distribution. Wish I had this course when I was in college!

Can have more adavanced excercisesm and scope of data visualizations can be improved(since those are not that advanced) but for a begineer this is a great course, the links in the courses are great to extend the knowledge.

Very helpful course for newcomer in data science studies. Great in clearing fundamentals for descriptive statistics, use of python to get these insights,plotting. Overall provide good learning curve.

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.

Good content but I dont like some assigment/assessment, especially the one asking to write a memorandum, which is totally not related to "Understanding and Visualizing Data with Python"

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

Great course to start with Statistics. Methods of data collection and their implications are explained in good detail. Good start with coding in Python visualizing data as well.

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.