# 学生对 密歇根大学 提供的 Understanding and Visualizing Data with Python 的评价和反馈

4.7
1,758 个评分
348 条评论

## 课程概述

In this course, learners will be introduced to the field of statistics, including where data come from, study design, data management, and exploring and visualizing data. Learners will identify different types of data, and learn how to visualize, analyze, and interpret summaries for both univariate and multivariate data. Learners will also be introduced to the differences between probability and non-probability sampling from larger populations, the idea of how sample estimates vary, and how inferences can be made about larger populations based on probability sampling. At the end of each week, learners will apply the statistical concepts they’ve learned using Python within the course environment. During these lab-based sessions, learners will discover the different uses of Python as a tool, including the Numpy, Pandas, Statsmodels, Matplotlib, and Seaborn libraries. Tutorial videos are provided to walk learners through the creation of visualizations and data management, all within Python. This course utilizes the Jupyter Notebook environment within Coursera....

## 热门审阅

AT
May 21, 2020

Excellent course materials, especially the videos, with content that is thoughtfully composed and carefully edited. Very good python training, great instructors, and overall great learning experience.

VV
Aug 2, 2020

Great course to learn the basics! The supplementary material in Jupyter notebooks is extremely valuable. Really appreciate the PhD students who took the time to explain even the simplest of codes :)

## 251 - Understanding and Visualizing Data with Python 的 275 个评论（共 346 个）

Oct 26, 2019

I loved several things, first that gives you an overview, useful, clear and fun of several basic statistical concepts such as measures of central tendency, different forms of graphic representation, and one of the most important at least for me (already that neither in school nor I would have ever thought about) the types of sampling that exist, because in school there is usually something called simple random sampling and we develop statistical techniques for it, almost completely ignoring the other types of sampling that are really common in real life and that when we face them we don't panic, I know that this is an easy level and I appreciate that in some way, but I would have expected a more difficult course that would have made the concepts really stay in me because I would be thinking about them continuously and how to apply them to the tasks that are presented week by week

Apr 4, 2020

I think the content here is great and gives you a good overview for understanding and visualizing data without getting into the mathematics. Week 4 is absolutely great in terms of how the information is conveyed by Mr. West who is an excellent teacher in my opinion. I do think, however, that the quizzes and notebook assignments could be a little bit more challenging and I would have loved to have answers to the "more practice" notebooks. I think it would have been great for those notebooks to have been part of the assignments, adding to the difficulty of the course.

Jan 13, 2019

Good introduction to basic statistical methods with an emphasis on working with surveys, and a good introduction to basic statistical techniques with core Python, numpy, matplotlib, seaborn and statsmodels. Instructors and presentations are excellent, very clear. I would give it five stars if it were more interactive, i.e. with more in-video quizzes, and practice quizzes between videos. Also, I wish I had take this course before I did the Applied Data Science with Python specialization, also on Coursera, but, alas, it wasn't available then.

Apr 28, 2020

The course could be improved with more quizzes to apply what lectures cover. A lot of useful information is presented, but there was not enough opportunity for us to apply it. Also, the course should present more examples of statistical concepts. At times, it felt as if I was just listening to an audiobook. Statistics can be better understood by applying concepts and visualizing. Week 4, in particular, felt very rushed. There was a lot of "this will be addressed later", which diminished the relevance.

Jun 28, 2020

It is a fairly good course for statistics introduction. However, the explanation on how to apply with python libraries is not well-organized. Learners must have a well understanding of numpy, pandas, Matplotlib and Seaborn on their own in advance, because the TAs just read through the code without explaining why in details.

The statistics concepts lecturer is very good, but the TA didn't describe python libraries or modules selection and application concept.

Aug 9, 2020

Best course for Statistic to understand from Datascience POV. If you're a software developer or from computer science, then this course is good to go into to understand the statistics for DataScience.

Deducting one start for :- 1. Week 4 was too much lectures and less assignment. Felt rushed.

2. The pythonic technical tutorial was not explained much technically and hence i had to spent a lot of time on different course to learn them.

Sep 28, 2020

I am so happy to learn about data visualization through python. This course gives you a good amount of insight on how to visualize data through python and helps you understand the graphs and statistics behind it. I am very thankful to the team who have made up this course as it has been very helpful to me and other students like me to be much more confident with our knowledge in Python and Statistics.

Dec 6, 2020

The course is pretty technical and there are some gaps in the information that is presented (that will probably be addressed in later courses in the specialization), but it certainly whets one's appetite to learn more about statistics. I also appreciated the opportunities provided to apply the code that was learned and to see some of the theories in action. A worthwhile take overall.

May 23, 2020

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

Aug 15, 2020

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.

Mar 30, 2019

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!

May 31, 2020

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.

Sep 29, 2019

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.

Jul 2, 2020

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.

Aug 17, 2020

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).

Aug 1, 2020

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.

Sep 8, 2019

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.

Apr 12, 2020

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.

Dec 17, 2019

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).

Nov 23, 2020

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).

Apr 10, 2020

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

May 23, 2020

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.

Apr 4, 2020

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!

Sep 1, 2019

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.

Sep 4, 2020

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.