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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
1,593 个评分
315 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 22, 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 03, 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 :)

筛选依据:

201 - Understanding and Visualizing Data with Python 的 225 个评论(共 313 个)

创建者 GOWRISWARI S

May 29, 2020

good course

创建者 Amarildo Q

May 23, 2020

Excelente!

创建者 Kondapalli S V

Feb 20, 2020

wonderfull

创建者 Andria

Nov 02, 2019

Very nice.

创建者 Beatriz J F

Oct 28, 2019

Excellent!

创建者 madhurima c

Aug 28, 2020

very good

创建者 Yurgenis R

Jun 16, 2020

very good

创建者 Satrio T S

Oct 03, 2019

Excellent

创建者 Nedal

May 25, 2020

v

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y

g

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创建者 Gabriel A A C

Feb 05, 2020

Excelent

创建者 Israel F

Jun 25, 2020

Amazing

创建者 周晓

Apr 07, 2020

Thanks!

创建者 KAYDAN P R

Jun 30, 2020

awssem

创建者 Frank S Y R

Jan 17, 2019

Nice!

创建者 chang l

Aug 31, 2020

good

创建者 GUNDA S K G

Mar 04, 2020

good

创建者 ATHIPATLA S N

Feb 25, 2020

nice

创建者 BODIREDDI S A

Feb 23, 2020

nice

创建者 PUPPALA B A

Feb 21, 2020

GOOD

创建者 PEDASINGU T K

Feb 24, 2020

gud

创建者 Jerrold

Oct 07, 2020

There are two main fields of study in this course which forms the foundation for the specialization: statistical theory, and programming with python data analysis packages. I learned so much about statistics and visualization that would have taken months to learn in university, I gained a lot of experience and knowledge from this course. I have a decent background in Jupyter notebook from university yet I still learned many new things and got an excellent chance to practice programming in the python packages. The course offered excellent optional practices and gave us several extremely insightful and educational analysis reports done in JN that were related to the module of the week for us to download.

I recommend you have a datacamp subscription to have access to some extra notes regarding programming in the packages particularly Pandas to get the most out of this course by attempting all the optional programming practices.

创建者 Luis D R T

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

创建者 Matteo L

Apr 04, 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.

创建者 Iver B

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.

创建者 steven h

Apr 29, 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.