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学生对 密歇根大学 提供的 Applied Plotting, Charting & Data Representation in Python 的评价和反馈

4.5
3,777 个评分
605 条评论

课程概述

This course will introduce the learner to information visualization basics, with a focus on reporting and charting using the matplotlib library. The course will start with a design and information literacy perspective, touching on what makes a good and bad visualization, and what statistical measures translate into in terms of visualizations. The second week will focus on the technology used to make visualizations in python, matplotlib, and introduce users to best practices when creating basic charts and how to realize design decisions in the framework. The third week will be a tutorial of functionality available in matplotlib, and demonstrate a variety of basic statistical charts helping learners to identify when a particular method is good for a particular problem. The course will end with a discussion of other forms of structuring and visualizing data. This course should be taken after Introduction to Data Science in Python and before the remainder of the Applied Data Science with Python courses: Applied Machine Learning in Python, Applied Text Mining in Python, and Applied Social Network Analysis in Python....

热门审阅

SB

Nov 03, 2017

Loved the course! This course teaches you details about matplotlib and enables you to produce beautiful and accurate graphs.. Assignments are challanging, and helps to build a solid foundation.

ML

Jun 28, 2017

Good course to learned matplotlib and other Graphs libraries, but the course goes further than Python and also encourages the studies to create more meaningful and beautiful Graphic views.

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76 - Applied Plotting, Charting & Data Representation in Python 的 100 个评论(共 592 个)

创建者 Juan R C C

Aug 24, 2017

Great course!! It requires to dedicate several hours per week but it's a very good investment. Teachers, contents are very good as well than materials. Assignments are very well aligned with the course objectives and they are really profitable in terms of learning on job.

创建者 Nahim O

May 06, 2019

It's awesome, the course is incredible, I've learnt a lot of thing about python, I'd like to know more about similar python course like this. this specialization its vast to improve your knowledge in programming with python. I'm glad to took this course. Simply awesome.

创建者 Carlos V

Mar 03, 2019

The concepts and theory explained in the course are perfect for building a solid foundation for data representation, highly recommended for anyone looking to improve in their data-science skills and understanding of the science behind extracting insights from data.

创建者 谢仑辰

Feb 27, 2018

I highly recommend this class Though we cannot remember all the things the instructor delivered here, it really provided me a way to se how significant the toolkit can achieve. And the rest relied on ourselves such as referencing documentation.Great class.

创建者 Shadi A

Mar 14, 2019

Dr.Christopher Brooks is the best instructor ever. He starts with simple step by step into Matplotlib instructions along with valuable reading materials as well as challenging assignments where each assignment add more and more the learning of the course.

创建者 carol a

Oct 03, 2018

Very well taught. The only thing I currently work with Tableau and it has more functionality( drill down to data) which helps the user understand the data that they are look at. So it makes me wonder do we really need to learn mapplotlib in today world.

创建者 Marcel A G

Jun 09, 2019

I have really enjoyed this course. It requires a bit of effort researching things that are not available on the course but I think that this is done on purpose and it really helped me to get a better understanding on how things work. Thank you so much

创建者 Jeffrey D R

Jul 24, 2018

This course is not as challenging as Course 1, unless you find visualization difficult. As with Course 1, the instruction is good but brief, and you'll need to dig through various resources to find the details you'll need to complete the assignments.

创建者 Aamir M K

Oct 14, 2019

A wonderful course. As a practitioner, I wasn't expecting much newer things but I gained knowledge at both the fronts; aesthetics and technicality of plotting graphs. I learned so many newer things. Thank you Professor for such a wonderful resource.

创建者 Dongliang Z

Dec 05, 2017

This is a nice beginning to learn and use python. The assignments are very good to practice what I learned. I want to thank Dr.Brooks and all teaching staff. It 's super useful to go to the forum when I got confused in the assignment.

创建者 Mark M

Jun 08, 2017

I really like this approach of the specialization. Data visualization is a great topic and this was very insightful for one week.

However as with all other courses in this specialization I miss qualified feedback on my submissions.

创建者 Jun W

Jul 29, 2018

I've learned a lot from this course. Not only python, but also the philosophy of plotting. Data ink ratio is really important. Thanks Chris. And also thanks to Filip. Many tricks you introduced are very impressive and useful.

创建者 Carolyn O

Aug 19, 2019

Learn alot, but intermediate level, so you have to learn alot on your own and fill any gaps you have.

Great jump start and overview into real visualization. Like that its peer reviewed. Done professionally and academically.

创建者 SRIHARI

May 16, 2017

Its an essential course for all data scientist and also analysts work with every day visualizations. This course taught me about many things of Matplotlib and pandas plots. which I am unable to learn from any other source.

创建者 Kyaw S

May 04, 2019

Course was great. The material is very helpful for my research and career. One suggestion would be that when grading peers, the figure is shown larger. It was necessary for me to right click and open figure in new table.

创建者 Jayadev H

Jun 01, 2018

Such a good course!

Dr Brooks is an amazing teacher.

Assignments are hard as always but you are forced to learn alot.

Peer review was fun except last one where I only review people that didnt put in any effort:(

Thanks Dr!

创建者 Wenlei Y

Oct 13, 2019

GREAT COURSE! I have learnt a lot about data analysis and presentation, which are "essential skills" for lots of other fields nowadays. For example, these skills will greatly help me with my research in neurobiology!

创建者 David K

Jan 17, 2020

I was a bit apprehensive about this part, but once the course progressed the options for plotting and charting became clear, I learned a lot about this subject and I could have done with this information years ago !!

创建者 Felipe L

Feb 09, 2018

I really enjoyed this class. Rather than teaching only the computational tools, the instructor took the time to describe the fundamentals of data representation and to explain how to best communicate data in figures.

创建者 Radha S

Sep 17, 2019

Excellent course I really enjoyed learning this course it has all the basic covered and doing the assignments helped me in my work. Thanks a lot for putting together this material and special thanks to the Professor

创建者 yannick t

Mar 25, 2018

Knowing about Tufte's principles definitely changes the way I decode and make data visualizations.

And as to matplotlib, knowing what's under the hood takes (some of) the struggle out of my data visualization coding.

创建者 Lawrence O

Mar 29, 2017

One of the Best Data Science Course ever. Very informative. I will recommend for all Data enthusiast wanting to know more about Python data plotting, charting and data representation.

I loved it, hope you will too.

创建者 Roberto C

Oct 15, 2019

This course is great, I learned a lot of data visualization techniques, thank you to Professor Christopher Brooks, the University of Michigan and Coursera for making this quality material available to the public.

创建者 Li J

Sep 11, 2017

Very hands-on and good way to practice problem-solving skills (you'll have to research ways to conquer the homework assignments such as checking Stack Overflow, course discussion forums and Python documentation)

创建者 Meher B

Aug 23, 2017

Excellent course with very good assignments and help. I learned a lot doing the assignments, following the lectures and reading through the discussion forum. Thanks to the professor and the teaching assistant.