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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

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1,000 条评论


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....


Jun 26, 2020

its actually a good course as it starts from fundamentals of visualization to the data visualization,the assignments this course provide are exciting and full of knowledge that you learn in course ..

May 13, 2020

I am going for the specialization and I know this is just the second course in it and I haven't even seen the further courses yet, but this is already my most favourite course in the specialization.


676 - Applied Plotting, Charting & Data Representation in Python 的 700 个评论(共 984 个)

创建者 Indrajit C

Jun 9, 2021


创建者 Abdikarim I S

Nov 7, 2020


创建者 Кулжумуров Д Б

Oct 26, 2020


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Oct 19, 2020


创建者 Akshay P

Oct 2, 2020


创建者 Marlon Z R A

Aug 26, 2020


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Aug 22, 2020



Jul 25, 2020


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Jul 15, 2020


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Jun 28, 2020


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Jun 2, 2020


创建者 Hong R C

Sep 8, 2019


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Jul 15, 2019


创建者 Warnakulasuriya N E P

Jun 28, 2019


创建者 karthik l

Oct 22, 2018


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Jun 26, 2018


创建者 Piotr B

Jun 1, 2017


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Jun 29, 2018


创建者 Parth P

Jun 3, 2020


创建者 Junaid L S

May 14, 2019


创建者 Ross O

Feb 27, 2019


创建者 Sunny

Jan 9, 2021

This was a very good course and I feel like I really learned a lot. It starts out with a module on how data visualizations can mislead (intentionally or unintentionally!) and principles of good data visualization. I found it very informative. The instructor used good examples and also walks through the tweaking of a plot to follow the principles of good data visualization using matplotlib.

Subsequent modules give you lots of experience with the matplotlib library and the process of transforming data and making visualizations. There is often a moderate amount of flexibility in the assignments, giving the learner the opportunity to take as much as they want from the experience. You get back what you put in. Multiple assignments have you go out in the real world to look for charts and data to use in your assignments, which give you a very good opportunity to apply what you've learned, moreso than in constrained assignments where data is given to you.

My only complaint is the peer grading system, but I wish I could only dock half a star for it. I think it was actually implemented very well for a peer-grading system in a MOOC, and I even think that peer grading was the appropriate choice of grading system for this course, but of course it is going to have its downfalls. You are graded on a rubric provided by the instructor which mostly awards points just for completion of various parts of the assignment. This is how it has to be, as judging the quality of a visualization is very subjective (and dependent on the grader's comprehension of the course content), and students' grades shouldn't suffer because one of their graders doesn't like the colour red or because they don't understand the principles we are supposed to be applying.

As an aside, there are many complaints that students are directed to read the documentation of a given library, google, search stackoverflow, etc. A course cannot teach you everything you need to know about a library. You are going to have to look things up yourself, especially when debugging. This is the reality coding.

创建者 Jordanka M

Mar 13, 2021

I liked this course. It was very practical. The reading material was very interesting and valuable. Project had some flaws in terms of formulation of questions but they really pushed me to search and look for help. That in my opinion was actually good and I think that after each of these courses there is still a lot we need to learn ourselves. The course materials was laid out pretty well. Sometimes I had a feeling that things were a bit rushed (like introducing seaborn at the very end) . There is a lot of software terminology involved in the beginning when explaining matplotlib notebook and it was hard to follow that part. My biggest complaint is the Coursera's online Jupyter notebook. I got very frustrated with it. Even if you save your work frequently it often happens that the connection does not work or isn't strong and after you close your assignment you edits are lost!!! My advice, download all necessary links and work in your own Jupiter notebook and then upload the assignment.

创建者 Shourya P

Jul 2, 2017

I think the greatest strength of this course is that at the end of this you will be very confident in writing code for creating data visualizations. However the expected timelines for completion of assignments are completely above expectations. Unless you already have experience with matplotlib and its API, it is difficult for students to cope up.

But on the other hand searching for stuff online on stackoverflow and matplotlib also was a really enlightening experience and teaches you are not the only one having these kind of problems. I would have loved to see more video explanations on ScalarMappable objects which was a huge part of the assignment but was not covered in the video lectures. Also would have loved to see more concepts explored about sea born package.

创建者 Peter B

Jul 11, 2018

Great course!A couple things keep it from being 5 stars. 1 - the content comes a little fast without enough reinforcement. The balance here isn't perfectly struck as it is in the 3rd course of the specialization - Machine Learning. Although the content of week 1 is good, I think quite a bit of it should be optional and substituted with more coding exercises and longer assignments in the subsequent weeks. Week 2 has a bit too much esoterica for an intro course, and I'd rather have week 3 and 4 concepts reinforced more instead. At the end of this course, and after a few days, I'm confident I can look back and make any kind of plot I want. A minor quip - much of the code for the course will throw deprecation warnings in the latest versions of matplotlib.