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學生對 密歇根大学 提供的 Applied Plotting, Charting & Data Representation in Python 的評價和反饋

4.5
3,554 個評分
582 個審閱

課程概述

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....

熱門審閱

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.

篩選依據:

551 - Applied Plotting, Charting & Data Representation in Python 的 568 個評論(共 568 個)

創建者 Benny P

Oct 02, 2017

The video guide is pretty good, it shows you a lot of thing that you need to learn. It covers a lot of breadth and depth, but only briefly. For further info, and for the most part of your time when doing assignment, you need to seek the relevant manuals yourself. But that is fine, because matplotlib is very very rich library and there's no way all can be taught in a single course like this, and also it makes you familiar with how to find information yourself.

The main drawback is with the assignments though. I'm okay with the peer review system. The problem is that the assignment specification is not too clear. For example, in assignment 4, you need to think yourself about what you want to visualize. So a lot of time was spent on thinking about WHAT problem to display rather than HOW to address the problem (using plotting/visualization), which is the subject of this course.

創建者 David P

Mar 28, 2017

Decent overview but could have spend more time showing plotting techniques in more detail than showing what makes an appealing plot. Also The section on the back-end of MatPlotLib was more detailed than it needed to be for quick overview but not detailed enough to be very useful.

創建者 Bart T C

Sep 12, 2018

An excellent course for learning plotting, but requires a very strong background in stats if you want to avoid being lead into mistakes in your thinking about how to evaluate data.

創建者 Amit m

Apr 09, 2017

The first week was interesting as it broke down the different layers that occur behind the scenes of matplotlib. The next couple of weeks felt a little shallow and rushed. Maybe we will explore more of the functionality in the later courses.

創建者 Steven O

Mar 18, 2017

I think there there is too much time given to the esoteric of what makes plots pretty rather than the nuts and bolts of how to do it and the limitations of using Pandas and Matplotlib for real world data

創建者 Xing W

Jul 25, 2017

Not well organized.

創建者 Jason B

Oct 16, 2017

Some of the material was interesting but on a whole not nearly as engaging as course 1. I fully can appreciate how the principles of chart design are valuable to the subject matter covered in this series but on a whole I would have liked more focus on the technical skills and maybe had the academic perspective on design extra reading.

Also the peer grading portion of this course is a little rough. The people that graded my work were great but I don't expect them to engage my work in a very meaningful way. It's not realistic to ask them to give their full effort to grade 3 assignments for an online course that they pay for. My personal preference would have been to structure the assignments so that they could be automatically graded like in course 1.

創建者 Linda L

Jun 13, 2018

I am not too crazy over the peer review assignments plus the course was hard to follow

創建者 Filippo R

Mar 30, 2018

The rate lectures/assignment is disappointingly low, a lot of time goes only to find data available online and to find questions to answer. In my work I have plenty of opportunity to apply data science and very little knowledge on how to. This course gave me more assignments and not so much tools.

創建者 Kaya Ö

Apr 24, 2019

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創建者 Kumar I

May 25, 2017

Compared to the first course in this series, I found this one not so challenging. The final project was very loose (I understand that the instructors wanted to give the feel of a real research). The first assignment was very superficial. As much as Cairo's principles are important, I feel devoting an entire assignment to that is justified. The second and third were relatively straight-forward, but that was perhaps the saving grace.

Wish the course spent time in dwelling on complex visualizations.

創建者 Alexandre G

Oct 11, 2019

This course only scratches the service of the subject and asks the learner to learn almost everything by himself searching the Internet. The lecture content must be expanded significantly in order to give enough knowledge for the programming assignments.

創建者 Bruce H

Feb 14, 2018

The concept is good: introduce the theory of information visualization and introduce how to make charts with Python and matplotlib. Unfortunately the materials are deficient for the programming part. There aren't nearly enough practice exercises to help you learn matplotlib. The previous course in this specialization (intro to data science in python) by comparison has many more guided practice exercises, and I am disappointed that this course does not live up to the standard set by the first course. If you are taking the complete specialization, as I am, then I guess it's worth it and I hope the next courses in the series have more material.

創建者 jun L

Jul 28, 2018

The course does provide a good guideline on evaluate a good chart. However, as a fundamental course of introduce plot in python, I don't think the course is well structured. I can't say I learn too much from this course.

創建者 Harshad H

Jun 19, 2019

Too slow grading and a very inefficient process.

創建者 Darien M

Nov 21, 2019

This course is anbalagous to taking a creative writing course, but all lessons are on vocabulary and grammar. Once again the lectures are unhelpful. The discussion forum in this course does not provide much help (unlike the first course in the sequence). I suppose they are applying the graduate school mentality to teaching: you want to learn it, figure it out. I myself am definitely not at that level right now.

The assignments are challenging, and you will learn from them, but you won't learn deeply. It seems all very superficial. Just look things up to get them done. Type in any question you have and a solution will certainly appear on SO. Why not give students the tools necessary to solve challenging problems on their own (like in Python for Everybody and Python 3 Programming)?

Professor Brooks is clearly passionate about programming and is very accomplished/intelligent. Unfortunately the teaching in this course is of low quality.

創建者 Randal P

Nov 18, 2017

Hate the community evaluation process.

創建者 haozhen6

Aug 27, 2017

Too many jargon and all vedios is useless, he makes me feel like he is trying to show his English and Knowledge.