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Learner Reviews & Feedback for Applied Plotting, Charting & Data Representation in Python by University of Michigan

4.5
stars
6,219 ratings

About the Course

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....

Top reviews

OK

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 ..

RM

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.

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101 - 125 of 1,035 Reviews for Applied Plotting, Charting & Data Representation in Python

By Gisela M O

Jun 11, 2021

since i was given the course for free i dont regreat taking it. while doing the assigments i learned new things. but to be honest very little from what i learned come from the course content, as i mostly had to research everything online, and there's no usefull feedback. the first course of this especialization was much better.

By 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.

By Jonathan C

Aug 9, 2021

Uses a lot of outdated python packages which is sad and a lot of people use the course to just farm certificates which is also not nice but sadly possible because there is not much monitoring or whatsoever of the people who made the course. But the rest makes for a half decent course

By 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.

By Georgii B

Mar 20, 2020

Peer-grading is horrible. Nobody reads assignments or checks your work - they just give top grade for every category and leave "." as a comment, all to breeze through the mandatory peer grading. This certificate has very low value.

By 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

By Rodrigo L

Jun 27, 2021

I feel like I didn't learn much. Various topics are covered but quickly and superficially. The notebooks provided each week are useful. Almost all assignments are peer reviewed.

By Jean-Michel P

Jun 2, 2021

Another one of those UoM courses where you learn nothing unless you scour the internet for actual education. Makes one wonder what value UoM brings to the table...

By Linda L

Jun 13, 2018

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

By Xing W

Jul 25, 2017

Not well organized.

By Kaya Ö

Apr 24, 2019

.

By Sarah S

Mar 30, 2021

If you are already an expert at python and data science you might enjoy this course. If, on the other hand, you would like to learn plotting in python, this is a very poorly taught course.The lectures are too fast and cover too much material before you get a chance to practice. When you do get assignments, they are ambiguously worded and expect you to research way beyond the course material before being able to do them. Very disappointing.

By Yaron K

Sep 20, 2017

Disappointing. Matplotlib is built from layers of interacting functionality, and this course doesn't create a structure to understand it. Unclear and confusing. Note however that the following courses in the specialization show matplotlib code but don't necessitate writing it, so you can do them (at most auditing this course before) and only return to this course if you want a specialization certificate.

By Rohan G

Dec 30, 2019

This course is absolutely terrible, and in no way self-sufficient. The professor basically tells you what can be done using matplotlib, give you a cursory example and leaves you all on your own to understand what actually happened by referring to sources such as google or stack overflow.

By Anders C

Mar 23, 2021

This course needs a serious overhaul. Assignments are very unclear and only reviewed by other students, which questions the legitimacy of this course certificate. Lectures are shallow and clearly made by very unexperienced lecturers.

By Abhimanyu S

Apr 11, 2020

Nice assignments but spent most of my time on Google rather than utilizing my notes made from the video lectures. That kinda destroys the purpose of taking an online course in the first place.

By Muhammad A F

Oct 31, 2021

Very hard to grasp the content as the content is not well explained in the required detail, as it should have been.

By Jaekwan S

Sep 4, 2022

A lot of technical errors to submit assignments....

Spent more time to resolve the technical issues than learning

By Freya

Aug 6, 2020

Assignments are not clear at all.

Things covered in videos are not enough to complete course assignments.

By Konstantinos K

Apr 20, 2021

fake reviews from coursera bots, assigment is scam too :P

By Harshad H

Jun 19, 2019

Too slow grading and a very inefficient process.

By Sophia C

Oct 14, 2018

Not very well done

By Yue Z

Apr 8, 2017

really bad!

By ROHAN S

Jul 27, 2020

NOT GOOD

By Leonid I

Sep 17, 2018

Overall, the course is great and definitely deserves 5-star rating.

However, it starts quite slow and in my opinion first few lectures discuss irrelevant topics, like minimalism of presentation. The problem is that a person can't grasp them without experience...

For example, several videos discuss idea of Edward Tufte. I understand that CS and mathematical statistics are the background of the instructor, but really, Tufte had only repeated well-known basics. Indeed, it was Leonardo da Vinci who first said that "simplicity is the ultimate sophistication". He was followed by Antoine de Saint Exupéry with "It seems that perfection is attained not when there is nothing more to add, but when there is nothing more to remove" and the KISS principle of Kelly Johnson of Lockheed Martin Skunk Works.

Perhaps, for the authors of the course software engineering is closer: https://wiki.archlinux.org/index.php/Arch_Linux#Principles ...