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

4.5
stars
5,302 ratings
888 reviews

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 27, 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 14, 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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601 - 625 of 874 Reviews for Applied Plotting, Charting & Data Representation in Python

By Parth P

Jun 03, 2020

L

By Junaid L S

May 14, 2019

G

By Ross O

Feb 27, 2019

/

By Shourya P

Jul 02, 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.

By 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.

By Nicholas B

Jan 08, 2018

Course materials (videos, jupyter notebooks were very useful. All the code that was shared through the lectures pointed students in the right direction. Taught useful concepts. The time estimates stated in the syllabus are grossly understated. I didn't use the forums at all, as I like to learn independently, so I probably found some creative solutions, but I came to the course with substantial programming experience in python & still found that I needed much more time to complete the assignments than what was stated.

Grading was a bit easy too, as all the assignments were peer graded. Good course overall.

By Aya

Apr 06, 2018

It was good to know that visualization is possible in Python, but I would probably not use them because there are so many other tools that make it a lot easier to create interactive visualizations in a much shorter time. While I do not disagree with Albert Cairo, I do not think he is the only person we should read about nor the best visualization expert. Assignments were good, but peer reviewing was not always great; I wish to not be graded by peers who do not follow instructions and give poor grade because they do not understand the course content and/or just out of spite.

By Maximilian W

Jun 29, 2019

The course gave a really good overview of design principles for displaying information, something worth learning even if you aren't going into Data Science.

Really good course. Its a good mix of active and passive learning. Well formulated lectures, and interesting and challenging assignments - at least you can make them as challenging as you like..

Initially sceptical about the peer review system for this kind of learning, but actually received good and clear feedback, and was able to see the learning and approaches of other people.

By Xiaojun M

Nov 16, 2019

The course itself is great. For those complaining it's not detailed enough I think data scientists need to learn how to search for code and adapt it for their own purposes. If it's too hard to achieve in this course, probably start from a easier course or this is not the right career for you.

However the grading system is broken. Cheaters just submit empty/irrelevant answers and trying to get 3 other people to give them good score on those empty answers. All the 3 reviews I've done for assignment 4 are such cases.

By Leo C

Jul 10, 2017

Great course to get one very comfortable with the matplotlib library without going too deep under the hood. I wish there was a bit more focus on the various advantages of using other libraries such as seaborn and Bokeh, but given the course's length that would have been hard to squeeze in.

I am hoping there will be a second part to this course, focusing on real-world data visualization problems and converting graphics, with newly acquired data science skills from other courses in the series, into a full portfolio.

By sam s

Jun 22, 2020

It gives you a nice overview knowledge of the concepts. The instructional videos are too brief in my opinion. Some concepts do not have enough instruction to learn unless you have a computer science background and some assignments are frustrating because they do not give enough of the tools to even understand posts on stack overflow. That being said, by the end of the course I was able to make a very pretty graph and learned some useful academic concepts on plotting style in addition to the programming knowledge.

By Max P

Nov 30, 2017

Interesting course with several ways to plot data in Python. I think it briefly goes over the main topics, but I would have liked to see some more examples and explanation. Also, the assignments at sometimes focussed to much on a particular plotting exercise, whereas I would've preferred more exercises with a bit simpler plots yet exposing me to more libraries. On the other hand, the assignments were very relevant and insightful.

By Ramon S

Oct 14, 2020

Pretty good course! The only reason I didn't give 5/5 is because the 3rd assignment required you to know quite a lot about custom colours and how to change the colours based on values. This was not covered in the lectures and was a high pain point for me. I understand that there is a level of finding the information yourself in this course but this really did take me a very long time as the matplotlib documents are quite dense.

By Marianne O

Sep 17, 2018

Another great course, very informative and useful with good real-world assignments. Very clear lectures and the Jupyter notebooks are very useful too. My only gripe is that assignments are graded by other students. Not ideal. Some students don't fully grasp the concepts. You can resubmit so that you'll be graded again, but... that doesn't guarantee you'll get better graders. But that aside, it's a great course!

By Cathryn S

May 22, 2020

Excellent course, which will teach you a lot if you put the effort in. I spent a lot of time exploring matplotlib, and python, as well as reading the design resources.

Unfortunately, when I marked the final assignment, 2 of the 4 I saw were clearly plagarised. This seems to be an ongoing problem, and so the certificate itself should be treated with caution. That's why I've given it 4 stars, rather than 5.

By Tahir M

Jun 28, 2017

This course teaches the extremely important concept of high-quality visualization in data science. Having performed similar staff in PhD, I did not have much difficulty in assignments, but it can be tough to learn and apply the concepts for beginners, if they do not spend some significant amount of time for the assignments. There could be more practical quizzes or practice exams to aid learning.

By Frantisek H

Jul 15, 2017

The course taught me well how matplotlib works, as well as quite a bit of theory of making plots and what to look for. This knowledge is very useful and applicable in many situations when doing data science. On the other hand, it required perhaps too much work. Ocassionaly I had a feeling some of the work was repetitive and not leading to new knowledge any more. But overall, very well worth it!

By Victor M S D

Jul 01, 2017

Great course, I wish I could have more time between evaluations to explore more details and artistic details of matplotlib figures. It have four weeks and the necessary contents are mostly in the course but there are many interesting external references that help in the course if they are read. Stackoverflow questions and answers are very useful to accomplish some course objectives.

By Nan B

Oct 22, 2019

The material of the first week is extremely good and inspiring. However, the following lectures and assignments aren't directing us to the exact result. Could have given more lectures on how to generate those high-quality graphs. For now, everything is too basic to that goal. Looking forward to the more advanced data visualization stuff!

By Darell B

May 28, 2018

I found the course to be very informative and requiring the student to think differently about data and how to represent that data. I also like the ethical aspects of the course, that require the author of the charts to really thinking about the message being conveyed, how it is be presented and the message that might be inferred.

By Dairui Y

Aug 26, 2020

Overall great class, you will nead tons of research outside the class material, but you do learn a lot. P.s. so many learners just copy and paste the final project which is annoying. I was expecting to see some new way to to analyze problem by utilizing new skill that people acquired from this class. Otherwise all good.

By Gennady I

Mar 20, 2017

Good intro to plotting, charting and visualization in Python. Focuses mainly on matplotlib. I feel good about the content that I learned, but also feel like I wanted to learn more in this class. Maybe more coverage of other python charting libraries. More examples of financial type charts -- High/Low/Open/Close etc.

By Fabian G

Apr 26, 2020

Theory part was kept quite short and most of the time is spent programming, which I liked a lot. You will need to research lots of stuff on your own to finsih the assignments. Maybe some more information would have been helpful at times.

Overall a solid course and I certainly improved my coding doing the exercsises.

By Yonatan S

Oct 23, 2019

Good introduction to working with matplotlib.

All the parts about theoretical/aesthetic considerations when making figures were, in my opinion, very fuzzy, unenjoyable and somewhat of a waste of time. These are things which should be taught through experience or many specific examples, not long-form articles.

By Ben B

Dec 14, 2017

Most of the learning was self-directed as I worked through the assignments using Stackoverflow and other online resources and documentation. It would have helped to provide a lot more instruction on customizing templates such as the Seaborn library, adding notations, and fixing alignment issues.