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Avis et commentaires pour d'étudiants pour Applied Plotting, Charting & Data Representation in Python par Université du Michigan

4.5
étoiles
6,123 évaluations

À propos du cours

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....

Meilleurs avis

OK

26 juin 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

13 mai 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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51 - 75 sur 1,015 Avis pour Applied Plotting, Charting & Data Representation in Python

par Mariusz K

10 nov. 2019

Too little of expounding and too much of searching the net by oneself. Too few examples. It is a self-learning but what's the Course for then?

Plus the assignments. I didn't like the peer evaluation idea, just as evaluating the others, because I don't have time for this and that's not what I came for.

First - what's the motivation of random viewers to fairly and thoroughly evaluate my work? Plus it's hard to finish the course quicker for this reason, because one has to wait a couple of days to get a grade. That's the reason I resigned from waiting for the assignments evaluations for next weeks assignments and in consequence for the certificate.

par Qiang L

27 mars 2020

The construction of this course is fine, but content is really bad. Instructor could not give detailed introduction in matplotlib. So basically you need to learn everything by yourself. On the other hand, there is huge gap between course and assignment. I would say that you should have at least intermediate level of matplotlib before you take this course, which strongly against the principal of this course. I suggest instructor giving a more general idea first and gradually providing more specific application and harder examples.

par Kumar I

25 mai 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.

par marco f

1 févr. 2022

Not the best course I've had. Video are too short and superficial. Assessment are based on personal research and often not well explained. Teaching material is quite poor, python libraries version in jupyter notebook online environment is old and it is quite difficult to find something in the forums because of this (and you need to do it because thay do not introduce enought concept about what you'll need for assessments). At the end, a really poor content course.

par Markus Z

11 janv. 2021

From the previous course I know what was coming.

And it was tuffer than Tufte...

I'm not that confident with the structure of the course. I would prefer more mini tests on checking the knowledge of the singe plotting commands and then heading to the assignment of each week.

I think that the challenge would be less frustrating when beeing more skilled with the tools in your plotting toolbox.

par Liam L

11 mai 2020

Too little teaching and too much googling. The questions are poorly defined and you end up using Stacker and the discussion forums to really understand what they are asking. I put the time in and got the answers but would have liked them to explain whats going on a bit more rather and give a bit of guidance. Also very expensive, compared to other Pandas and Matplotlib courses.

par Shuang S

15 août 2019

It taught some visualization that is not use very often and sometimes I feel I couldn't catch up the knowledge, so if you are a beginner, skip this class first.

par 2331_GRISHMA D

20 juin 2020

It was too fast. The jump from basic to advance was too quick

par Zhongtian Y

15 juil. 2020

too little explanation of the code

par Rachit G

23 juil. 2020

The content is very limited

par Darien M

21 nov. 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.

par Adam S

17 août 2020

The explanations are horrible. You either see the profesor talking which is difficult to grasp when you don't really see the code. Once you see the code it goes too fast with hardly no explanation. I understand the point to encourage students to learn how to get extra information online, but this is just too much. 95% of the knowledge I'm getting is not from the course. Waste of time and money.

par Ben A

12 nov. 2021

A better use of your time is watching youtube videos on MatPlotLIb and practicing charting with w3reasource exercises. The strength of this class is independent learning (reading library documentation and StackOverflow), which you can do without the class.

par Devansh K

15 juil. 2020

Awful course. What a waste of time! No proper explanation of the different functions used. Half the time, I'm confused. This is the pattern that Prof. Brooks follows. I'm done. I'm not enrolling in any more courses offered by him.

par Feng H

16 août 2019

Lectures are not detailed enough and speaks too fast, assignments too difficult. If I have to do my own study 90% of the time why do I need to pay tuition?

par Mack S

1 juil. 2019

There are some rubbish assignments in this course which involve searching the web for badly made info graphics.

par Naveen P

15 mai 2018

Well to be honest youtube videos are quite informative than this. Opting out from this course.

par Yifei Z

7 oct. 2017

I feel like this course is bad. Since it basically tell us to search google for everything.

par Jakob P

19 juin 2017

Too few lectures with detailed explanations of the functionality of matplotlib.

par Javier P S

8 mars 2018

A course where you practice your googling capabilities. It could be improved.

par Ben B

14 nov. 2020

This course offers a nice introduction to plotting with matplotlib (and a bit of seaborn).

Much depends on you. The videos give you general instructions, but you should also search proactive for more detailed information on your own and learn by doing the assignments. To enjoy the course as much as I did, you should be familiar with the material of the first course of the specialization (especially with pandas and data wrangling).

I really liked the peer-reviewed assignments. There are a lot of fellow learners, thus you never have to wait more than a couple of hours (or maybe a day) to receive feedback and a grade. The assignments meet different skill levels and let you decide how much effort you want to put in. You could do them in 20-60 minutes or you can really dive deep into it and learn a lot while solving provided questions and your own questions as well. It’s up to you.

par eric g

10 janv. 2021

You are going to learn by doing, less then getting a deep lecture of Matplotlib. Yes you will learn it quickly, but the lecture videos are only about 15-30 minutes a week, while the projects will take you a few hours to complete (With the last two taking significantly more time if you want them to). I was a little disappointed that I didn't get I 100% clear picture on how to use Matplotlib and Seaborn, but I do feel like I gained comfort, so it was worth taking!

par Evandro R

5 nov. 2020

And then, there it goes, another course in this amazing Specialization. This course of Applied Plotting, Charting & Data Representation in Python was magnificently well constructed. The videos, quizzes and assignments are pretty fun to dive into and, this is the first course in which I see Peer Assignment (because it makes sense) and it was great to learn with other people from all around the world!

par Thomas P

16 oct. 2020

This Course is really interesting for those who are already worked with matplotlib, numpy and scipy.

The first three weeks a lot of hard plotting is done for learing the modules. In the last lecture, week 4, the more easy way is shown with pandas built in plotting functions and a toolkit expansion - which makes the plotting more applicable when working with Pandas Data Frames.

par Omkar K

27 juin 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 ..