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Bewertung und Feedback des Lernenden für Applied Plotting, Charting & Data Representation in Python von University of Michigan

4.5
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6,018 Bewertungen
1,017 Bewertungen

Über den Kurs

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-Bewertungen

OK

26. Juni 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 von 1,001 Bewertungen für Applied Plotting, Charting & Data Representation in Python

von Feng H

16. Aug. 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?

von Mack S

1. Juli 2019

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

von Naveen P

15. Mai 2018

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

von Yifei Z

7. Okt. 2017

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

von Jakob P

19. Juni 2017

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

von Javier P S

8. März 2018

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

von 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.

von eric g

10. Jan. 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!

von 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!

von Thomas P

16. Okt. 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.

von Omkar K

27. Juni 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 ..

von Rutwik M

14. 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.

von Dipanjan G

11. Juni 2020

Great course with lots of learning. The lectures were crisp and the course inspired us to look at materials beyond the course and in the internet which is a important skill for any data scientist

von SIMRAN S

6. Sep. 2020

A beautiful Course to accompany with python and Machine Learning.

I learnt along with my peers who graded my assignments too, Thank you.

von Josselin G

13. Sep. 2019

Pretty good course the material is good.

Offers good coverage and proposes some interesting problems.

Pairs grading works pretty well.

von Somaiya J G

6. Nov. 2018

Really amazing course, Christopher Brooks salute man, you explained every details in good way that one can easily understand.

von Ahmad H S

28. Juli 2019

Amazing source

von Maria Z

10. März 2021

I am confused how to rate this course... Let me introduce my personal Pros and Cons

Pros:

1) I've learned A LOT.

2) Assignments are really interesting.

3) There is a Peers Grading system, which I personally like.

4) If you really dig into problem - there is a big chance you learn cool things.

Cons:

1) The Professor explains only the very basic stuff. It's a bit disappointing because I finally was doing the assignments with external sources of information. It was not much usage in videos.

2) You have to spend tonnes of time on your own digging into possible solutions to learn how to do the assignments. But if you care only about passing it - don't worry it will take you maximum 1 hour as there are a lot of already done examples on many sites.

3) While grading the assignments you can see a lot of copies. Once I've found my own project copied. After that I decided to leave the code with advanced charts only for my personal usage and for assignments - the simple basic charts.

To sum up - great source if you like exploring new things and digging into details on your own. It's like a tool that give you some direction and base to start. If you prefer to get information ready to use - it's not for you.

I put 4 stars out of 5 as it was a great help for me but still almost all the information I had to find on other sources.

von Muhammad S

1. Feb. 2021

Good course if you want to learn basic data representation in Python Matplotlib. I would suggest it needs a little work up in assignments and syllabus section to make it more competitive towards the end. Like building visual animations, heatmaps, clusters in assignments rather than just simple line and bar charts

von Dr. R H

23. Sep. 2020

For the last assignment, it would have been great if we could have chosen the topic of our work ourselves (e.g. sports/politics/...). I had to work on a task regarding religion, which is for me an extremely boring subject; this led me to delay the finalization of the assignment by weeks.

von Oleksii K

3. Sep. 2020

I did not find this topic really useful. I think there could have been more details about matplotlib and less information about 'what is a good plot'.

von Sandip K D

9. Mai 2020

Good course. But I think Seaborn should have been explored in detail since it's much better.

von Guo X W

4. Juni 2020

This course provides an overview to the matplotlib and seaborn library and guides learners to create useful visualisations with Python. My main issue with the course is that the various topics are not covered in sufficient detail. Successful completion of the assignments required far too much independent learning on commands that were not covered in the course (particularly for Assignment 3).

The course also covered Principles of Information Visualisation in great detail. I thought that was refreshing and useful. However, I felt that the portion on Matplotlib Architecture could be explained in more layman and palatable terms. In addition, it would have been more meaningful if the course drew more on actual real-world datasets instead of histograms generated from a random normal distribution.

von Betty C

3. Mai 2020

The material does not cover all of the assignments. I did learn A LOT by finishing my assignments, but the process was frustrating. I feel like a baby who have not learnt how to stand, but my parents ask me to run.

If you are good at finding solutions in original documentations (e.g., python, pandas, and matplotlib) and Stack Overflow, this is the right course for you.

However, if you are seeking for abundant materials and examples to sharpen your skill, sorry, this course may not right for you.

von Aarya P

20. Sep. 2020

Learnt about the different plotting and charting techniques.How to get subplots and architecture of matplotlib. Just syntax of each type of charts is shown.

The downside is there is alot of research work on your own.Also the course diffculty is quite high as i was not much experienced in matplot. Wouldnt recommened to beginners. Also teaching style could be largely improved so as the assignments.