学生对 University of Michigan 提供的 Applied Plotting, Charting & Data Representation in Python 的评价和反馈
课程概述
热门审阅
A
Mar 5, 2018
Very helpful to understand what it takes to make a scientific and sensible visual. Recommended for someone who is interested in learning data visualization and does not have a background.
EL
Oct 1, 2017
it is a good course to help me have a glance to the data visualization area. However, I think I cannot learned a lot from the course and the homework is so easy that I haven't practice enough.
801 - Applied Plotting, Charting & Data Representation in Python 的 825 个评论(共 1,046 个)
创建者 Luke G
•Mar 3, 2018
This course is pretty good. There's a lot of general guidance and the topics covered are very broad. Expect to spend some time reading documentation, but overall you'll get a really good coverage of a lot of different things.
创建者 Michael H
•Feb 11, 2018
The course was very informative and provided good exposure to plotting tools in Python. However, I don't feel that the peer-reviewed assignments were very effective as nearly anything submitted would receive a passing grade.
创建者 KylinMountain
•Apr 26, 2018
About pandas plot and seaborn, it is very short and it looks like ends suddenly. Besides, the design of practice is not very good as well as first class 'Introduction to Data Science in Python'. It need improvement.
创建者 Alan J
•Apr 2, 2017
Excellent course to begin matplotlib. It shows us the intricacies of the matplotlib by showing the basics and prodding us to go deeper by reading the documentation. The assignments are also really good. Recommended!
创建者 A W
•Aug 14, 2018
This course gives me an overview of data visualization, and I felt pretty accomplished with that goal. Data science is a broad subject, this course is a good place to start. It is an intermediate level course.
创建者 Arvind S
•Oct 25, 2020
It is a nice course ,if you are looking to start your journey in data visualization then this course may interest you a lot, although this course covers basic as well as some advance lessons in visualization.
创建者 Manuela D
•Feb 11, 2018
The very last 2 weeks were quite interesting and full con concepts, whereas weeks 1 and 2 were more theorical. I would suggest to summarize initial theorical concepts and give more practical coding examples.
创建者 Mohamed A H
•Oct 26, 2018
The instructor is very professional. The course has really high-quality academical information that come very valuable and handy when you get to create charts and visualize the data. Definitely recommended!
创建者 Steve M
•Mar 3, 2018
An very good overview of how to develop honest, functional and aesthetically pleasing data visualizations. With additional instruction in how to use matplotlib and Seaborn, it would be a five-star course!
创建者 Marija K
•Mar 17, 2021
I liked this course, but I thought that it would be a little more advanced. I would have liked if it dived a little deeper in how to use visualizations to make decisions while analysing and cleaning data.
创建者 ayush k
•Jul 5, 2018
Practical course with hands on exercise to make you well versed in Applied Plotting, Charting & Data Representation in Python. I recommend at least every college student should experience this course
创建者 Ivan R
•Feb 28, 2018
It contains very good recommended lectures, good material and explanation about matplotlib to grasp a big picture. However, you must invest a lot of time on your own to research deeper in the topic
创建者 Vishal S
•Mar 20, 2018
Week 1 is a little bit theory and boring for me because that doesn't interest me but week 2 and week 4 is amazing. Especially week 4 assignment is too good. Overall the course is worth learning.
创建者 Brandy B
•Aug 18, 2017
I thought this was a really good introduction to matplotlib and some of the things you can do with it. The final project we got to apply what we'd learned to real data, which was a lot of fun.
创建者 Tarun Y
•Aug 3, 2020
This course is really helped me not only to increase my knowledge about the tools but also with the help of the additional reading and optional assignment help me out to improve my skill.
创建者 Vidya M
•Aug 23, 2019
It's a good intermediate level course . Prior work in Python plotting functions does help . Assignments are good and make you stretch your skills . Discussion forum is quite supportive.
创建者 Ezequiel P
•Sep 8, 2020
Good course! Could be improved by assignments better suited to the lectures. But having them pushing a bit further and forcing you to figure things out on your own is definitely great
创建者 Temuge B
•May 16, 2019
Week 1 of the course is complete waste of time but weeks 2 to 4 are decent. Only complaint is that the assignments are not very clear and also it doesn't go very deep into matplotlib.
创建者 Venkata K N J
•Aug 19, 2020
Great topic to learn. Fantastic assignments - learnt a lot from self learning, stackoverflow mainly. Though the course cannot cover all the details, major topics have been covered.
创建者 James S
•Feb 26, 2018
This was good course, but a little heavy going at times. I actually stopped it, then came back to it after doing course 4 in the specialization. It is worth it tho, so keep going!
创建者 STEVEN V D
•Dec 28, 2017
Really interesting course covering matplotlib functionality. There is a lot of self-study required, but that's okay. Liked the demo's about Panda's and Seaborn in week 4 as well.
创建者 Ling G
•Sep 18, 2017
It's a course that is hard to be taught, because it involves a lot of human judgment in terms of aetheticism. It is good to know some examples of how to create a plot, though.
创建者 Rahul M
•Oct 8, 2020
This course is very helpful before doing any machine learning course. It helps us in understanding and creating our own visualizations, insights and representations of data.
创建者 ROBIN J
•Jul 27, 2020
Great introductory course towards data-visualization. But one requires more learning to be better at data visualization apart from the contents provided by this course.
创建者 Vishnu V M
•Jun 7, 2021
The course is good, but could have been much better. I really appreciate the efforts placed in this course. But I felt that some of the important concepts were missing