课程概述
热门审阅
JG
Apr 16, 2020
This is a very helpful course. It introduces a variety of data visualization tools. The interesting practices in the lab sessions inspired me to explore different solutions for a problem.
MN
May 15, 2019
More in class projects similar to final assignment where we can challenge our knowledge as we are all remote and it takes time to communicate through the available coursera forums. Thank you.
1651 - Data Visualization with Python 的 1675 个评论(共 1,952 个)
创建者 Alla F
•Dec 23, 2024
Labas where Dashboards are - uncomfortable. Instruction how to use workspace - after Laba. Many bags. Need to read forum all the time
创建者 Timothy T
•Jan 14, 2024
the course should have been divided into fundamental and advanced visualizations. there are too many tools for one course to grasp
创建者 Lin W
•Aug 3, 2019
The course content does not sync up with the assignment, you need to self-study about many other materials to get the certificate.
创建者 RD P
•Sep 29, 2021
Data Visualization with Python Course must be used on a certain date so that it is quite distracting to the target participants
创建者 rohikian
•Jul 26, 2025
Great course! I would be more pleased with this course if more detailed explanation for the final assignments were provided.
创建者 Charles J
•Apr 14, 2020
Actually I think the final assignment part 1 is too difficult for the videos and lab courses to draw the bar plot as required.
创建者 Pedro F
•Aug 24, 2019
Video explanations and difficulty of the assignments don't match. Unnecessary long and tedious exercises. Needs to be revised.
创建者 Matteo E
•Aug 1, 2019
The way topics are explained during lectures are not enough deeply treated for the final assignment. It is anyway interesting.
创建者 Spataru N
•Oct 23, 2018
Out of all IBM courses so far, I didn't like this that much. IBM should put more emphasis on teaching database transformation.
创建者 Robert T
•Jun 23, 2019
Not all of the tutorials rendered correctly. Information was good. Would have preferred more questions throughout the videos.
创建者 Fan B
•Jan 4, 2022
not good, many typo in the lab instructions, many times the lab wont work out, i think this issue realy needs to be fixed.
创建者 Paweł K
•May 2, 2019
Peer grade assignment in this course is far too hard and packed with a bunch of topics not directly covered in the curse.
创建者 Mohammad Q
•Aug 23, 2019
Great overview course, I wish if there longer videos that explains the content.. not just trying to do the lab by myself
创建者 Ramsrinivas A
•Jan 2, 2020
Part about Maps can be some what more extensive. The Thing taught in Lesson and Assignment does not maps section alone.
创建者 amir s
•Sep 9, 2019
In general, it was a good course.
Some of the quizzes were very much based on syntax which I don't think is very useful.
创建者 Andrey P
•May 4, 2024
I usually enjoy IBM courses, but this one is a disappointment. The labs are of poor quality and provide little value.
创建者 Sowmya S
•Feb 19, 2021
The course is good. However, instructions, support and details to actually help you learn and understand is useless.
创建者 Mahmoud H
•Sep 4, 2019
The course is really good, but Matplotlib is not popular now. Plotly is trendy and more interactive than Matplotlip
创建者 Danila M
•Aug 20, 2021
Many bugs in the practice labs and the final assignment is a way too far from the material that has been taught.
创建者 Sokob C
•Jul 21, 2020
It was a difficult course but it could've been better if there were little short quizzes during all the videos.
创建者 Pavan T
•Sep 18, 2023
NOT AS GOOD AS OTHER IBM DATA SCIENCE COURSES WHEN COMES TO DETAILING AND EXPLANATION. IT IS OVER SIMPLIFIED.
创建者 Aman A
•Jun 5, 2020
A lot of techniques have not been covered in the module even though they did show up in the final assessment.
创建者 Henrie E N
•May 29, 2020
The course content and labs are a bit light on context considering the work required in the final assignment.
创建者 Mayank S
•Feb 12, 2020
Very less detail and seaborn was not covered which is better for visualisation than matplotlib in most cases.
创建者 Jonathon V
•Apr 22, 2019
Some of the notebooks given did not function correctly, overall did not ruin the learning experience thought.