Chevron Left
返回到 Data Visualization with Python

学生对 IBM 提供的 Data Visualization with Python 的评价和反馈

4.5
12,229 个评分

课程概述

One of the most important skills of successful data scientists and data analysts is the ability to tell a compelling story by visualizing data and findings in an approachable and stimulating way. In this course you will learn many ways to effectively visualize both small and large-scale data. You will be able to take data that at first glance has little meaning and present that data in a form that conveys insights. This course will teach you to work with many Data Visualization tools and techniques. You will learn to create various types of basic and advanced graphs and charts like: Waffle Charts, Area Plots, Histograms, Bar Charts, Pie Charts, Scatter Plots, Word Clouds, Choropleth Maps, and many more! You will also create interactive dashboards that allow even those without any Data Science experience to better understand data, and make more effective and informed decisions. You will learn hands-on by completing numerous labs and a final project to practice and apply the many aspects and techniques of Data Visualization using Jupyter Notebooks and a Cloud-based IDE. You will use several data visualization libraries in Python, including Matplotlib, Seaborn, Folium, Plotly & Dash....

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.

筛选依据:

1626 - Data Visualization with Python 的 1650 个评论(共 1,952 个)

创建者 Thi N T N

May 25, 2024

Some task requirements in the 1st part of the final assignments are not consistent and clear. It is even not coherent. Some hints and template solutions have the same problem.

创建者 rorschach p

Dec 21, 2021

I think the final project should add more difficulty and tasks. Or provide the option to choose the difficulty level base on the learner's python and data science experience.

创建者 Dominique B

Jun 24, 2024

Challenging is good ! But the instructions weren't that clear and I really had to employ myself to earn this one. Proud now, but with some headaches (and coffees at night).

创建者 Jessica U

May 20, 2020

The assessments are a little silly- the quizzes trip you up on minor syntax instead of being concept-focused, and the final assignment used some skills that weren’t taught.

创建者 Everett T

Jul 10, 2019

1) Quite a lot of contents of the final assignment are not covered in labs/videos

2) Huge portion of videos is redundancy and repitition

3) Labs cannot be exported to HTML

创建者 Alex M

Dec 6, 2020

The instructor provided lots of useful code, but the final assignment is unnecessarily difficult because the required code customization was not covered in the course.

创建者 asher b

Nov 27, 2018

Course was pretty good, except... The final project was too much of a stretch, had to google too much to figure stuff out that wasn't in the lectures or practice labs.

创建者 Claudiu I

Sep 23, 2021

The lab excercises are too time-consuming, for reasons unrelated to the course material. I found it hard to simply run the programs in the development environment

创建者 Kristine M

May 31, 2021

The final project needs some review and updating. It was a frustrating couple of hours to try and get it working. I finally got it half way working and gave up.

创建者 David C

Mar 17, 2022

The course starts out great with some insight into Matplotlib but gets very hung-up on Cognos and Dash and approaches something similar to Java web development.

创建者 Courtney G

May 15, 2020

The final assignment required knowledge that was not thoroughly explained in the videos and labs. Some of the practice labs could use more/better explanations.

创建者 Pranav C

Oct 26, 2023

dash components have been depracted and yet this course hasnt been updated , some parts are hard and too much of a jump in final project in terms of difficulty

创建者 Baptiste M

Nov 4, 2019

Overall a good review over the different graphs, yet the course feels wonky in the flow of this courses covering stuff already studied and staying on surface.

创建者 pooja j

Jun 29, 2021

week 4 - no outtput received in dashboard in new window plus only errors received in jupyter notebbok even after copy paste of solution in entire week 4 labs

创建者 Andre M

Jun 12, 2023

MIxed quality of the videos / labs. I found the labs about Matplotlib in Jupyter excellent, the part regarding Plotly and Dash were not so well explained.

创建者 Juan I B

Jul 3, 2020

Final Assignment covers many aspects that weren't explained in the classes. Meanwhile, every video repeats the same data management segment over an over.

创建者 Kevin

Jul 15, 2024

I am disappointed with module 4 and 5...I have the impression that this course was done by an external Indian service provider? skillup.online ?

创建者 Soh J P

Mar 19, 2020

Some of the content tested in the assignment is not covered by the lessons, staff is not fast and helpful in answering questions from students

创建者 Stan M

Aug 18, 2020

Great course, very bad exam. Most of the stuff in the exam was impossible to do using the classes. Level of the exam was way too difficult...

创建者 Nguyen T V A

Jun 1, 2019

Labs are very difficult and hard to follow. There is a big gap between what we learn from the videos and what we are asked to do in the Labs.

创建者 Jingjing L

Feb 4, 2021

The final exam is way too frustrating as some content isn't covered in the course, especially about modifying the key for the last question.

创建者 Tsungai J M

Oct 25, 2019

There some information gaps in the labs and lectures that made the assignment quite challenging without seeking further external knowledge.

创建者 Kevin G

Oct 18, 2020

While the classes are interesting, the course should be updated.

Folium version is 0.11 now, not 0.5 anymore, and there is lots of changes.

创建者 Tania P

Aug 16, 2022

The labs need to be improved. They were had to follow and there was a lot of trial and error involved in order to complete the course.