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

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12,236 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.

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1151 - Data Visualization with Python 的 1175 个评论（共 1,954 个）

创建者 Dilfuza T

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Jun 14, 2024

GOOD

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Jun 14, 2024

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Jun 6, 2024

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May 28, 2024

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May 28, 2024

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May 26, 2024

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May 3, 2024

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Sep 13, 2023

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Jul 22, 2023

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Mar 20, 2023

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Jan 19, 2023

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Nov 6, 2022

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Nov 2, 2022

nice

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Sep 28, 2022

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Apr 25, 2022

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Apr 24, 2022

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Jan 20, 2022

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Dec 23, 2021

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Dec 18, 2021

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Jun 24, 2021

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Jun 15, 2020

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Jun 2, 2020

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