Artificial Intelligence & Data Science
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Improving Your Data Visualizations in Python

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Course Report - Improving Your Data Visualizations in Python

Course Report

Find detailed report of this course which helps you make an informed decision on its relevance to your learning needs. Find out the course's popularity among Careervira users and the job roles that would find the course relevant for their upskilling here. You can also find how this course compares against similar courses and much more in the course report.

Course Features

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Duration

4 hours

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Mobile, Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Intermediate

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Teaching Type

Self Paced

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Video Content

4 hours

Course Description

Data visualization is a crucial aspect of data science, as it allows for the discovery of insights and effective communication of results. While scatter plots and bar graphs are commonly taught, the true power of data visualization lies in understanding how, what, and why you visualize your data. This course focuses on creating captivating visualizations that effectively communicate your findings. It includes a comparison of US data and explores how uncertainty can be displayed. The course concludes with the use of open-access data from farmers' markets to create a polished visual report. By learning Python and utilizing its tools for data science, participants can gain the necessary skills to excel in this field.

Course Overview

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Virtual Labs

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International Faculty

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Post Course Interactions

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Hands-On Training,Instructor-Moderated Discussions

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Case Studies, Captstone Projects

Skills You Will Gain

Prerequisites/Requirements

Introduction to Data Visualization with Matplotlib

Introduction to Data Visualization with Seaborn

Python Data Science Toolbox (Part 2)

What You Will Learn

In this course you will learn how to construct compelling and attractive visualizations that help you communicate the results of your analyses efficiently and effectively

Learn to construct compelling and attractive visualizations that help communicate results efficiently and effectively

We will cover comparing data, the ins and outs of color, showing uncertainty, and how to build the right visualization for your given audience through the investigation of a datasets on air pollution around the US and farmer's markets

Course Instructors

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Nicholas Strayer

Biostatistician at Vanderbilt

I am currently biostatistician and data scientist at Vanderbilt University. My research focuses on the fusion of machine learning and data visualization to explore and explain electronic health recor...
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