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Understanding Data Visualization

BasicSkill Level
4.8+
11,121 reviews
Updated 09/2025
An introduction to data visualization with no coding involved.
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TheoryData Visualization2 hr14 videos41 Exercises2,400 XP250K+Statement of Accomplishment

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Course Description

Visualizing data using charts, graphs, and maps is one of the most impactful ways to communicate complex data. In this course, you’ll learn how to choose the best visualization for your dataset, and how to interpret common plot types like histograms, scatter plots, line plots and bar plots. You'll also learn about best practices for using colors and shapes in your plots, and how to avoid common pitfalls. Through hands-on exercises, you'll visually explore over 20 datasets including global life expectancies, Los Angeles home prices, ESPN's 100 most famous athletes, and the greatest hip-hop songs of all time.The videos contain live transcripts, which can be accessed by clicking "Show transcript" at the bottom left of the videos.The course glossary can be found on the right in the resources section.To obtain CPE credits you need to complete the course and reach a score of 70% on the qualified assessment. You can navigate to the assessment by clicking on the CPE credits callout on the right.

Prerequisites

There are no prerequisites for this course
1

Visualizing distributions

In this chapter you’ll learn the value of visualizations, using real-world data on British monarchs, Australian salaries, Panamanian animals, and US cigarette consumption, to graphically represent the spread of a variable using histograms and box plots.
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2

Visualizing two variables

You’ll learn how to interpret data plots and understand core data visualization concepts such as correlation, linear relationships, and log scales. Through interactive exercises, you’ll also learn how to explore the relationship between two continuous variables using scatter plots and line plots. You'll explore data on life expectancies, technology adoption, COVID-19 coronavirus cases, and Swiss juvenile offenders. Next you’ll be introduced to two other popular visualizations—bar plots and dot plots—often used to examine the relationship between categorical variables and continuous variables. Here, you'll explore famous athletes, health survey data, and the price of a Big Mac around the world.
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3

The color and the shape

It’s time to make your insights even more impactful. Discover how you can add color and shape to make your data visualizations clearer and easier to understand, especially when you find yourself working with more than two variables at the same time. You'll explore Los Angeles home prices, technology stock prices, math anxiety, the greatest hiphop songs, scotch whisky preferences, and fatty acids in olive oil.
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4

99 problems but a plot ain't one of them

In this final chapter, you’ll learn how to identify and avoid the most common plot problems. For example, how can you avoid creating misleading or hard to interpret plots, and will your audience understand what it is you’re trying to tell them? All will be revealed! You'll explore wind directions, asthma incidence, and seats in the German Federal Council.
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Understanding Data Visualization
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*4.8
from 11,121 reviews
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  • Katherine
    4 hours ago

  • Jurgen
    9 hours ago

    great presented

  • Fei
    16 hours ago

  • Juan
    16 hours ago

  • Ahmed
    17 hours ago

  • Rehman
    18 hours ago

Katherine

"great presented"

Jurgen

Fei

FAQs

Is this course suitable for beginners?

Yes, this course is designed for users with a basic understanding of data science. You’ll learn how to choose the best visualization for your dataset, and how to interpret common plot types like histograms, scatter plots, line plots and bar plots.

Will I receive a certificate at the end of the course?

Yes, at the end of the course, you will receive a certificate of completion from DataCamp.

Who will benefit from this course?

Understanding data visualization is beneficial for a variety of professions, including data scientists, business analysts, and marketing professionals.

What types of visualizations will I learn in this course?

In this course, you'll learn how to choose the best visualizations for your dataset, and how to interpret common plot types like histograms, scatter plots, line plots, and bar plots. Additionally, you'll explore best practices for using colors and shapes in your plots.

How will this course help me with data analysis?

This course will teach you how to identify key patterns and better understand complex data sets by visualizing them. This can help you identify correlations, linear relationships, and log scales when analyzing data.

What data will be used in the course?

This course will use over 20 datasets, such as global life expectancies, Los Angeles home prices, ESPN's 100 most famous athletes, and the greatest hip-hop songs of all time.

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