Fundamentals of Data Visualization

Fundamentals of Data Visualization

This course is part of Vital Skills for Data Science Specialization

Instructor: Danielle Szafir

What you'll learn

Develop a toolkit for exploring and communicating complex data using visualization
Produce basic data visualizations using a chosen dataset
Compare methods for visualizing data and understand how these methods may guide users towards different conclusions
Evaluate how effectively a visualization conveys target data

Skills you'll gain

Data Visualization

Details to know

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Assessments

3 assignments

Taught in English

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This course is part of the Vital Skills for Data Science Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

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There are 3 modules in this course

Data is everywhere. Charts, graphs, and other types of information visualizations help people to make sense of this data. This course explores the design, development, and evaluation of such information visualizations. By combining aspects of design, computer graphics, HCI, and data science, you will gain hands-on experience with creating visualizations, using exploratory tools, and architecting data narratives. Topics include user-centered design, web-based visualization, data cognition and perception, and design evaluation.

This course can be taken for academic credit as part of CU Boulder’s MS in Data Science or MS in Computer Science degrees offered on the Coursera platform. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Data Science: https://www.coursera.org/degrees/master-of-science-data-science-boulder MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder

In this module, you will learn the foundations of visualization design. You will walk through the key components of a visualization, how we effectively represent data using channels like color, size, and position, and some ground rules for honest and effective visualization. You will also gain preliminary exposure to Altair, a Python library for rapidly generating interactive visualizations. Each week will also include either two readings or one reading and one notebook activity.

What's included

13 videos14 readings1 assignment2 discussion prompts2 ungraded labs

13 videosTotal 156 minutes

Course Overview3 minutesPreview module
Why Visualization?13 minutes
A Grammar of Graphics10 minutes
Introduction to Altair7 minutes
Hands on with Altair - Part 113 minutes
Hands on with Altair - Part 211 minutes
Mapping Basics11 minutes
Mapping Tips11 minutes
Color17 minutes
Rules of Thumb16 minutes
Introduction to Interaction12 minutes
Interactions Part 113 minutes
Interactions Part 212 minutes

14 readingsTotal 140 minutes

Earn Academic Credit for your Work! 10 minutes
Course Support10 minutes
Assessment Expectations10 minutes
A Tour Through the Visualization Zoo10 minutes
Data Humanism: The Revolutionary Future of Data Visualization10 minutes
Vega-Lite: A Grammar of Interactive Graphics10 minutes
Workshop Overview of Altair Basics10 minutes
Exploratory Data Visualization with Altair10 minutes
The Structure of the Information Visualization Design Space10 minutes
Extra Resources: Data Types, Graphical Marks, and Visual Encoding Channels10 minutes
The Good, the Bad, and the Biased10 minutes
Extra Resources: WTF Visualizations10 minutes
Extra Resources: Ethical Dimensions of Visualization Research10 minutes
Toward a Deeper Understanding of the Role of Interaction in Information Visualization10 minutes

1 assignmentTotal 30 minutes

Week 1 Quiz30 minutes

2 discussion promptsTotal 20 minutes

Introduce Yourself10 minutes
Visualization Project Part 1: Finding your Data10 minutes

2 ungraded labsTotal 120 minutes

Introduction to Altair60 minutes
Implementing Interaction in Altair 60 minutes

In this module, you will learn how to choose the right visualization for a given scenario. You will learn how to reason about the different kinds of questions people ask with visualization and, how to align your design with that task. The module will cover basics of task analysis, methods for task elicitation, and foundational knowledge of visual perception for design. Each week will also include two external readings or one reading and one notebook activity.

What's included

9 videos7 readings1 assignment1 discussion prompt

9 videosTotal 110 minutes

Visualization Tasks12 minutesPreview module
Task Elicitation15 minutes
Basic Design Methods11 minutes
Design Studies17 minutes
Perception Overview5 minutes
Preattention13 minutes
Attention & Search14 minutes
Uncertainty10 minutes
Ethical Questions8 minutes

7 readingsTotal 70 minutes

A Design Space of Visualization Tasks10 minutes
Design Study Methodology: Reflections from the Trenches and the Stacks10 minutes
Overview: The Design, Adoption, and Analysis of a Visual Document Mining Tool for Investigative Journalists10 minutes
Criteria for Rigor in Visualization Design Study10 minutes
On the Prospects for a Science of Visualization10 minutes
Attention and Visual Memory in Visualization and Computer Graphics10 minutes
Why Authors Don't Visualize Uncertainty10 minutes

1 assignmentTotal 30 minutes

Week 2 Quiz30 minutes

1 discussion promptTotal 10 minutes

Visualization Project Part 2: Sketching your Data10 minutes

In this module, you will learn how to assess the effectiveness of your visualization. You will learn both qualitative and quantitative approaches for evaluating visualizations as well as how to isolate key elements for assessment and iteration. The module will cover basics of insight-based evaluation, interview studies, and experimental design and analysis. Each week will also include two external readings or one reading and one notebook activity.