Data & Analytics Data Visualization

Data Visualization Concepts

Learn how to turn data into clear, credible, and compelling visuals with Professor Peter Lambert

Quick Course Facts

Self-paced, Online, Lessons

Videos and/or Narrated Presentations

5.7

Approximate Hours of Course Media

About the Data Visualization Concepts Course

Data Visualization Concepts is a practical Data & Analytics course that teaches you how to create visuals people can understand quickly and trust. Learn how to turn data into clear, credible, and compelling visuals with Professor Peter Lambert, and build the confidence to present information with precision and purpose.

Master Data Visualization Concepts For Clearer Data & Analytics Communication

Learn how to choose the right chart for each question, dataset, and audience
Build stronger visuals using proven principles of perception, encoding, layout, and colour
Improve your ability to explain trends, comparisons, relationships, and distributions clearly
Create dashboards, reports, and data stories that support better decisions

Data Visualization Concepts gives you a strong foundation in visual communication for modern Data & Analytics work.

Across 17 focused lessons, you will explore why visualization matters, how people read visuals, and how to match chart types to different data types and structures. The course walks through bars, line charts, scatter plots, part-to-whole displays, and distribution views, so you can select the most effective format for the message you want to communicate.

You will also learn the design choices that make visuals more effective, including visual encoding, colour use, labeling, annotation, hierarchy, and layout. Just as importantly, you will study how to avoid misleading visuals by paying attention to scale, distortion, cherry-picking, and context. These skills help you create work that is both persuasive and responsible.

As you progress, you will develop the ability to build dashboards and reports that combine multiple views into a coherent story. You will also practice visual storytelling for decisions and learn a practical framework for reviewing and refining your own work. By the end of this course, you will be able to communicate with greater clarity, turn raw data into meaningful insight, and present Data & Analytics visuals with more confidence and credibility.

Course Lessons

Full lesson breakdown

Lessons are organized by topic area and each includes descriptive copy for search visibility and student clarity.

Foundations of visual communication

1 lesson

Lesson 1: Why Data Visualization Matters

18 min Preview

Data visualization matters because it turns raw numbers into meaning people can understand quickly. In this lesson, learners see how effective visuals reduce cognitive load, reveal patterns, support d…

Perception, attention, and cognition

1 lesson

Lesson 2: How People Read Visuals

20 min

This lesson explains how people actually read visuals : what the eye notices first, how the brain groups information, and why some charts feel instantly clear while others feel confusing or misleading…

Matching chart type to question and data

1 lesson

Lesson 3: Choosing the Right Chart

22 min

Choosing the right chart starts with a simple question: what do you want the audience to understand? In this lesson, Professor Peter Lambert shows how to match common chart types to the most common ta…

Categorical, numerical, temporal, and spatial data

1 lesson

Lesson 4: Understanding Data Types and Structures

18 min

Every chart choice starts with one question: what kind of data are you working with? In this lesson, Professor Peter Lambert explains the four core data types used in visualization—categorical, numeri…

Marks, channels, and their effects

1 lesson

Lesson 5: Visual Encoding Basics

22 min

This lesson introduces the building blocks of visual encoding: marks and channels . Students learn how dots, lines, bars, areas, and text become meaningful when paired with position, length, color, si…

Bars, dot plots, and ranked views

1 lesson

Lesson 6: Comparing Values Clearly

20 min

This lesson focuses on one core question: how do you compare values so people can see the differences quickly and accurately? You will learn when bars are the best choice, when dot plots communicate m…

Line charts, trends, and time series thinking

1 lesson

Lesson 7: Showing Change Over Time

20 min

In this lesson, Professor Peter Lambert shows how to choose and build line charts that make change over time easy to see and hard to misread. You will learn when a line chart is the right choice, how …

Spread, shape, outliers, and variability

1 lesson

Lesson 8: Displaying Distributions

22 min

Distributions are one of the most important ideas in data visualization because they show not just where values sit, but how they are spread, clustered, and shaped. In this lesson, you will learn how …

Scatter plots and multivariate insight

1 lesson

Lesson 9: Understanding Relationships and Correlation

21 min

This lesson explains how scatter plots reveal relationships between two variables and how to judge whether a pattern is meaningful, weak, or misleading. You will learn to read direction, strength, and…

Composition, proportion, and context

1 lesson

Lesson 10: Visualizing Part-to-Whole

18 min

This lesson explains how to show part-to-whole relationships clearly and credibly, so audiences can understand how categories contribute to a total without being misled by scale or design. You will le…

Using colour for emphasis, grouping, and accessibility

1 lesson

Lesson 11: Colour With Purpose

20 min

This lesson shows how colour can make a chart clearer, not just prettier. You’ll learn when to use colour to draw attention to a key point, when to use it to separate groups, and when to keep a palett…

Helping viewers interpret the message

1 lesson

Lesson 12: Labels, Annotations, and Explanatory Text

19 min

Labels, annotations, and explanatory text help viewers understand what a chart is saying without forcing them to guess. In this lesson, you will learn when to label directly on the visual, when to rel…

Arranging information for quick understanding

1 lesson

Lesson 13: Layout, Hierarchy, and Reading Order

18 min

This lesson explains how layout, hierarchy, and reading order shape the way people interpret a chart, dashboard, or slide. Students learn how to guide attention with position, size, contrast, spacing,…

Scale, distortion, cherry-picking, and context

1 lesson

Lesson 14: Avoiding Misleading Visuals

23 min

This lesson shows how visuals can mislead even when the underlying data are accurate. You will learn how scale choices, truncated axes, distorted proportions, and selective data use can change the sto…

Combining multiple visuals into a coherent view

1 lesson

Lesson 15: Designing Dashboards and Reports

22 min

Designing effective dashboards and reports means combining multiple visuals into a single view without creating confusion. In this lesson, you will learn how to choose the right mix of charts, arrange…

Building a narrative around evidence

1 lesson

Lesson 16: Visual Storytelling for Decisions

20 min

Visual storytelling is the skill of turning charts into decisions. In this lesson, you will learn how to frame data around a clear question, choose the right evidence, and arrange visuals so the audie…

A practical framework for improvement

1 lesson

Lesson 17: Reviewing, Refining, and Critiquing Visuals

18 min

This lesson gives you a practical framework for improving data visuals before they are published or presented. You will learn how to review charts for clarity, accuracy, and audience fit; how to criti…

About Your Instructor

Professor Peter Lambert

Professor Peter Lambert guides this AI-built Virversity course with a clear, practical teaching style.