Data Visualization Course

Lesson 1 • Principles of Effective Visual Design

Introduces data-ink ratio, chart junk, and clarity principles. Applies design rules to improve basic chart quality.

Lesson 2 • Human Perception and Visual Encoding

Covers how the human visual system processes graphical information. Connects perceptual science to practical encoding decisions.

Lesson 3 • Core Chart Types and Their Uses

Surveys the most common chart families and the data relationships each communicates. Provides a decision framework for chart selection.

Lesson 4 • Data Types and Measurement Scales

Distinguishes nominal, ordinal, interval, and ratio data. Guides encoding choices based on data type.

Lesson 1 • Joining and Combining Datasets

Explains merging multiple data sources using keys and relationships. Enables richer visualisations from combined data.

Lesson 2 • Data Transformation for Charts

Covers pivoting, unpivoting, and reshaping data to match chart requirements. Bridges raw data structure and visualisation-ready format.

Lesson 3 • Aggregation and Summarization

Teaches grouping, counting, and summarising data to create meaningful metrics. Aggregated data forms the basis of most charts.

Lesson 4 • Understanding Data Structure

Explains tidy data principles and common data shapes. Prepares students to recognise structures that visualisation tools expect.

Lesson 1 • Colour Theory for Data Visualization

Explains sequential, diverging, and categorical colour palettes and their appropriate uses. Prevents common colour misuse in charts.

Lesson 2 • Layout and Composition Principles

Teaches grid systems, white space, and visual flow for multi-chart layouts. Applies to both single charts and full dashboards.

Lesson 3 • Applying a Consistent Visual Style

Guides creation of a reusable style guide for charts and dashboards. Consistency builds audience trust and brand recognition.

Lesson 4 • Accessibility and Colour Blindness

Covers designing for colour vision deficiencies and contrast requirements. Ensures charts are readable by all audiences.

Lesson 1 • Version Control and Reproducibility

Introduces saving, versioning, and documenting visualisation projects. Ensures work can be reproduced and audited over time.

Lesson 2 • Spreadsheet Charting Techniques

Covers chart creation, formatting, and dynamic ranges in spreadsheet software. Reinforces core concepts in a widely accessible tool.

Lesson 3 • Code-Based Visualization Basics

Introduces chart creation using a programming language and visualisation library. Builds flexibility for custom and automated outputs.

Lesson 4 • Overview of Visualization Tool Categories

Maps the landscape of drag-and-drop, code-based, and hybrid tools. Helps students choose the right tool for each context.

Lesson 1 • Small Multiples and Faceting

Explains the small multiples technique for comparing patterns across categories. Reduces the need for complex interactive filters.

Lesson 2 • Network and Relationship Visualizations

Covers node-link diagrams and adjacency matrices for relational data. Addresses layout algorithms and readability challenges.

Lesson 3 • Geospatial Visualizations

Teaches choropleth maps, point maps, and flow maps for location-based data. Covers projection choices and geographic data formats.

Lesson 4 • Part-to-Whole and Hierarchical Charts

Introduces treemaps, sunburst charts, and Sankey diagrams for hierarchical data. Extends part-to-whole concepts beyond simple pie charts.

Lesson 1 • Narrative Structure in Data Communication

Introduces story arc frameworks adapted for data presentations. Connects analytical findings to audience-relevant conclusions.

Lesson 2 • Knowing Your Audience

Covers audience analysis techniques to tailor complexity and framing. Audience alignment determines which data and charts to include.

Lesson 3 • Building a Complete Data Story

Guides assembly of multiple charts into a cohesive, persuasive narrative document. Integrates all prior storytelling skills into one deliverable.

Lesson 4 • Choosing the Right Chart for the Story

Revisits chart selection through a narrative lens rather than a data-type lens. Aligns chart choice with the message being communicated.

Lesson 1 • Performance and Load Optimisation

Addresses query efficiency, data extracts, and rendering speed for dashboards. Slow dashboards reduce adoption and trust.

Lesson 2 • Layout Patterns for Dashboards

Covers common dashboard layout templates and when to apply each. Layout choice affects how quickly users find critical information.

Lesson 3 • Dashboard Design Principles

Establishes purpose, audience, and scope before any visual design begins. A clear brief prevents scope creep and redesign cycles.

Lesson 4 • Filters, Parameters, and Controls

Teaches adding interactive filters, date pickers, and parameter controls. Interactivity lets users explore data without needing technical skills.

Lesson 1 • Defining a Visualisation Strategy

Connects visualisation decisions to organisational goals and data maturity. Strategy ensures visualisation investment delivers measurable value.

Lesson 2 • Standards, Templates, and Style Guides

Covers creating and enforcing organisation-wide chart standards. Consistency reduces cognitive load across all stakeholders.

Lesson 3 • Data Governance and Visualisation Ethics

Addresses data accuracy, source transparency, and misleading chart practices. Ethical visualisation builds long-term credibility.

Lesson 4 • Measuring Visualisation Effectiveness

Introduces metrics for evaluating whether dashboards and reports drive decisions. Measurement justifies continued investment in visualisation.