COURSE OBJECTIVE:
• Learn chart types and when to use them.
• Evaluate generative AI tools for data visualization.
• Use visual design elements to create effective data visualizations.
• Encode data with color meaningfully and follow accessibility guidelines.
• Evaluate data quality through data collection, cleaning, and compiling stages.
• Avoid misleading data visualizations.
• Balance making an argument with representing data accurately.
• Tailor data visualizations to specific audiences.
• Address barriers that audiences face in understanding or taking action.
• Ethically communicate data through data storytelling.

TARGET AUDIENCE:
Data analysts, data visualization practitioners, and technical AI users who want to create more compelling arguments with their data, and learn how to combine data, text, and visualizations to craft a data story.

COURSE PREREQUISITES:
• Familiarity with a data visualization tool, such as Tableau or PowerBI
• Basic familiarity with data visualization

COURSE CONTENT:
1- Introduction to Data Storytelling

• What is Data Visualization?
• Types of Charts and Choosing the Right Visualization
• Generative AI Tools for Data Visualization
2- Visual Design Theory

• Elements of Visual Design
• Limitations of Generative AI in Design
• Grouping and Highlighting Data to Build and Argument
3- Analyzing Misleading Visualizations

• Data Quality and Collection
• Accuracy in Scale and Context
• Reporting and Misrepresentation of Statistics
4- Data Storytelling

• Introduction to Data Storytelling
• Key Elements of a Compelling Data Story
• Anticipating Audience Barriers
5- Data for Your Audience

• Tailoring Insights to the Audience
• Structure of a Compelling Data Story
• Ethics and Truth in Data Storytelling
• Reducing Friction for the Audience.

FOLLOW ON COURSES:
Not available. Please contact.