Self AssessmentFree
21 Key Traits of Data & AI Literacy
Assess Your Data & AI Literacy Across 21 Key Traits
Discover and self-assess the 21 key traits that define data and AI literacy, organized into four categories: Knowledge, Skills, Attitudes, and Behaviors. Score yourself on proficiency and importance for each trait to create a personalized growth plan.
Ben Jones2h 0m0 lessons
About this course
Growing in data & AI literacy is one of the most important and strategic development paths we can embark upon. This course introduces the 21 key traits that highly fluent individuals possess, organized into four categories: - **Knowledge** (5 traits): Basic Elements of Data, Data Storage Methods, Data Analysis Principles, Data Visualization Rules of Thumb, AI Systems & Capabilities - **Skills** (6 traits): Reading & Interpreting Data, Evaluating AI Outputs, Cleaning & Preparing Data, Exploring & Analyzing Data, Visualizing Data, Communicating Data - **Attitudes** (5 traits): Inclusive, Critical yet Open-Minded, Alert, Ethical, Adaptable - **Behaviors** (5 traits): Resourceful Utilization of Data & AI, Continuous Improvement of Data & AI Systems, Effective Advocacy for Responsible Use, Enthusiastic Promotion of Literacy, Effective Integration of AI Tools For each trait, you'll assess your current **proficiency** (0-4) and the trait's **importance** (0-4) to your current role. Your scores are plotted on an interactive Trait Development Grid that identifies your Growth Opportunities, Sweet Spot, areas to Flex or Coach Others, and traits you can Leave Alone for now. The course includes video lessons, expert quotes from Alberto Cairo, RJ Andrews, Giorgia Lupi, and Cheryl Phillips, case studies, and a companion eBook.
What you'll cover
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