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AI for All: Essentials for Educators

SELF-PACED PROFESSIONAL LEARNING

The Course

Free, self-paced modules to cultivate your pedagogical agency and tend a thriving digital classroom ecosystem. Plant the seeds of AI basics—how models learn, work, and sprout in daily tools—before branching into critical realities like data privacy, ethical guardrails, and Indigenous data sovereignty. From root-level safety to cross-curricular growth, gain the homegrown confidence to nurture student AI literacy and lead ethical adoption in your learning community.
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A smiling person holds out a hand as two yellow birds come to land, in an illustrated garden.

Chapter 1 What is AI?

The foundations: what artificial intelligence actually is, how data, computing power and infrastructure make it work, how generative and agentic systems differ, and why AI literacy matters for educators and their students.
TopicsTasks
  1. I. Defining Core Concepts0/4
  2. II. Inside the AI Engine0/5
  3. III. From Chatbots to Agents0/5
  4. IV. So What for Classrooms?0/3
Start module
Illustrated garden: a pink planter with a screen face, cabled to a server rack, beside a smiling aubergine.

Chapter 2 How AI Learns & Makes Decisions

How AI learns and makes decisions: the different ways models learn from data, how training data shapes what they recognize and what they miss, how patterns become predictions, and how those predictions come to influence what happens next.
TopicsTasks
  1. I. Meet the Model: Data, Patterns and Training0/7
  2. II. Data Shapes What AI Learns0/8
  3. III. From Patterns to Predictions0/7
  4. IV. From Predictions to Decisions0/7
Start module
Illustrated garden: a person in a virtual-reality headset stands in front of a geodesic greenhouse dome, beside a tomato plant.

Chapter 3 Risks and Realities

The risks and responsibilities that come with AI in schools: algorithmic bias, hallucinations, deepfakes and AI companions, the cost of cognitive offloading, Indigenous Data Sovereignty and ethical guardrails, and academic integrity and copyright.
TopicsTasks
  1. I. Navigating AI’s Ethical Risks0/5
  2. II. Impact of Cognitive Offloading0/4
  3. III. Indigenous Data Sovereignty & Ethical Guardrails0/7
  4. IV. Academic Integrity & Copyright0/11
Start module
Two students share a tablet in an illustrated garden, with an orange fruit character perched on a server cabinet behind them.

Chapter 4 Daily Practice & Classroom Integration

AI in the working week: lightening administrative load, differentiating learning and adapting instruction, and designing learning experiences with AI rather than around it.
Topics
  1. I. Supporting Teacher Workflow & Administrative Tasks
  2. II. Differentiating Learning and Adapting Instruction
  3. III. Designing Learning with AI
Coming Soon
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Chapter 5 Student AI Literacy & Future Readiness

Preparing students for what comes next: building AI literacy across grade levels, the career pathways opening in a changing digital workforce, and how this connects to Canada’s Skills for Success.
Topics
  1. I. Fostering Student AI Literacy Across Grade Levels
  2. II. Career Pathways and the Evolving Digital Workforce
  3. III. Canada Skills for Success
Coming Soon
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Chapter 6 Professional Leadership and Agency

Leadership beyond the classroom: Canada’s own AI story, the international competency frameworks shaping practice, and the habits that keep educators adaptable as the technology changes.
Topics
  1. I. Our Home-Grown AI Story
  2. II. Understanding International AI Competency Frameworks
  3. III. Developing Lifelong Adaptability for an Evolving Tech Ecosystem
Coming Soon