How AI works
Lessons 01–02L · 01
AI Literacy as a Public Health Skill: Machine Learning and Neural NetworksThe lesson sets out why skilled use of AI is becoming a core public health competency, defines artificial intelligence, machine learning and deep learning, explains how a neural network learns, and traces the history of the field to the generative turn.
L · 02
How Large Language Models and AI Agents WorkThe lesson explains tokens, embeddings and next-token prediction, how a pretrained model becomes an assistant, how reasoning, retrieval and tools extend it, and how AI agents plan, act and use other software.
Working with AI
Lessons 03–04L · 03
Working with AI: Prompting, Context and VerificationStudents map the uneven strengths of AI across tasks, write structured prompts with context and examples, apply a verification routine scaled to the stakes of a task, and classify information before it enters any tool.
L · 04
AI for Learning and StudyThe lesson reviews randomized evidence that AI can strengthen or weaken learning and teaches tutoring techniques, AI-assisted reading of difficult material and a study routine that builds understanding.
AI in academic work
Lessons 05–08L · 05
AI-Assisted Literature Searching and ReadingStudents use AI research tools to scope a topic, draft and test a search, extract findings from papers and audit AI-generated citations, with pointers to the systematic review methods of HSCI 241.
L · 06
AI-Assisted Academic and Professional WritingThe lesson applies AI across the writing process, from outlining and feedback to plain-language and translated materials, and covers authorship, disclosure and the limits of AI-text detectors.
L · 07
AI as a Thinking Partner: Generating and Testing IdeasStudents use AI to generate and test ideas, counter sycophancy, stress-test research questions, logic models and causal diagrams, and prepare for engagement with interest holders.
L · 08
AI for Data Analysis and Coding in RThe lesson shows how AI coding assistants help beginners write and understand R code, how to check an AI-written analysis with real survey data, and how health data governance applies to AI tools.
AI in public health practice
Lessons 09–10L · 09
AI in Public Health PracticeStudents examine AI in surveillance, prediction and decision support, language models in health care and communication, and the everyday work of public health teams under Canadian and British Columbian rules.
L · 10
Responsible Adoption and Continued LearningThe lesson considers equity, bias and Indigenous data sovereignty, summarizes the governance and environmental costs of AI, and sets out a personal workflow and a method for continued learning as tools change.