Resources
Starting points for AI literacy
A growing library of resources for learning about AI and using it well as a student. Entries marked as samples are placeholders that will be replaced with verified resources.
This library is under active curation. Sample entries below show the kinds of resources we're gathering; they'll be replaced with verified links as our resource team reviews them. SAIL@UofT does not endorse specific commercial tools.
AI fundamentals
What is a large language model?
SampleSample entry — a plain-language introduction to how modern AI models work will be linked here.
Key AI terms explained
SampleSample entry — a glossary covering prompts, tokens, hallucinations, fine-tuning, and more.
Academic use
Using AI within course policies
SampleSample entry — guidance on checking each course's AI policy and citing AI assistance appropriately.
Study workflows with AI
SampleSample entry — practical patterns for summarizing readings, generating practice questions, and self-testing.
Research and writing
Literature discovery with AI tools
SampleSample entry — approaches for finding and triaging papers while verifying sources independently.
Editing and feedback, not ghostwriting
SampleSample entry — how to use AI for structure and clarity feedback while keeping the writing your own.
Productivity and organization
Planning a semester with AI assistance
SampleSample entry — templates for breaking down assignments and building realistic schedules.
Responsible AI
Limitations and failure modes
SampleSample entry — understanding hallucination, bias, and when not to rely on AI output.
Privacy basics for AI tools
SampleSample entry — what to consider before sharing personal or course data with AI services.
Careers and professional development
AI skills employers ask about
SampleSample entry — an overview of AI-related competencies appearing in internship and new-grad postings.
Have a resource worth sharing? Let us know.