• Thinking Slowly: Robot Card Sorter

    How learning to think slowly is the first step in computational reasoning.

  • DIDM01

    Draft Course Plan for Data Informed Decision Making (2023)

  • Visualizing the Rod Cutting Algorithm

  • Eye Rests

  • Frost and Decision Theory I

  • Frost and Decision Theory

  • BI Info Night Fall 2022

  • Regression Continuity Design

  • Propensity Score Video (5m)

  • ICS212 Statistical Matching - Balance Assessment

  • R's Match Library Documentation

    Slides to walk students through Match function in R as used in a workbook to follow in LP19 of ICS212

  • ICS212-CI-based-on-assignment

    Slides for in-class activity reviewing pp 39-45 of Rubin's (2003) Basic concepts of statistical inference for causal effects in experiments and observational studies

  • ICS212 Assignment 3 Thinking Guide

    A guided tour of how one might start to think about interview data for assignment 3, location-based-assignment.

  • Aspirin

    Three slides based on Rubin Basic Concepts of Statistical Inference for Causal Effects in Experiments and Observational Studies

  • LP16 Lalonde Article

  • Stochastic and Systematic

  • Selection Bias

  • LP14:PropensityScores

  • LP14:We Both Have Headaches Discussion

  • Copy of Copy of deck

  • SimplifiedNotationCausalInferenceLIVE

  • Copy of deck

  • Math of Causal Inference

  • Dataverse Workflow

  • deck

  • SRI

  • INF313 F21W22

  • 453 Week XII

  • AI Alignment 313W22

  • How do machines learn? (313 2022)

  • How Do Machines See?

  • APIs in Everyday Life (1339)

  • Patterns INF113F21W22

  • PID in NetLogo

  • Pitch and Catch

  • deck

  • Automation INF313F21W22

  • Archive copy of How do machines see?

  • CT Problems & Solutions

  • deck

  • Sierpinski Triangle

  • Repetition-Recursive-Tree

    Module for "Problem Solving with Repetition"

  • Repetition-Fibonacci

    Module for "Problem Solving with Repetition"

  • Bubble Sort

  • The Bachelor of Information Program at the University of Toronto Faculty of Information

    The BI program at UofT's Faculty of Information is a unique second entry bachelors degree that combines technology, design, and critical social analysis.

  • Repetition INF313F21W22

  • Info Jigs INF313F21W22

  • Logic inf313f21w22

  • deck

  • Flow and Modularity (inf313F21)