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Program Description

This not-for-credit microcredential introduces essential tools and concepts used in genetic association studies, with a focus on developing practical skills for analyzing complex genomic datasets using modern computational methods. As genomics continues to transform biomedical research, health sciences, and biotechnology, this microcredential supports learners in building relevant skills aligned with current data-intensive research and industry practices.

Cancellation Policy

Participants may withdraw at any time by emailing courses.dsi@utoronto.ca.

Refunds are available only if the request is received at least twenty-five (25) business days before the start date. All refunds are subject to a $150 CAD administrative fee. No refunds will be issued after the deadline. Requests must include the original payment receipt.

Prerequisites

  • Some background understanding of genetics via a post-secondary course in biology, genetics, or similar
  • A basic understanding of R. Participants should be able to:
    • Clean and summarize data
    • Make basic plots
    • Troubleshoot simple errors
    • Run R scripts and import simple datasets
  • English Language Proficiency
  • Participants should be familiar with key concepts in statistical inference, including:
    • Elementary probability and statistical methods
    • Distributions of basic random variables (e.g., binomial, normal)
    • Likelihood-based methods, including estimation and hypothesis testing
    • Basic regression techniques (e.g., linear and logistic regression)
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