STA314H1 - Statistical Methods for Machine Learning I
Course: STA314H1 (Statistical Methods for Machine Learning I) in STA department at University of Toronto.
Credit Hours: 36 • Academic Level: third-year undergraduate course
Course Requirements: Requires 19 prerequisite courses
Prerequisite Chain Depth: 6 levels of foundational courses required
Future Opportunities: Unlocks 5 advanced courses for further study
Interdisciplinary Requirements: Prerequisites span 3 different departments
Course Type: Core pathway course - critical for degree progression
Part of the STA curriculum at University of Toronto, helping students progress through degree requirements.
Prerequisites for STA314H1
- STA302H1
- STA302H5
- MAT223H1
- MAT224H1
- MAT240H1
- MAT223H5
- MAT240H5
- MAT224H5
- MAT235Y1
- MAT237Y1
- MAT257Y1
- One of: MAT223H1, MAT224H1, MAT240H1, MAT223H5, MAT240H5, MAT224H5
- One of: MAT232H5, MAT236H5
- One of: MAT233H5, MAT236H5
- One of: STA302H1, STA302H5
- One of: CSC108H1, CSC110Y1, CSC120H1, CSC148H1, CSC148H5, CSC108H5
- One of: MAT235Y1, MAT237Y1, MAT257Y1
- One of: MAT232H5, MAT236H5
- One of: MAT233H5, MAT236H5
Courses unlocked by STA314H1
Academic Planning at University of Toronto
Students planning STA314H1 at University of Toronto should complete 19 prerequisites before enrollment.
Course Sequence: This course requires a 6-level prerequisite chain, requiring careful multi-semester planning for optimal progression.
Future Pathways: Completing STA314H1 enables enrollment in 5 advanced courses for further study
This third-year course at University of Toronto integrates into structured degree pathways for STA programs, supporting timely graduation and academic progression.