UAlberta

Modelling, Data & Predictions Curriculum & Career Navigator

Core Required Inference / Stats Machine Learning Practicum Capstone
STAT 566: Applied Regression & Generalized Linear Models
Explores GLM theory, quasi-likelihood, deviance analysis, and high-dimensional diagnostic regression. Essential for statistical inference foundation.
Credits: 3.0 Workload: 4/5 (Heavy coding + theory) Term Recommended: Fall Year 1
Personalized Study Plan (3 Terms / 18 Credits) ✓ Full Degree Plan Complete (100%)
Term 1: Fall Year 1 (6 Credits)
Term 2: Winter Year 1 (6 Credits)
Term 3: Fall Year 2 (6 Credits)

Saved study-plan score arithmetic

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Saved catalog courses carry three credits and export total is selected course count times three. Hypothetical five versus eight courses gives fifteen versus twenty-four credits. Bars share zero at twenty pixels per credit. Actual program requirements and course availability are not independently verified. Source production score adds twelve when cloud course is selected and otherwise subtracts four. Holding a hypothetical base eighty and other course adjustments aside gives ninety-two versus seventy-six. Bars compare at six pixels per point. Difference sixteen reflects assigned weights rather than demonstrated competence. Hypothetical production base ninety-five plus twelve cloud bonus plus four project-course bonus totals one hundred eleven. Source upper clamp caps ninety-nine. Bars compare raw and clamped totals at five pixels per point. These readiness percentages are heuristic. Complete native curriculum-plan JSON/reset preserved, credentials and instructional outcomes unproved.

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