CS-301Fall 2026 · Week 6 of 12

Machine Learning Foundations

From linear models to neural networks — theory, maths and hands-on Python labs.

DRTA
Dr. Daniel Reyes · 2 teaching assistants · 186 learners
64%
23 of 36 done
Continue: 6.3 Gradient descent
Grades Discussions
Participants
186 enrolled · 3 staff
NameRoleGroupProgressLast access
Competency map
Proficiency rated from quiz and assignment evidence
Evidence of learning
Linked to course outcomes
Proficient: Linear models
Quiz 3 — 92% · rated by Dr. Reyes
Proficient: Model evaluation
Lab 4 — 88/100
In progress: Neural networks
Needs Lab 6 + Week 6 quiz
Not started: Regularisation
Unlocks in Week 8
My notes
Private notes and video bookmarks from this course
12:04
Chain rule: multiply local gradients going backwards — draw the computational graph first.
6.2 Backpropagation
03:41
Learning rate too high → loss oscillates. Try 1e-3 then scale.
6.1 Gradient descent
Text
Ask in office hours: why does Adam use bias correction?
Week 5