Course Timeline

Week 1

Mar 31: Lec 1: Introduction & Logistics; slides | scribe notes
Apr 2: Lec 2: Machine Learning Basics; slides

Week 2

Apr 7: Lec 3: ML/DL basics (II)
Apr 9: Lec 4: ML/DL basics (III)

Week 3

Apr 14: Lec 5: Robustness – overview + attack
Apr 16: Lec 6: Robustness attacks (vision) (I)

Week 4

Apr 21: Lec 7: Robustness attacks (vision) (II)
Apr 23: Lec 8: Robustness – LLMs

Week 5

Apr 28: Lec 9: Robustness Verification (I)
Apr 30: Lec 10: Robustness Verification (II)

Week 6

May 5: Lec 11: Interpretability overview
May 7: Lec 12: No Class

Week 7

May 12: Lec 13: Interpretability – post-hoc interpretability tools (I)
May 14: Lec 14: Interpretability – post-hoc interpretability tools (II)

Week 8

May 19: Lec 15: Interpretability – learning interpretable NN models (I)
May 21: Lec 16: Interpretability – learning interpretable NN models (II)

Week 9

May 26: Lec 17: Interpretability – evaluation (I)
May 28: Lec 18: Interpretability – evaluation (II)

Week 10

Jun 02: Lec 19: Open challenges (I)
Jun 04: Lec 20: Open challenges (II)

Week 11 (Finals Week)

Jun 09: Final presentation