Lecture schedule
Live lectures are
- Friday, Sep 6: Introduction
- Friday, Sep 13: Neural networks / Deep learning (part 1)
- Homework 1 assigned (Due Friday, Sep 27) (instructions for accessing)
- Friday, Sep 20: Neural networks / Deep learning (part 2)
- Friday, Sep 27: Reinforcement learning (part 1)
- Friday, Oct 4: Reinforcement learning (part 2)
- Homework 2 assigned (Due Friday, Oct 18) (instructions for accessing)
- Friday, Oct 11: Reinforcement learning (part 3)
- Friday, Oct 18: Bayesian modeling (part 1)
- Homework 3 assigned (Due Friday, Nov 1) (instructions for accessing)
- Friday, Oct 25: Bayesian modeling (part 2)
- Project proposal is due
- Friday, Nov 1: Model comparison and fitting
- Friday, Nov 8: Categorization
- Homework 4 assigned (Due Friday, Nov 22) (instructions for accessing)
- Friday, Nov 15: Probabilistic Graphical models
- Friday, Nov 22: Program induction and language of thought models
- Friday, Nov 29: No Class, Thanksgiving Break
- Friday, Dec 6: Information sampling and active learning
- Wednesday, Dec 11: Computational Cognitive Neuroscience, Final summary (Note special day/date due to Legislative Day)
- Final project due (Due Friday, Dec 13)
Lab schedule
Fridays 12:30-1:20PM (in person or zoom)
- Friday, Sep 6: Python and Jupyter notebooks review
- Friday, Sep 13: Introduction to PyTorch
- Friday, Sep 20: HW 1 review
- Friday, Sep 27: No lab
- Friday, Oct 4: Reinforcement learning
- Friday, Oct 11: HW 2 review
- Friday, Oct 18: Probability Review
- Friday, Oct 25: HW 3 Review
- Friday, Nov 1: No lab
- Friday, Nov 8: Collecting behavioral data online part 1
- Friday, Nov 15: Collecting behavioral data online part 2
- Friday, Nov 22: HW 4 Review
- Friday, Nov 29: No class, Thanksgiving break
- Friday, Dec 6: Final project consultation time/hackathon
- Wednesday, Dec 11 (note special date): Final project consultation time/hackathon