# Data 102: Data, Inference, and Decisions

UC Berkeley, Spring 2024

### Alexander StrangInstructor

alexstrang

### Ramesh SridharanInstructor

ramesh_s

## Week 14

- Lab 11 has been released. It is extra credit, and it is due Sunday, April 21st at 11:59 PM.
- Vitamin 12 is due Sunday, April 21st at 11:59 PM.

## Schedule

## Week 1: Binary Decisions

- Jan 16
**Lecture**1. Binary Decision-Making I- Jan 18
**Lecture**2. Binary Decision-Making II**Vitamin**Vitamin 1 (due Jan 21 at 11:59 PM)- Jan 19
**Homework**Homework 1 (due Feb 2 at**5 PM**)

## Week 2: Multiple Testing

- Jan 22
**Lab**Lab 1: Review and Warm-Up (due Jan 24 at**5 PM**)- Jan 23
**Lecture**3. \(p\)-Values and Multiple Hypothesis Testing- Jan 24
**Discussion**Discussion 1 (Answers)- Jan 25
**Lecture**4. False Discovery Rate Control & ROC Curves**Vitamin**Vitamin 2 (due Jan 28 at 11:59 PM)

## Week 3: The Bayesian Framework

- Jan 29
**Lab**Lab 2: Testing (due Jan 31 at**5 PM**)- Jan 30
**Lecture**5. Frequentist vs. Bayesian Decision-Making- Jan 31
**Discussion**Discussion 2 (Answers)- Feb 1
**Lecture**6. Introduction to Frequentist and Bayesian Modeling**Vitamin**Vitamin 3 (due Feb 4 at 11:59 PM)- Feb 2
**Homework**Homework 2 (due Feb 16 at**5 PM**)

## Week 4: Graphical Models and Sampling

- Feb 5
**Lab**Lab 3: Loss and Risk (due Feb 7 at**5 PM**)- Feb 6
**Lecture**7. Bayesian Hierarchical Models- Feb 7
**Discussion**Discussion 3 (Answers)- Feb 8
**Lecture**8. Bayesian Inference with Sampling**Vitamin**Vitamin 4 (due Feb 11 at 11:59 PM)

## Week 5: Sampling and Generalized Linear Models

- Feb 12
**Lab**Lab 4: Graphical Models (due Feb 14 at**5 PM**)- Feb 13
**Lecture**9. Rejection Sampling and Gibbs Sampling- Feb 14
**Discussion**Discussion 4 (Answers)- Feb 15
**Lecture**10. Regression and GLMs**Vitamin**Vitamin 5 (due Feb 18 at 11:59 PM)

## Week 6: Generalized Linear Models

- Feb 19
**Lab**Lab 5: Sampling & GLMs (due Feb 23 at**5 PM**)- Feb 20
**Lecture**11. Model Checking for GLMs- Feb 21
**Discussion**Discussion 5 (Answers)- Feb 22
**Lecture**12. Uncertainty Quantification for GLMs**Vitamin**Vitamin 6 (due Feb 25 at 11:59 PM)- Feb 23
**Homework**Homework 3 (due 8 Mar at**5 PM**)

## Week 7: Nonparametric Methods

- Feb 26
**Review Session**Slides- Feb 27
**Midterm**Midterm I- Feb 29
**Lecture**13. Nonparametric Methods and Neural Networks

## Week 8: Neural Networks and Causal Inference

- Mar 4
**Lab**Lab 6: GLMs and the Bootstrap (due Mar 6 at**5 PM**)- Mar 5
**Lecture**14. Neural Networks and Interpretability- Mar 6
**Discussion**Discussion 6 (Answers)- Mar 7
**Lecture**15. Causal Inference I: Association and Causation**Vitamin**Vitamin 7 (due Mar 10 11:59 PM)- Mar 8
**Homework**Homework 4 (due Mar 22 at**5 PM**)

## Week 9: Causal Inference

- Mar 11
**Lab**Lab 7: Nonparametric Methods (due Mar 13 at**5 PM**)- Mar 12
**Lecture**16. Causal Inference II: Randomized Experiments- Mar 13
**Discussion**Discussion 7 (Answers)- Mar 14
**Lecture**17. Causal Inference III: Observational Studies**Vitamin**Vitamin 8 (due Mar 17 11:59 PM)

## Week 10: Concentration and Bandits

- Mar 18
**Lab**Lab 8: Unconfoundedness (due Mar 20 at**5 PM**)- Mar 19
**Lecture**18. Concentration Inequalities- Mar 20
**Discussion**Discussion 8 (Answers)- Mar 21
**Lecture**19. Bandits I**Vitamin**Vitamin 9 (due Mar 31 11:59 PM)- Mar 22
**Homework**Homework 5 (due Apr 12 at**5 PM**)

## Week 11: Spring Break

- Mar 26
*Spring Break*- Mar 28
*Spring Break*

## Week 12: Bandits and Reinforcement Learning

- Apr 1
**Lab**Lab 9: Instrumental variable (due Apr 3 at**5 PM**)- Apr 2
**Lecture**20. Bandits II- Apr 3
**Discussion**Discussion 9 (Answers)- Apr 4
**Lecture**21. Reinforcement Learning I**Vitamin**Vitamin 10 (due Apr 7 11:59 PM)

## Week 13: Reinforcement Learning

- Apr 8
**Lab**Lab 10: Bandits (due Apr 10 at**5 PM**)- Apr 9
**Lecture**22. Reinforcement Learning II- Apr 10
**Discussion**Discussion 10(Answers)- Apr 11
**Lecture**23. Monte Carlo Tree Search**Vitamin**Vitamin 11 (due Apr 15 11:59 PM)

## Week 14: Midterm II and Privacy

- Apr 16
**Midterm**Midterm II- Apr 17
**Lab**Lab 11: Reinforcement Learning (due Apr 21 at**11:59 PM**)- Apr 18
**Lecture**24. Privacy in Machine Learning**Vitamin**Vitamin 12 (due Apr 21 11:59 PM)- Apr 19
**Homework**Homework 6 (due Apr 26 at**5 PM**)

## Week 15: Wrap-Up

- Apr 22
**Lab**Lab 12: Differential Privacy (due Apr 24 at**5 PM**)- Apr 23
**Lecture**25. Case Studies: Robustness and Generalization- Apr 24
**Discussion**Discussion 11 (Answers)- Apr 25
**Lecture**26. Course Wrap-Up

## Week 16: RRR Week

- Apr 30
*RRR Week*- May 3
*RRR Week*

## Week 17: Finals

- May 7
*Finals Week*- May 9
*Finals Week*