Data 140 · Probability for Data Science

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1/14 - Welcome to Data 140!

Week 0 Overview

Getting Started

Before January 19

Prerequisites

Week 1

Introduction

1/19-1/24

Week 2

Symmetry and Random Counts

1/25-1/31

Week 3

Poissonization

2/1-2/7

Week 4

Expectation

2/8-2/14

Week 5

Conditioning and Markov Chains

2/15-2/21

Week 6

Markov Chain Monte Carlo

2/22-2/28

Week 7

Variance and Covariance

3/1-3/7

Week 8

Central Limit Theorem and Continuous Random Variables

3/8-3/14

Week 9

Transformations and Joint Densities

3/15-3/21

Week

Spring Break

3/22-3/28

Week 10

The Normal & Gamma Families and MGFs

3/29-4/4

Week 11

MLE and MAP

4/5-4/11

Week 12

Prediction

4/12-4/18

Week 13

Simple regression

4/19-4/25

Week 14

Multiple regression

4/26-5/2

Week	Content	Assignments
1	Probability — axioms, rules, approximation Random variables - distributions, equality, conditioning Week 1 Study Guide	Lab 1: Birthday Attack (Part A due 1/25 at 11:59PM) Homework 1 (Due 1/25 at 11:59PM)
2	Conditioning, symmetry, and independence Symmetry and collections of events Week 2 Study Guide	Week 2 Checkpoint (Complete on Gradescope, Due 1/27 at 11:59PM) Lab 1: Birthday Attack (Part B due 2/1 at 11:59PM) Homework 2 (Due 2/1 at 11:59PM)
3	Binomial and related counts; a Poisson limit Independence and Poissonization Week 3 Study Guide	Week 3 Checkpoint (Complete on Gradescope, Due 2/3 at 11:59PM) Lab 2: Total Variation (Part A due 2/8 at 11:59PM) Homework 3 (Due 2/8 at 11:59PM)
4	Expectation and Additivity More Properties of Expectation Week 4 Study Guide	Week 4 Checkpoint (Complete on Gradescope, Due 2/10 at 11:59PM) Lab 2: Total Variation (Part B due 2/16 at 11:59PM) Homework 4 (due 2/16 at 11:59PM)
5	Expectation by Conditioning Long run behavior of Markov Chains Midterm 1 on 2/19 Week 5 Study Guide	Midterm 1 on 2/19 Week 5 Checkpoint (Complete on Gradescope, Due 2/17 at 11:59PM)
6	Balance Markov Chain Monte Carlo Week 6 Study Guide	Week 6 Checkpoint (Complete on Gradescope, Due 2/24 at 11:59PM) Lab 3: Codebreaking by MCMC (due 3/1 at 11:59PM) Homework 5 (Due 3/1 at 11:59PM)
7	SD and tail bounds Covariance and its uses Week 7 Study Guide	Week 7 Checkpoint (Complete on Gradescope, Due 3/3 at 11:59PM) Lab 4: Decisions Based on Ranks (Part A due 3/8 at 11:59PM) Homework 6 (Due 3/8 at 11:59PM)
8	Central Limit Theorem Probability densities Week 8 Study Guide	Week 8 Checkpoint (Complete on Gradescope, Due 3/10 at 11:59PM) Lab 4: Decisions Based on Ranks (Part B due 3/15 at 11:59PM) Homework 7 (Due 3/15 at 11:59PM)
9	Transformations Joint Densities Week 9 Study Guide	Week 9 Checkpoint (Complete on Gradescope, Due 3/17 at 11:59PM) Lab 5: Densities and SymPy (Part A due 3/29 at 11:59PM) Homework 8 (Due 3/29 at 11:59PM)
	Spring Break
10	Independent normal and gamma variables Moment generating functions; CLT revisited; Chernoff bound Midterm 2 on 4/2 Week 10 Study Guide	Midterm 2 on 4/2 Week 10 Checkpoint (Complete on Gradescope, Due 3/31 at 11:59PM) Lab 5: Densities and SymPy (Part B due 4/5 at 11:59PM)
11	MLE; Bayesian approach and MAP Estimates The beta and the binomial Week 11 Study Guide	Lab 6: Poisson Process (Part A due 4/12 at 11:59PM) Homework 9 (Due 4/12 at 11:59PM)
12	Prediction and Error Error Variance Week 12 Study Guide	Lab 6: Poisson Process (Part B due 4/19 at 11:59PM) Homework 10 (Due 4/19 at 11:59PM)
13	Random vectors; multivariate normal Simple regression Week 13 Study Guide	Week 13 Checkpoint (Complete on Gradescope, Due 4/21 at 11:59PM) Lab 7: Constructing the Bivariate Normal (due 4/26 at 11:59PM) Homework 11 (Due 4/26 at 11:59PM)
14	Multiple regression I Multiple regression II Week 14 Study Guide	Homework 12 (Due 5/3 at 11:59PM)
15	RRR Week
	Final Exam on 5/13	Final Exam on 5/13