Data 140: Probability for Data Science

UC Berkeley, Fall 2024

Ani AdhikariProfessor

adhikari

Week 6

Sep 30

The Week 6 Study Guide has been released.
Homework 6 and Lab 4 have been released. They are both due next Monday, October 7th at 5 PM.

Calendar

Jump to current week

Week 1: Introduction

Aug 28

Guide Week 1

Aug 29

Lecture Probability: axioms, rules, approximation: Course Information, Ch 1, 2

Homework Homework 1: Due Sep 3 at 9 AM

Lab Lab 1: Due Sep 3 at 9 AM

Aug 30

Mega-Section

Week 2: Random Variables and Symmetry

Sep 2

Labor Day

Guide Week 2

Sep 3

Lecture Random variables: distributions, equality, conditioning: Ch 3, 4

Homework Homework 2: Due Sep 9 at 5 PM

Lab Lab 2: Due Sep 9 at 5 PM

Sep 4

Section

Sep 5

Lecture Symmetry and collections of events: Ch 5

Sep 6

Mega-Section

Week 3: Random Counts

Sep 9

Guide Week 3

Homework Homework 3: Due Sep 16 at 5 PM

Lab Lab 3A: Due Sep 16 at 5 PM

Sep 10

Lecture Binomial and related counts; a Poisson limit: Ch 6

Sep 11

Section

Sep 12

Lecture Independence and Poissonization: Ch 7

Sep 13

Mega-Section

Week 4: Expectation

Sep 16

Guide Week 4

Homework Homework 4: Due Sep 23 at 5 PM

Lab Lab 3B: Due Sep 23 at 5 PM

Sep 17

Lecture Expectation: Ch 8.1 - 8.3

Sep 18

Section

Sep 19

Lecture Expectation and additivity: Ch 8.4 - 8.5

Sep 20

Mega-Section

Week 5: Conditioning and Markov Chains

Sep 23

Guide Week 5

Homework Homework 5: Due Sep 30 at 12 PM NOON

Sep 24

Lecture Expectation by conditioning: Ch 9

Sep 25

Section

Sep 26

Lecture Long run behavior of Markov chains: Ch 10

Sep 27

Mega-Section

Week 6: Markov Chain Monte Carlo

Sep 30

Exam Midterm 1: 8PM - 10PM

Oct 1

Guide Week 6

Homework Homework 6: Due Oct 7 at 5 PM

Lab Lab 4: Due Oct 7 at 5 PM

Lecture Balance: Ch 10, 11.1

Oct 2

Section

Oct 3

Lecture Markov Chain Monte Carlo: Ch 11.2 - 11.3

Oct 4

Mega-Section

Week 7: Variance and Tail Bounds

Oct 7

Oct 8

Lecture Standard deviation and tail bounds: Ch 12

Oct 9

Section

Oct 10

Lecture Covariance and its uses: Ch 13

Oct 11

Mega-Section

Week 8: Central Limit Theorem and Densities

Oct 14

Oct 15

Lecture Central Limit Theorem: Ch 14

Oct 16

Section

Oct 17

Lecture Probability densities: Ch 15

Oct 18

Mega-Section

Week 9: Transformations and Joint Densities

Oct 21

Oct 22

Lecture Transformations: Ch 16

Oct 23

Section

Oct 24

Lecture Joint densities: Ch 17

Oct 25

Mega-Section

Week 10: The Beta, Normal, and Gamma Families

Oct 28

Oct 29

Lecture Joint distributions; sums of normal and gamma variables: Ch 17, Ch 18

Oct 30

Section

Oct 31

Lecture Moment generating functions: Ch 19

Nov 1

Mega-Section

Week 11: MGFs, MLE, and MAP

Nov 4

Exam Midterm 2: 8PM - 10PM

Nov 5

Lecture Moment generating functions; Chernoff bound: Ch 19

Nov 6

Section

Nov 7

Lecture MLE; conditioning; MAP estimates: Ch 20

Nov 8

Mega-Section

Week 12: The Beta and the Binomial; Prediction

Nov 11

Veterans Day

Nov 12

Lecture The beta and the binomial: Ch 21

Nov 13

Section

Nov 14

Lecture Prediction and error: Ch 22.1 - 22.2

Nov 15

Veterans Day Holiday

Week 13: Variance by Conditioning and Random Vectors

Nov 18

Nov 19

Lecture Variance by conditioning: Ch 22.3 - 22.4

Nov 20

Section

Nov 21

Lecture Random vectors; the multivariate normal: Ch 23

Nov 22

Mega-Section

Week 14: Simple Regression

Nov 25

Nov 26

Lecture Correlation and simple regression: Ch 24

Nov 27

Thanksgiving Break

Nov 28

Thanksgiving Break

Nov 29

Thanksgiving Break

Week 15: Multiple Regression

Dec 2

Dec 3

Lecture Multiple regression I: Ch 25.1 - 25.3

Dec 4

Section

Dec 5

Lecture Multiple regression II: Ch 25.4

Dec 6

Mega-Section

Week 16: Reading, Review, Recitation

Dec 9: RRR Week
Dec 10: RRR Week
Dec 11: RRR Week
Dec 12: RRR Week
Dec 13: RRR Week

Week 17: Final Exams

Dec 17

Exam Final Exam: 3PM - 6PM