Data 140: Probability for Data Science

UC Berkeley, Fall 2025

Week 1

Aug 28

Welcome to Data 140! The first lecture will be on Thursday, August 28th, from 3:30 PM - 5 PM in Dwinelle 155. The first mega-sections will happen on Friday, August 29th.
Please carefully read through the course information, which covers the details of the course this fall.
Please work through the math prerequisites. The first lecture will use Basic Counting, Sums, and Exponential and Log Functions.
The Week 1 Study Guide has been released.

Calendar

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Week 1: Introduction

Aug 27

Guide Week 1

Aug 28

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

Aug 29

Mega-Section

Week 2: Random Variables and Symmetry

Sep 1

Labor Day

Sep 2

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

Sep 3

Section

Sep 4

Lecture Symmetry and collections of events: Ch 5

Sep 5

Mega-Section

Week 3: Random Counts

Sep 8

Sep 9

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

Sep 10

Section

Sep 11

Lecture Independence and Poissonization: Ch 7

Sep 12

Mega-Section

Week 4: Expectation

Sep 15

Sep 16

Lecture Expectation: Ch 8.1 - 8.3

Sep 17

Section

Sep 18

Lecture Expectation and additivity: Ch 8.4 - 8.5

Sep 19

Mega-Section

Week 5: Conditioning and Markov Chains

Sep 22

Sep 23

Lecture Expectation by conditioning: Ch 9

Sep 24

Section

Sep 25

Lecture Long run behavior of Markov chains: Ch 10

Sep 26

Mega-Section

Week 6: Markov Chain Monte Carlo

Sep 29

Exam Midterm 1: 8PM - 10PM

Sep 30

Lecture Balance: Ch 10, 11.1

Oct 1

Section

Oct 2

Lecture Markov Chain Monte Carlo: Ch 11.2 - 11.3

Oct 3

Mega-Section

Week 7: Variance and Tail Bounds

Oct 6

Oct 7

Lecture Standard deviation and tail bounds: Ch 12

Oct 8

Section

Oct 9

Lecture Covariance and its uses: Ch 13

Oct 10

Mega-Section

Week 8: Central Limit Theorem and Densities

Oct 13

Oct 14

Lecture Central Limit Theorem: Ch 14

Oct 15

Section

Oct 16

Lecture Probability densities: Ch 15

Oct 17

Mega-Section

Week 9: Transformations and Joint Densities

Oct 20

Oct 21

Lecture Transformations: Ch 16

Oct 22

Section

Oct 23

Lecture Joint densities: Ch 17

Oct 24

Mega-Section

Week 10: The Beta, Normal, and Gamma Families

Oct 27

Oct 28

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

Oct 29

Section

Oct 30

Lecture Moment generating functions; Chernoff bound: Ch 19

Oct 31

Mega-Section

Week 11: MGFs, MLE, and MAP

Nov 3

Exam Midterm 2: 8PM - 10PM

Nov 4

Lecture MLE; conditioning; MAP estimates: Ch 20

Nov 5

Section

Nov 6

Lecture The beta and the binomial: Ch 21

Nov 7

Mega-Section

Week 12: The Beta and the Binomial; Prediction

Nov 10

Nov 11

Veterans Day

Nov 12

Section

Nov 13

Lecture Prediction and error: Ch 22.1 - 22.2

Nov 14

Mega-Section

Week 13: Variance by Conditioning and Random Vectors

Nov 17

Nov 18

Lecture Variance by conditioning: Ch 22.3 - 22.4

Nov 19

Section

Nov 20

Lecture Random vectors; the multivariate normal: Ch 23

Nov 21

Mega-Section

Week 14: Simple Regression

Nov 24

Nov 25

Lecture Correlation and simple regression: Ch 24

Nov 26

Thanksgiving Break

Nov 27

Thanksgiving Break

Nov 28

Thanksgiving Break

Week 15: Multiple Regression

Dec 1

Dec 2

Lecture Multiple regression I: Ch 25.1 - 25.3

Dec 3

Section

Dec 4

Lecture Multiple regression II: Ch 25.4

Dec 5

Mega-Section

Week 16: Reading, Review, Recitation

Dec 8: RRR Week
Dec 9: RRR Week
Dec 10: RRR Week
Dec 11: RRR Week
Dec 12: RRR Week

Week 17: Final Exams

Dec 19

Exam Final Exam: 7PM - 10PM