Data 100: Principles and Techniques of Data Science

UC Berkeley, Fall 2025

Datahub Pensieve Ed Office Hours Queue Lectures Playlist

Josh GrossmanHe/Him/His

jdgg AT berkeley DOT edu

data100.instructors@berkeley.edu

Welcome to Week 13 of Data 100!

Lectures will be webcast on Zoom.

Schedule Jump to Current Week

Week 1

Thu Aug 28

Lecture 1 Introduction

Note 1

Lecture Participation 1 Slido

Lab 1 Prerequisite Coding (due Wed 9/3)

Homework 1 Prerequisite Math and Coding (due Thu 9/4)

Week 2

Tue Sep 2

Lecture 2 Pandas I

Note 2

Lecture Participation 2 Slido

Discussion 1 Prerequisites

Mini-Lecture, Solutions

Thu Sep 4

Lecture 3 Pandas II

Note 3

Lecture Participation 3 Slido

Lab 2A Pandas (due Wed 9/10)

Homework 2A Food Safety (due Thu 9/11)

Fri Sep 5

Drop Deadline (without fee) 11:59 PM

Week 3

Tue Sep 9

Lecture 4 Pandas III

Note 4

Lecture Participation 4 Slido

Discussion 2 Pandas I

Mini-Lecture, Notebook, Groupwork Notebook, Solutions, Notebook Solutions, Groupwork Notebook Solutions

Thu Sep 11

Lecture 5 Data Cleaning and EDA

Note 5

Lecture Participation 5Slido

Lab 2B Data Cleaning and EDA (due Wed 9/17)

Homework 2B Food Safety II (due Thu 9/18)

Fri Sep 12

Add Deadline (without fee) 11:59 PM

Week 4

Mon Sep 15

Exam Prep 1 Pandas

Solutions, Walkthrough

Tue Sep 16

Lecture 6 Regex

Note 6

Lecture Participation 6 Slido

Discussion 3 Pandas II, EDA

Mini-Lecture, Monopoly Demo Notebook, Solutions

Wed Sep 17

Drop Deadline (with fee) 11:59 PM

Thu Sep 18

Lecture 7 Visualization I

Note 7

Lecture Participation 7 Slido

Lab 3 Regex, EDA (due Wed 9/24)

Homework 3 Text Analysis of New York Times Articles (due Thu 9/25)

Week 5

Mon Sep 22

Exam Prep 2 EDA and Regex

Solutions, Walkthrough

Tue Sep 23

Lecture 8 Visualization II

Note 8

Lecture Participation 8 Slido

Discussion 4 Regex, Visualization, and KDE

Mini-Lecture, Bigfoot Demo Notebook, Solutions

Thu Sep 25

Lecture 9 Sampling

Note 9

Lecture Participation 9 Slido

Lab 4 Transformations (due Wed 10/1)

Homework 4 Bike Sharing (due Thu 10/2)

Fri Sep 26

Add/Drop Deadline for Graduate Students 11:59 PM

Week 6

Mon Sep 29

Exam Prep 3 Visualization

Solutions, Walkthrough

Tue Sep 30

Lecture 10 Modeling, SLR

Note 10

Lecture Participation 10 Slido

Discussion 5 Transformations, Sampling, and SLR

Mini-Lecture, Solutions

Thu Oct 2

Lecture 11 Constant Model, Loss, Transformations

Note 11

Lecture Participation 11 Slido

Lab 5 Modeling, Summary Statistics, and Loss Functions (due Wed 10/8)

Homework 5 Modeling and OLS (due Mon 10/13)

Week 7

Mon Oct 6

Exam Prep 4 Modeling and Midterm Prep

Solutions, Walkthrough

Tue Oct 7

Lecture 12 Ordinary Least Squares

Note 12

Lecture Participation 12 Slido

Discussion 6 Modeling and OLS

Mini-Lecture, Solutions

Thu Oct 9

Lecture 13 Case Study HCE: CCAO

Note 13

Lecture Participation 13 Slido

Lab 6 OLS (due Fri 10/17)

Week 8

Tue Oct 14

Lecture 14 Gradient Descent

Note 14

Lecture Participation 14 Slido

Discussion 7 Midterm 1 Review

Solutions

Thu Oct 16

No Lecture

Midterm 1 See Syllabus for details

Lab 7 Gradient Descent / Sklearn (due Thu 10/23)

Project A1 Housing I (due Fri 10/24)

Week 9

Mon Oct 20

Exam Prep 5 OLS and Gradient Descent

Solutions, Walkthrough

Tue Oct 21

Lecture 15 Feature Engineering

Note 15

Lecture Participation 15 Slido

Discussion 8 Gradient Descent, Feature Engineering, and Housing

Mini-Lecture, Solutions

Thu Oct 23

Lecture 16 Cross-Validation, Regularization

Note 16

Lecture Participation 16 Slido

Lab 8 Model Selection (due Wed 10/29)

Project A2 Housing II (due Fri 10/31)

Week 10

Mon Oct 27

Exam Prep 6 Feature Engineering, Cross Validation, and Regularization

Solutions, Walkthrough

Tue Oct 28

Lecture 17 Random Variables

Note 17

Lecture Participation 17 Slido

Discussion 9 Cross-Validation, Regularization, and Random Variables

Mini-Lecture, Solutions

Thu Oct 30

Lecture 18 Estimators, Bias, and Variance

Note 18

Lecture Participation 18 Slido

Lab 9 Probability (due Wed 11/5)

Homework 6 Coding, Probability (due Fri 11/7)

Fri Oct 31

Grade Option Change 11:59 PM

Week 11

Mon Nov 3

Exam Prep 7 Probability and Bias-Variance

Solutions, Walkthrough

Tue Nov 4

Lecture 19 Parameter Inference & Bootstrap

Note 19

Lecture Participation 19 Slido

Discussion 10 Bias and Variance

Mini-Lecture, Solutions

Thu Nov 6

Lecture 20 SQL I

Note 20

Lecture Participation 20 Slido

Lab 10 SQL (due Fri 11/14)

Homework 7 SQL (due Mon 11/17)

Week 12

Mon Nov 10

Exam Prep 8 Midterm 2 Prep

Solutions

Tue Nov 11

Holiday Veterans Day

No Lecture

Wed Nov 12

Discussion 11 SQL (RECORDED)

Mini-Lecture, Notebook, Walkthrough, Solutions

Thu Nov 13

Lecture 21 SQL II

Note 21

Lecture Participation 21 Slido

Week 13

Tue Nov 18

Lecture 22 Logistic Regression I

Note 22

Lecture Participation 22 Slido

Discussion 12 Midterm 2 Review

Solutions

Wed Nov 19

Lab 11 Logistic Regression (due Mon 12/1)

Thu Nov 20

No Lecture

Midterm 2 See Syllabus for details

Project B1 Spam & Ham I (due Tue 12/2)

Week 14

Tue Nov 25

Lecture 23 Logistic Regression II

Lecture Participation 23 Slido

Discussion 13 Logistic Regression (RECORDED)

Lab 12 PCA (due Fri 12/5)

Thu Nov 27

Holiday Thanksgiving

No Lecture

Week 15

Mon Dec 1

Project B2 Spam & Ham II (due Tue 12/9)

Tue Dec 2

Lecture 24 PCA and Clustering I

Lecture Participation 24 Slido

Discussion 14 PCA and Clustering

Thu Dec 4

Lecture 25 PCA and Clustering II

Lecture Participation 25 Slido

Lab 13 Clustering (due Wed 12/10)

Week 16

Tue Dec 9

Final Review

Thu Dec 11

Final Review

Week 17

Wed Dec 17

Final Exam Final (8:00 AM - 11:00 AM)