Data 100: Principles and Techniques of Data Science

UC Berkeley, Fall 2024

Ed Datahub Gradescope Lectures Playlist Additional Accommodations Office Hours Queue

Joseph E. Gonzalez

He/Him/His

jegonzal@cs.berkeley.edu

Narges Norouzi

She/Her/Hers

norouzi@berkeley.edu

Welcome to Week 13 of Data 100!

Lectures will be webcast at: https://berkeley.zoom.us/j/91349586134.

Schedule

Week 1

Aug 29

Lecture 1 Introduction

Note 1

Lecture Participation 1 Lecture Participation 1

Aug 30

Lab 1 Prerequisite Coding (due Sep 3)

Homework 1A Plotting and the Permutation Test (due Sep 5)

Homework 1B Prerequisite Math (due Sep 5)

Week 2

Sep 3

Lecture 2 Pandas I

Note 2

Lecture Participation 2 Lecture Participation 2

Discussion 1 Prerequisites

Mini-Lecture, Solutions, Walkthrough

Sep 5

Lecture 3 Pandas II

Note 3

Lecture Participation 3 Lecture Participation 3

Exam Prep 1 Pandas

Solutions, Walkthrough

Sep 6

Lab 2A Pandas (due Sep 10)

Homework 2A Food Safety (due Sep 12)

Drop Deadline (w/o fee) 11:59pm PT

Week 3

Sep 10

Lecture 4 Pandas III

Note 4

Lecture Participation 4 Lecture Participation 4

Discussion 2 Pandas I

Mini-Lecture, Solutions, Notebook, Groupwork Notebook, Groupwork Walkthrough, Regular Walkthrough

Sep 12

Lecture 5 Data Cleaning and EDA

Note 5

Lecture Participation 5 Lecture Participation 5

Exam Prep 2 Pandas and EDA

Solutions, Walkthrough

Sep 13

Lab 2B Data Cleaning and EDA (due Sep 17)

Homework 2B Food Safety II (due Sep 19)

Add Deadline (w/o fee) 11:59pm PT

Week 4

Sep 17

Lecture 6 Regex

Note 6

Lecture Participation 6 Lecture Participation 6

Discussion 3 Pandas II, EDA

Mini-Lecture, Solutions, Walkthrough

Sep 19

Lecture 7 Visualization I

Note 7

Lecture Participation 7 Lecture Participation 7

Exam Prep 3 RegEx

Solutions, Walkthrough

Sep 20

Lab 3 Regex, EDA (due Sep 24)

Homework 3 Text Analysis of Bloomberg Articles (due Sep 26)

Drop Deadline (with fee) 11:59pm PT

Week 5

Sep 24

Lecture 8 Visualization II

Note 8

Lecture Participation 8 Lecture Participation 8

Discussion 4 Regex, Visualization, and Transformation

Mini-Lecture, Solutions, Walkthrough

Sep 26

Lecture 9 Sampling

Note 9

Lecture Participation 9 Lecture Participation 9

Exam Prep 4 Data Visualization

Solutions, Walkthrough

Sep 27

Lab 4 Transformations (due Oct 1)

Homework 4 Bike Sharing (due Oct 3)

Add Deadline for Graduate Students 11:59pm PT

Week 6

Oct 1

Lecture 10 Modeling, SLR

Note 10

Lecture Participation 10 Lecture Participation 10

Discussion 5 Probability, Sampling, and Visualization

Mini-Lecture, Solutions, Walkthrough

Oct 3

Lecture 11 Constant model, Loss, and Transformations

Note 11

Lecture Participation 11 Lecture Participation 11

Exam Prep 5 SLR

Solutions, Walkthrough

Oct 4

Lab 5 Modeling, Summary Statistics, and Loss Functions (due Oct 8)

Homework 5A Modeling (due Oct 10)

Week 7

Oct 8

Lecture 12 OLS (Multiple Regression)

Note 12

Lecture Participation 12 Lecture Participation 12

Discussion 6 Models, OLS

Mini-Lecture, Solutions, Walkthrough

Oct 10

Lecture 13 Gradient descent / sklearn

Note 13

Lecture Participation 13 Lecture Participation 13

Exam Prep 6 OLS, Gradient Descent

Solutions, Walkthrough

Oct 11

Lab 6 OLS (due Oct 15)

Homework 5B OLS (due Oct 17)

Week 8

Oct 15

Lecture 14 Feature Engineering

Note 14

Lecture Participation 14 Lecture Participation 14

Discussion 7 Gradient Descent, Feature Engineering

Mini-Lecture, Solutions,Walkthrough

Oct 17

Lecture 15 Case Study (HCE): CCAO

Note 15

Lecture Participation 15 Lecture Participation 15

Oct 18

Lab 7 Gradient descent and Sklearn (due Oct 22)

Project A1 Housing I (due Oct 25)

Week 9

Oct 22

Lecture 16 Cross-Validation and Regularization

Note 16

Lecture Participation 16 Lecture Participation 16

Discussion 8 Midterm Review

Solutions

Oct 23

Midterm Exam Midterm (7-9 PM PST)

Oct 24

Lecture 17 Random Variables

Note 17

Lecture Participation 17 Lecture Participation 17

Exam Prep 7 Cross Validation and Regularization

Solutions, Walkthrough

Oct 25

Lab 8 Model Selection (due Oct 29)

Project A2 Housing II (due Oct 31)

Week 10

Oct 29

Lecture 18 Estimators, Bias, and Variance

Note 18

Lecture Participation 18 Lecture Participation 18

Discussion 9 Cross-Validation and Regularization

Mini-Lecture, Solutions, Walkthrough

Oct 31

Lecture 19 Parameter Inference & the Bootstrap

Note 19

Lecture Participation 19 Lecture Participation 19

Exam Prep 8 Probability and Bias-Variance

Solutions, Walkthrough

Nov 1

Lab 9 Probability (due Nov 5)

Homework 6 Probability (due Nov 7)

Grade Option Change Deadline 11:59pm PT

Week 11

Nov 5

Lecture 20 SQL I

Note 20

Lecture Participation 20 Lecture Participation 20

Discussion 10 RVs, Bias, and Variance

Mini-Lecture, Solutions, Walkthrough

Nov 7

Lecture 21 SQL II

Note 21

Lecture Participation 21 Lecture Participation 21

Exam Prep 9 SQL

Solutions

Nov 8

Lab 10 SQL (due Nov 12)

Homework 7 SQL (due Nov 16)

Week 12

Nov 12

Lecture 22 Logistic Regression I

Note 22

Lecture Participation 22 Lecture Participation 22

Discussion 11 SQL

Mini-Lecture, Notebook, Solutions, Walkthrough

Nov 14

Lecture 23 Logistic Regression II

Note 23

Lecture Participation 23 Lecture Participation 23

Nov 15

Lab 11 Logistic Regression (due Nov 19)

Nov 17

Project B1 Spam & Ham I (due Nov 23)

Week 13

Nov 19

Lecture 24 PCA I

Note 24

Lecture Participation 24 Lecture Participation 24

Discussion 12 Logistic Regression

Mini-Lecture, Solutions

Nov 21

Lecture 25 PCA II

Nov 22

Lab 12 PCA (due Nov 26)

Nov 24

Project B2 Spam & Ham II (due Dec 5)

Week 14

Nov 26

Lecture 26 Clustering

No Discussion

Nov 28

No Lecture

Nov 29

Lab 13 Clustering (due Dec 10)

Week 15

Dec 3

Lecture 27 Neural Networks

Discussion 13 PCA + Clustering

Dec 5

Lecture 28 LLMs + closing

Week 16

Dec 9

RRR

Dec 10

RRR

Dec 11

RRR

Dec 12

RRR

Dec 13

RRR

Week 17

Dec 18

Final Exam Final (8-11 AM PST)