Data 100: Principles and Techniques of Data Science
UC Berkeley, Spring 2024
Ed Datahub Gradescope Lectures Playlist Extenuating Circumstances Office Hours Queue
Joseph E. Gonzalez
He/Him/His
Office Hours: Tuesdays from 3:00PM to 4:30PM in Soda 773 (Starting Jan 23rd)
Narges Norouzi
She/Her/Hers
Office Hours: Mondays 10:00AM  11:00AM in Soda 775
Thursdays from 1:00 to 2:30PM in Warren Hall (Room 101BC)
Welcome to Week 16 of Data 100!
Lectures will be webcast at: https://berkeley.zoom.us/j/91646148607.
Schedule
Week 1
 Jan 16

 Lecture 1 Introduction
 Note 1
 Lecture Participation 1 Lecture Participation 1
 Jan 18
 Lecture Participation 2 Lecture Participation 2
 Jan 19
 Lab 1 Prerequisite Coding (due Jan 23)
 Homework 1A Plotting and Permutation Test (due Jan 25)
 Homework 1B Prerequisite Math (due Jan 25)
Week 2
 Jan 23
 Lecture Participation 3 Lecture Participation 3

 Discussion 1 Prerequisites
 Solution, Video
 Jan 25

 Lecture 4 Pandas III
 Note 4
 Lecture Participation 4 Lecture Participation 4
 Jan 26
 Lab 2A Pandas (due Jan 30)
 Homework 2A Food Safety (due Feb 1)
Week 3
 Jan 30

 Lecture 5 Data Wrangling and EDA (Part 1)
 Note 5
 Lecture Participation 5 Lecture Participation 5

 Discussion 2 Pandas I, Worksheet Notebook, Groupwork Notebook
 Worksheet Solution, Video Groupwork Solution, Video
 Feb 1
 Lecture Participation 6 Lecture Participation 6
 Feb 2
 Lab 2B Data Cleaning and EDA (due Feb 6)
 Homework 2B Food Safety II (due Feb 8)
Week 4
 Feb 6

 Lecture 7 Visualization I
 Note 7
 Lecture Participation 7 Lecture Participation 7

 Discussion 3 Pandas II, EDA, Regex
 Solution, Video
 Feb 8

 Lecture 8 Visualization II
 Note 8
 Lecture Participation 8 Lecture Participation 8

 Exam Prep 2 Pandas II, RegEx
 Solution, Video
 Feb 9
 Lab 3 Regex, EDA (due Feb 13)
 Homework 3 Text Analysis of Bloomberg Articles (due Feb 15)
Week 5
 Feb 13
 Lecture Participation 9 Lecture Participation 9

 Discussion 4 Visualization and Transformation, Worksheet Notebook
 Feb 15

 Lecture 10 Modeling, SLR
 Note 10
 Lecture Participation 10 Lecture Participation 10

 Exam Prep 3 Visualization
 Solution, Video
 Feb 16
 Lab 4 Transformations (due Feb 20)
 Homework 4 Bike Sharing (due Feb 22)
Week 6
 Feb 20

 Lecture 11 Constant model, Loss, and Transformations
 Note 11
 Lecture Participation 11 Lecture Participation 11

 Discussion 5 Probability, Sampling, and Simple Linear Regression
 Solution, Video
 Feb 22

 Lecture 12 OLS (Multiple Regression)
 Note 12
 Lecture Participation 12 Lecture Participation 12
 Feb 23
 Lab 5 Modeling, Loss Functions, and Summary Statistics (due Feb 27)
 Homework 5 Sampling (due Feb 29)
Week 7
 Feb 27

 Lecture 13 Gradient descent / sklearn
 Note 13
 Lecture Participation 13 Lecture Participation 13
 Feb 29

 Lecture 14 Feature Engineering
 Note 14
 Lecture Participation 14 Lecture Participation 14
 Mar 1
 Lab 6 OLS (due Mar 5)
Week 8
 Mar 5

 Lecture 15 Case Study (HCE): CCAO
 Note 15
 Lecture Participation 15 Lecture Participation 15

 Discussion 7 Midterm Review
 Solution
 Mar 7
 No Lecture

Midterm Exam Midterm (79 PM PST)
 Mar 8
 Lab 7 Gradient descent and Sklearn (due Mar 12)
 Project A1 Housing I (due Mar 14)
Week 9
 Mar 12

 Lecture 16 CrossValidation and Regularization
 Note 16
 Lecture Participation 16 Lecture Participation 16

 Discussion 8 Gradient descent, Feature Engineering, Housing
 Solution, Video
 Mar 14

 Lecture 17 Random Variables
 Note 17
 Lecture Participation 17 Lecture Participation 17

 Exam Prep 6 Gradient Descent
 Solution , Video
 Mar 15
 Lab 8 Model Selection, Regularization, and CrossValidation (due Mar 19)
 Project A2 Housing II (due Mar 21)
Week 10
 Mar 19

 Lecture 18 Estimators, Bias, and Variance
 Note 18
 Lecture Participation 18 Lecture Participation 18

 Discussion 9 CrossValidation and Regularization
 Solution, Video
 Mar 21

 Lecture 19 Parameter Inference and the Bootstrap
 Note 19
 Lecture Participation 19 Lecture Participation 19

 Exam Prep 7 Cross Validation and Regularization
 Solution , Video
 Mar 22
 Lab 9 Probability (due Apr 2)
 Homework 6 Probability (due Apr 4)
Week 11
 Mar 25
 Spring Break
 Mar 26
 Spring Break
 Mar 27
 Spring Break
 Mar 28
 Spring Break
 Mar 29
 Spring Break
Week 12
 Apr 2
 Lecture Participation 20 Lecture Participation 20

 Discussion 10 RVs, Bias, and Variance
 Solution, Video
 Apr 4
 Lecture Participation 21 Lecture Participation 21

 Exam Prep 8 Probability and BiasVariance
 Solution , Video
 Apr 5
 Lab 10 SQL (due Apr 9)
 Homework 7 SQL (due Apr 11)
Week 13
 Apr 9

 Lecture 22 Logistic Regression I
 Note 22
 Lecture Participation 22 Lecture Participation 22

 Discussion 11 SQL, Discussion Notebook
 Worksheet Solution, Notebook Solution, Video
 Apr 11

 Lecture 23 Logistic Regression II
 Note 23
 Lecture Participation 23 Lecture Participation 23
 Apr 12
 Lab 11 Logistic Regression (due Apr 16)
 Project B1 Spam & Ham I (due Apr 18)
Week 14
 Apr 16
 Lecture 24 PCA I

 Lecture Participation 24 Lecture Participation 24
 Note 24

 Discussion 12 Logistic Regression
 Solution, Video
 Apr 18
 Lecture Participation 25 Lecture Participation 25

 Exam Prep 10 Logistic Regression
 Solution , Video
 Apr 19
 Lab 12 PCA (due Apr 23)
 Project B2 Spam & Ham II (due Apr 25)
Week 15
 Apr 23

 Lecture 26 Clustering
 Note 26
 Lecture Participation 26 Lecture Participation 26
 Apr 25
 Lecture 27 Intro to LLMs and Conclusion
 Lecture Participation 27 Lecture Participation 27

 Exam Prep 11 PCA and Clustering
 Solution , Video
 Apr 26
 Lab 13 Clustering (due Apr 30)
Week 16
 Apr 29
 RRR
 Apr 30
 RRR
 May 1
 RRR
 May 2
 RRR
 May 3
 RRR
Week 17
 May 9
 Final Exam Final (811 AM PST)