Data 100: Principles and Techniques of Data Science

UC Berkeley, Fall 2024

Ed Datahub Gradescope Lectures Playlist Additional Accommodations Office Hours Queue

Narges Norouzi

Narges Norouzi

She/Her/Hers

norouzi@berkeley.edu

Welcome to Week 16 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

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, Walkthrough
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
Exam Prep 10 Logistic Regression
Solutions, Walkthrough
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,Walkthrough
Nov 21
Lecture 25 PCA II
Note 25
Lecture Participation 25 Lecture Participation 25
Exam Prep 11 PCA and Clustering
Solutions, Walkthrough
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
Note 26
Lecture Participation 26 Lecture Participation 26
No Discussion
Nov 28
No Lecture
Nov 29
Lab 13 Clustering (due Dec 10)

Week 15

Dec 3
Lecture 27 Neural Networks
Lecture Participation 27 Lecture Participation 27
Discussion 13 PCA + Clustering
Mini-Lecture, Solutions, Walkthrough
Dec 5
Lecture 28 LLMs + closing
Lecture Participation 28 Lecture Participation 28

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)