Data 100: Principles and Techniques of Data Science

UC Berkeley, Fall 2023

Ed Datahub Gradescope Extenuating Circumstances

Fernando Pérez

Fernando Pérez

He/Him/His

fernando.perez@berkeley.edu

Office Hours: Tue 11-12pm (Evans 419)

Narges Norouzi

Narges Norouzi

She/Her/Hers

norouzi@berkeley.edu

Office Hours: Mon 11-12pm (Soda 775)

Welcome to Week 5 of Data 100!

Schedule

Week 1

Aug 24
Lecture 1 Introduction
Note 1
Lecture Participation 1 Lecture Participation 1
Aug 25
Lab 1 Prerequisite Coding (due Aug 29)
Homework 1A Plotting and Permutation Test (due Aug 31)
Homework 1B Prerequisite Math (due Aug 31)

Week 2

Aug 29
Lecture 2 Pandas I
Note 2
Lecture Participation 2 Lecture Participation 2
Discussion 1 Prerequisites
Solution
Aug 31
Lecture 3 Pandas II
Note 3
Lecture Participation 3 Lecture Participation 3
Sep 1
Lab 2A Pandas (due Sep 5)
Homework 2A Food Safety (due Sep 7)

Week 3

Sep 5
Lecture 4 Pandas III
Note 4
Lecture Participation 4 Lecture Participation 4
Discussion 2 Pandas I Worksheet, Notebook
Solution
Sep 7
Lecture 5 Data Cleaning and EDA
Note 5
Lecture Participation 5 Lecture Participation 5
Sep 8
Exam Prep 1 Pandas
Solution worksheet, notebook, recording
Lab 2B Data Cleaning and EDA (due Sep 12)
Homework 2B Food Safety II (due Sep 14)

Week 4

Sep 12
Lecture 6 Regex (and finish EDA)
Note 6
Lecture Participation 6 Lecture Participation 6
Discussion 3 Pandas II, III Worksheet, Groupwork notebook
Solution Worksheet, Groupwork notebook
Sep 14
Lecture 7 Visualization I
Lecture Participation 7 Lecture Participation 7
Sep 15
Exam Prep 2 Pandas II, RegEx worksheet, notebook
Solution worksheet, notebook, recording
Lab 3 Regex and EDA (due Sep 19)
Homework 3 Tweets (due Sep 21)

Week 5

Sep 19
Lecture 8 Visualization II
Lecture Participation 8 Lecture Participation 8
Discussion 4 EDA, RegEx
Solution
Sep 21
Lecture 9 Sampling
Lecture Participation 9 Lecture Participation 9
Sep 22
Exam Prep 3 Visualization
Solution
Lab 4 Transformations (due Sep 26)
Homework 4 Bike Sharing (due Sep 28)

Week 6

Sep 26
Lecture 10 Modeling and SLR
Discussion 5 Probability, Sampling, and Visualization
Sep 28
Lecture 11 Constant model, Loss, and Transformations
Sep 29
Lab 5 Modeling, Summary Statistics, and Loss Functions (due Oct 3)
Homework 5 Modeling (due Oct 5)

Week 7

Oct 3
Lecture 12 Ordinary Least Squares
Discussion 6 Models
Oct 5
Lecture 13 Gradient descent and Sklearn
Oct 6
Lab 6 Ordinary Least Squares (due Oct 10)
Homework 6 Regression (due Oct 12)

Week 8

Oct 10
Lecture 14 Feature Engineering
Discussion 7 OLS and Gradient Descent
Oct 12
Lecture 15 Case study (HCE): CCAO
Oct 13
Lab 7 Gradient descent and Sklearn (due Oct 17)
Project A1 Housing I (due Oct 19)

Week 9

Oct 17
Lecture 16 Cross-Validation and Regularization
Discussion 8 Feature Engineering and Housing
Oct 18
Midterm Midterm (7:00pm - 9:00pm)
Oct 19
Lecture 17 Random Variables
Oct 20
Lab 8 Model Selection (due Oct 24)
Project A2 Housing II (due Oct 26)

Week 10

Oct 24
Lecture 18 Estimators, Bias and Variance
Discussion 9 Cross-Validation and Regularization
Oct 26
Lecture 19 TBD
Oct 27
Lab 9 Probability (due Oct 31)
Homework 7 Probability (due Nov 2)

Week 11

Oct 31
Lecture 20 SQL I
Discussion 10 RVs, Bias, and Variance
Nov 2
Lecture 21 SQL II / Cloud Data
Nov 3
Lab 10 SQL (due Nov 7)
Homework 8 SQL (due Nov 9)

Week 12

Nov 7
Lecture 22 Logistic Regression I
Discussion 11 SQL
Nov 9
Lecture 23 Logistic Regression II
Nov 10
Lab 11 Logistic Regression (due Nov 14)
Project B1 Spam and Ham I (due Nov 16)

Week 13

Nov 14
Lecture 24 Case Study: Climate & Physical Data
Discussion 12 Logistic Regression I
Nov 16
Lecture 25 PCA I
Nov 17
Lab 12 Inference & Climate (due Nov 21)
Project B2 Spam and Ham II (due Nov 30)

Week 14

Nov 21
Lecture 26 PCA II
Discussion 13 Logistic Regression II
Nov 23
Lecture No Lecture (Thanksgiving)
Nov 24
Lab 13 PCA (due Nov 28)

Week 15

Nov 28
Lecture 27 KMeans Clustering
Discussion 14 PCA
Nov 30
Lecture 28 Closing
Dec 1
Lab 14 Clustering (due Dec 5)

Week 16

Dec 4
RRR
Dec 5
RRR
Dec 6
RRR
Dec 7
RRR
Dec 8
RRR

Week 17

Dec 14
Final Exam Final (11:30am - 2:30pm)