Principles and Techniques of Data Science

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UC Berkeley, Fall 2021

Fernando Pérez

Fernando Pérez

he/his

fernando.perez@berkeley.edu

Office Hour(s): W/Th, 11am - 12pm

Alvin Wan

Alvin Wan

he/him/his

alvinwan@berkeley.edu

Office Hour(s): M/T, 11am - 12pm



    Week 1

    Aug 26

    Lecture 1 Intro

    Aug 27

    Discussion 1 Intro (solutions)

    Homework 1 Intro + Prerequisites (due Sept 2)

    Lab 1 Prerequisite Coding (due Aug 31)

    Week 2

    Aug 30

    N/A

    Aug 31

    Lecture 2 Data Sampling and Probability I

    Live Lab

    Sep 1

    N/A

    Sep 2

    Lecture 3 Data Sampling and Probability II

    Sep 3

    Discussion 2 Probability (solutions)

    Homework 2 Sampling Error and Bias (due Sept 10)

    Lab 2 Pandas (due Sept 8)

    Week 3

    Sep 6

    Labor Day

    Sep 7

    Lecture 4 Pandas I

    Live Lab

    Sep 8

    N/A

    Sep 9

    Lecture 5 Pandas II

    Sep 10

    Discussion 3 Pandas (notebook) (pdf) (solutions)

    Homework 3 Food Safety (due Sept 16)

    Lab 3 Data Cleaning and Visualization (due Sept 14)

    Week 4

    Sep 13

    N/A

    Sep 14

    Lecture 6 Data Cleaning and EDA

    Live Lab

    Sep 15

    N/A

    Sep 16

    Lecture 7 Regex

    Sep 17

    Discussion 4 Data Cleaning and Regex (pdf) (notebook) (solutions)

    Homework 4 Tweets (due Sept 23)

    Lab 4 SQL (due Sept 23)

    Week 5

    Sep 20

    N/A

    Sep 21

    Lecture 8 SQL I

    Live Lab

    Sep 22

    N/A

    Sep 23

    Lecture 9 SQL II

    Sep 24

    Discussion 5 SQL (solutions)

    Homework 5 SQL (due Sept 30)

    Lab 5 Transformations and SQL (due Sept 28)

    Week 6

    Sep 27

    N/A

    Sep 28

    Lecture 10 Visualization I

    Live Lab

    Sep 29

    N/A

    Sep 30

    Lecture 11 Visualization II

    Oct 1

    Discussion 6 Visualization

    Homework 6 Bike Sharing (due Oct 7)

    Lab 6 Modeling, Summary Statistics, and Loss Functions (due Oct 5)

    Week 7

    Oct 4

    N/A

    Oct 5

    Lecture 12 Modeling

    Live Lab

    Oct 6

    N/A

    Oct 7

    Lecture 13 Simple Linear Regression

    Oct 8

    Discussion 7 Modeling and Linear Regression

    Homework 7 Regression (on paper) (due Oct 14)

    Lab 7 Simple Linear Regression (due Oct 12)

    Week 8

    Oct 11

    N/A

    Oct 12

    Lecture 14 Linear Regression + Geometric Interpretation

    Live Lab

    Oct 13

    N/A

    Oct 14

    Lecture 15 Human Contexts and Ethics

    Oct 15

    Discussion 8 Multiple Linear Regression and HCE

    Homework 8 Housing I (due Oct 21)

    Lab 8 Multiple Linear Regression (due Oct 19)

    Week 9

    Oct 18

    N/A

    Oct 19

    Lecture 16 Feature Engineering

    Live Lab

    Oct 20

    N/A

    Oct 21

    Lecture 17 RVs and Bias-Variance Tradeoff

    Oct 22

    Discussion 9 Feature Engineering and Bias-Variance Tradeoff

    Homework 9 Housing II (due Oct 28)

    Lab 9 Feature Engineering (due Oct 26)

    Week 10

    Oct 25

    N/A

    Oct 26

    Lecture 18 Regularization and Cross-Validation

    Live Lab

    Oct 27

    N/A

    Oct 28

    Lecture 19 Guest Lecture: Physical Data and the Climate

    Oct 29

    Discussion 10 Regularization and Cross-Validation

    No Homework 10 Midterm on 11/1

    Week 11

    Nov 1

    Midterm Midterm (7-9 pm)

    Nov 2

    Lecture 20 Gradient Descent

    Live Lab

    Nov 3

    N/A

    Nov 4

    Lecture 21 Logistic Regression I

    Nov 5

    Discussion 11 Gradient Descent and Logistic Regression I

    Homework 10 Gradient Descent and Logistic Regression (due Nov 11)

    Lab 10 Cross-Validation and Regularization (due Nov 9)

    Week 12

    Nov 8

    N/A

    Nov 9

    Lecture 22 Logistic Regression II and Classification

    Live Lab

    Nov 10

    N/A

    Nov 11

    Veterans Day

    Nov 12

    Discussion 12 Classification and Logistic Regression II

    Homework 11 Spam & Ham I

    Lab 11 Logistic Regression (due Nov 16)

    Week 13

    Nov 15

    N/A

    Nov 16

    Lecture 23 Decision Trees

    Live Lab

    Nov 17

    N/A

    Nov 18

    Lecture 24 Inference for Modeling

    Nov 19

    Discussion 13 Decision Trees and Inference

    Homework 12 Spam & Ham II (due Nov 25)

    Lab 12 Decision Trees & Random Forests (due Nov 23)

    Week 14

    Nov 22

    N/A

    Nov 23

    Lecture 25 Dimensionality Reduction & PCA

    Live Lab

    Nov 24

    N/A (Thanksgiving)

    Nov 25

    N/A (Thanksgiving)

    Nov 26

    No Discussion (Thanksgiving)

    Homework 13 PCA (due Dec 2)

    Lab 13 PCA (due Nov 30)

    Week 15

    Nov 29

    N/A

    Nov 30

    Lecture 26 Clustering

    Live Lab

    Dec 1

    N/A

    Dec 2

    Lecture 27 Guest Lecture: The Social Cost of Carbon

    Dec 3

    Discussion 14 PCA & Clustering

    Homework 15 (optional) Taxis (due Dec 9)

    Lab 15 Clustering (due Dec 7)

    Week 16

    Dec 7

    Review

    Dec 9

    Final Project Final Project due (?)