Time and Location: Tuesdays & Thursdays (1:30pm - 2:50pm at Lathrop 299)

Office Hours: Refer to course calendar

Staff Mailing List:

Instructor: Ethan Chan -
Instructor: Lisa Wang -

We want to make this class better, we'd love your feedback on class or lectures here

TypeDateDescriptionReadings/ReferencesCourse Materials
Lecture Tue Apr 4 Introduction to Course Introductory Readings [slides]
Lecture Thu Apr 6 Spreadsheet Data Analysis and Visualization Spreadsheet References [notes]
A0 Due Sun Apr 9 Assignment 0 Due Date [Assignment #0]
Lecture Tue Apr 11 Relational Databases and SQL (1) SQL References [notes]
In Class Jupyter Notebook
Lecture Thu Apr 13 Relational Databases and SQL (2) Same [slides]
A1 Due Sun Apr 16 Assignment 1 Due Date [Assignment #1]
Lecture Tue Apr 18 Introduction to Python Python References [slides]
In Class Jupyter Notebook
Lecture Thu Apr 20 Data Operations in Python; Correlation and Causation; Privacy CC and Privacy Readings
Pandas intro
SQL vs Pandas Comparison
In Class Jupyter Notebook
A2 Due Sun Apr 23 Assignment 2 Due Date [Assignment #2]
Lecture Tue Apr 25 Introduction to Data Mining [notes]
In Class Jupyter Notebooks
Lecture Thu Apr 27 Data Mining Continued Data Mining Explained Simply [slides]
A3 Due Sun Apr 30 Assignment 3 Due Date [Assignment #3]
Midterm Tue May 2 In Class Midterm [Solution]
Lecture Thu May 4 Introduction to Machine Learning (ML): Regression Intro to ML - Coursera [slides]
Linear Regression Notebook and Data
Proposal Due Sun May 7 Project Proposal Due Date [Project Proposal]
Lecture Tue May 9 ML: Classification Supervised Learning - Coursera [slides]
Regression/Classification Notebooks and Data
Lecture Thu May 11 ML: Classification (continued) [slides]
Lecture Tue May 16 ML: Classification (continued) [slides]
Naive Bayes Notebook and Data
Lecture Thu May 18 ML: Evaluation + ML Model Building [slides]
A4 Due Tue May 23 Assignment 4 Due Date Released in 2 parts, A and B [Assignment #4A+B]
[4A Solution]
[4B Solution]
Guest Speaker Tue May 23 Machine Learning Researcher Neal Jean Predicting Poverty with Deep Learning [Guest Lecture Slides]
Lecture Thu May 25 Data Visualization (Tableau) Tableau for Students (free 1 year)
Tableau Getting Started Guides
Tableau Workbook with Examples (on Tableau Public)
Lecture Tues May 30 Unsupervised Learning and Big Data Summary Unsupervised Learning - Coursera [slides]
Clustering Notebook
Guest Speaker Thu Jun 1 Trooly CTO Cofounder Anish Das Sarma Data Driven Trust
Final Project Slides Due Mon Jun 5 Final Project Slides Due
Final Project Due Tue Jun 6 Final Project Report Due Date [Final Project]
Presentations Tues Jun 6 Final Project Presentations [Final Project]
Lecture Thu Jun 8 No class
Final Exam Fri Jun 9 Final Exam 12:15-1:45 PM Lathrop 299 (Same as usual classroom) [Final Exam Information and Practice Problems]
[Practice Problem Solutions]