A general description of the course can be found here, and here is a list of frequently asked questions.

Time and Location: Tuesdays & Thursdays 10:30-11:50 AM, School of Education room 128

Office Hours: The Course Assistants hold working office hours every evening, Sunday-Thursday, from 7:00-9:30 PM in the basement of the Huang building. Look for the "CS 102" sign. Professor Widom holds daytime office hours in the Gates Building office #422 on a varying schedule announced in advance, and by appointment.

Staff Mailing List:

Professor: Jennifer Widom - Gates 422,
Course Assistant: Akash Das Sarma - Gates 430,
Course Assistant: Ethan Chan -
Course Assistant: Ivan Gozali -
Administrator: Marianne Siroker - Gates 435,

Date
Topic and Assignments
Readings/References
Notes (posted after class)
Tue Mar 29
Introduction to course and topic
Thurs Mar 31
Spreadsheets and basic data operations
Assignment 1 ready: Spreadsheets and basic data visualization
Tue Apr 5
Data visualization (basic)
Thu Apr 7
Relational databases and SQL (1)
Sun Apr 10
Assignment 1 due - sample solution
Tue Apr 12
Relational databases and SQL (2)
Assignment 2 ready: SQL, correlation and causation
See Apr 7
See Apr 7
Thu Apr 14
Correlation and causation; Privacy
April 14 slides
Tue Apr 19
Introduction to Python; using Python for basic data operations and visualization
Project 1 assigned: Personal Data Analysis
Thu Apr 21
Introduction to data mining; data mining in SQL and Python
Assignment 3 ready: Python, data mining, regression
Assignment 2 due - sample solution
Tue Apr 26
Regression (basic); regression in spreadsheets and Python
Project 1 proposal due
Thu Apr 28
Guest speaker - Lada Adamic, computational social scientist at Facebook
No readings
No notes
Sun May 1
Assignment 3 due - sample solution
Staff feedback provided on Project 1 proposal
Tue May 3
Regression (more advanced, limitations); exam Q&A
Thu May 5
Midterm exam - in class
Special location: same building, Cubberly Auditorium

Midterm sample solution
Tue May 10
Classification and clustering
Project 2 assigned: Movie-Rating Predictions
Thu May 12
Guest speaker - Stanford's CARTA system
Project 1 due
No readings
Tue May 17
Introduction to R; regression, classification, and clustering using R
Thu May 19
Anomaly detection, sampling and statistical significance
Assignment 4 ready: R, classification, clustering, sampling
Sun May 22
Project 2 due
Tue May 24
Data visualization using Tableau
Bonus Assignment (extra credit): Data visualization using Tableau
Thu May 26
Guest speaker - Trooly: Data-driven trust and compatibility
No readings
No notes
Sun May 29
Assignment 4 due - sample solution
Tue May 31
Big Data platforms (special guest Zoltan Fern, Google and CS347); Project 2 winners; exam Q&A
Wed June 1
Bonus Assignment due (no lates)
Tue Jun 7
Final exam 12:15-1:30 PM (1.25 hours)
Building 200 room 002

Final exam sample solution