Announcements

  • Thanks for a great summer! If you have any lingering questions or concerns, please feel free to email Anna and Phil or post on Piazza
  • Keep an eye out on Piazza for the fall Lab Assistant application!
  • The final project guidelines have been released! You can find them on Piazza by following this link.
  • Your final project proposal is due on 07/26 by 11:59pm.
  • We'll be holding a catch-up lecture on Thurs 7/9 at 10 am to review the programming techniques that were covered in the first few weeks of class. More information will be posted on Piazza!
  • Project 1 has been released! The checkpoint is due Thurs 7/9 at 11:59 PM and the project is due Sun 7/12. You can choose to work either on your own or with a partner. If you had requested to be matched with a partner, you should have received an email on Sunday. If you don't see the message, email Anna to follow-up!
  • Lab 5 is due tonight at 11:59 PM
  • Homework 5 is due Thursday 7/9 at 11:59 PM
  • We will not longer be offer lab checkoffs for lab credit. To receive credit on your lab, you must complete the lab notebook and pass all public tests by Tuesday/Thursday at 11:59 PM PDT.
  • The midterm is next Friday!
  • Friday 7/3 is an academic holiday - we will not holding live lecture or office hours.
  • Homework 3 is due on Thurs 7/2 at 11:59 PM PDT.
  • Homework 4 will be released on Thursday and is due on Sun 7/5 at 11:59 PM PDT.
  • Project 1 will be released next Monday! You can choose to work either on your own or with a partner. If you would like to be matched with a partner, fill out this form!
  • We will not longer be offer lab checkoffs for lab credit. To receive credit on your lab, you must complete the lab notebook and pass all public tests by Monday/Wednesday at 11:59 PM PDT.
  • Homework 3 will be released today and is due on Thurs 7/2 at 11:59 PM PDT.
  • Homework 4 will be released on Thursday and is due on Sun 7/5 at 11:59 PM PDT.
  • Project 1 will be released next Monday! You can choose to work either on your own or with a partner. If you would like to be matched with a partner, fill out this form!
  • Welcome to Data 8! Lecture and Lab start today. Discussion starts tomorrow. Zoom links for all sessions will be posted on Piazza.
  • Make sure you've been added to the course Piazza, Gradescope, and OkPy. If you do not have access to any of these platforms, email your GSI.
  • If you have DSP accommodations please have your letter sent in by Friday.
  • The midterm is scheduled for Friday July 17th at 10 am - 12 pm PDT. If you are in a time zone that would require you to start the exam between 12 am and 7 am or have a time conflict with another class and/or exam please fill out this form.
  • Homework 1 will be released later today, and will be due on Thursday 6/25 at 11:59 pm PDT.

Calendar

Instructors: Anna Nguyen and Philippe (Phil) Boileau

Note: Topics are subject to changes.

Date Course Content Assignments
Sun 06/21
Module 1.1 - Introduction: Introduction, Cause and Effect, Data Types
Mon 06/22
Live Lecture: Introduction (Slides) (Video)
Homework 01 (Due Thu 06/25)
Tue 06/23
Discussion 1: Introduction (Worksheet) (Video)
Wed 06/24
Live Lecture: Introduction to Tables (Slides) (Demo) (Video)
Thu 06/25
Discussion 2: Data Types (Worksheet) (Video)
Homework 02 (Due Sun 06/28)
Fri 06/26
Data Exploration Lecture: Data Sources (Slides) (Video)

Week 2: Visualizing Data and Advanced Table Operations

Textbook Readings:

Date Course Content Assignments
Sun 06/28
Module 2.1 - Data Visualization: Charts, Histograms, Overlayed Histograms
Mon 06/29
Live Lecture: Data Visualizations (Slides) (Demo) (Video)
Homework 03 (Due Thu 07/02)
Tue 06/30
Module 2.2 - Tables II: Functions, Groups, Joins, Tables Review
Discussion 3: Extending Tables (Worksheet) (Video)
Wed 07/01
Live Lecture: Advanced Table Opertations (Slides) (Demo) (Video)
Thu 07/02
Discussion 4: Visualizations and Histograms (Worksheet) (Video)
Homework 04 (Due Sun 07/05)
Fri 07/03
Holiday: No Class
Date Course Content Assignments
Sun 07/05
Module 3.1 - Probability and Sampling: Iteration, Chance, Conditioning, Sampling
Mon 07/06
Live Lecture: Probability and Sampling (Slides) (Demo) (Video)
Homework 05 (Due Thu 07/09)
Project 1 (Due Sun 07/12)
Tue 07/07
Discussion 5: Simulations (Worksheet) (Video)
Wed 07/08
Live Lecture: Hypothesis Testing (Slides) (Demo) (Video)
Thu 07/09
Discussion 6: Comparing Models (Worksheet) (Video)
Homework 06 (Due Sun 07/12)
Fri 07/10
Data Exploration Lecture: Data Quality Assessment (Slides) (Video)

Week 4: Hypothesis Testing (Continued)

Textbook readings: Chapter 12: Comparing Two Samples

Date Course Content Assignments
Sun 07/12
Module 4.1 - Hypothesis Testing II: A/B Testing, Causality
Mon 07/13
Live Lecture: A/B Testing (Slides) (Demo) (Video)
Homework 07 (Due Sun 07/19)
Tue 07/14
Discussion 7: A/B Testing (Worksheet) (Video)
Wed 07/15
Live Lecture: Midterm Review (Slides) (Video)
Discussion: Midterm Review 1/2 (Worksheet) (Video)
Thu 07/16
Discussion: Midterm Review 2/2 (Worksheet) (Video)
Fri 07/17
Midterm Exam
Midterm

Week 5: Uncertainty, Confidence, and Distributions

Textbook readings: Chapter 13: Estimation

Date Course Content Assignments
Sun 07/19
Module 5.1 - Uncertainty and Confidence Intervals: Estimation and the Bootstrap, Confidence Intervals
Mon 07/20
Live Lecture: Uncertainty and Confidence Intervals (Slides) (Demo) (Video)
Homework 08 (Due Thu 07/23)
Tue 07/21
Module 5.2 - Distributions: Center and Spread, The Normal Distribution
Discussion 8: Bootstrapping (Worksheet) (Video)
Wed 07/22
Live Lecture: Center, Spread, and the Normal (Slides) (Demo) (Video)
Thu 07/23
Discussion 9: The Variance of Sample Means (Worksheet) (Video)
Homework 09 (Due Sun 07/26)
Fri 07/24
Data Exploration Lecture: Hypothesis Testing (Slides) (Demo) (Video)

Week 6: Linear Regression

Textbook readings:

Date Course Content Assignments
Sun 07/26
Module 6.1 - Linear Regression I: Correlation, Linear Regression
Mon 07/27
Live Lecture: Introduction to Linear Regression (Slides) (Demo) (Video)
Homework 10 (Due Thu 07/30)
Tue 07/28
Module 6.2 - Linear Regression II: Least Squares, Residuals, Inference
Discussion 10: Correlation and Regression (Worksheet) (Video)
Wed 07/29
Live Lecture: Least Squares, Linear Regression Diagnostics, and Regression Inference (Slides) (Demo) (Video)
Thu 07/30
Discussion 11: Regression Inference (Worksheet) (Video)
Homework 11 (Due Sun 08/02)
Fri 07/31
Data Exploration Lecture: Linear Regression (Slides) (Demo) (Video)

Week 7: Classification, and Case Studies

Textbook readings: Chapter 16: Classification

Date Course Content Assignments
Sun 08/02
Module 7.1 - Classification: Introduction, Classifiers
Mon 08/03
Live Lecture: Classification (Slides) (Demo) (Video)
Homework 12 (Due Thu 08/06)
Project 2 (Due Sun 08/09)
Tue 08/04
Module 7.2 - Case Studies (Optional): Data Science and Privacy
Discussion 12: Classification (Worksheet) (Video)
Wed 08/05
Data Exploration Lecture: Classification (Slides) (Video)
Fri 08/07
Live Lecture: How to Present Final Project Results (Slides) (Video)

Week 8: Guest Lectures, and Final Project

Date Course Content Assignments
Mon 08/10
Guest Lecture: Ziad Obermeyer (Slides) (Video)
Wed 08/12
Live Lecture: Conclusion (Slides) (Video)
Final Project Due at 11:59 PM PDT
Fri 08/14
Panel: Careers in Data Science (1 PM) (Video)