Data 100: Principles and Techniques of Data Science

UC Berkeley, Summer 2025

jdgg AT berkeley DOT edu

michaelxiao1999 AT berkeley DOT edu

Welcome to Week 0 of Data 100!

Lectures will be webcast at: https://berkeley.zoom.us/j/91772046015.

Mon June 23: Lecture 1 Introduction; Lecture Participation 1 Slido; Lab 1 Prerequisite Coding (due Thu 6/26); Homework 1 Prerequisite Math (due Fri 6/27)
Tue June 24: Lecture 2 Pandas I; Lecture Participation 2 Slido
Wed June 25: Lecture 3 Pandas II; Lecture Participation 3 Slido; Discussion 1 Prerequisites
Thu June 26: Lecture 4 Pandas III; Lecture Participation 4 Slido; Lab 2A Pandas (due Mon 6/30)
Fri June 27: Homework 2A Food Safety (due Wed 7/2)

Mon June 30: Lecture 5 Data Cleaning & EDA; Lecture Participation 5 Slido; Discussion 2 Pandas I; Lab 2B Data Cleaning & EDA (due Thu 7/3)
Tue July 1: Lecture 6 Regex; Lecture Participation 6 Slido; Homework 2B Food Safety II (due Mon 7/7)
Wed July 2: Lecture 7 Visualization I; Lecture Participation 7 Slido; Discussion 3 Pandas II, EDA
Thu July 3: Lecture 8 Visualization II; Lecture Participation 8 Slido; Lab 3 Regex, EDA (due Mon 7/7)
Fri July 4: Holiday; Homework 3 NYT Articles (due Wed 7/9)

Mon July 7: Lecture 9 Sampling; Lecture Participation 9 Slido; Discussion 4 Regex, Visualization, and Transformation; Lab 4 Transformations (due Thu 7/10)
Tue July 8: Lecture 10 Modeling, SLR; Lecture Participation 10 Slido; Homework 4 Bike Sharing (due Fri 7/11)
Wed July 9: Lecture 11 Constant model, loss, and transformations; Lecture Participation 11 Slido; Discussion 5 Probability, Sampling, & Visualization
Thu July 10: Lecture 12 Ordinary Least Squares; Lecture Participation 12 Slido; Lab 5 Modeling, Summary Statistics, Loss Functions, OLS (due Mon 7/14)
Fri July 11: Homework 5 Modeling and OLS (due Mon 7/21)

Mon July 14: Lecture 13 Gradient Descent, sklearn; Lecture Participation 13 Slido; Discussion 6 Modeling and OLS; Lab 6 Gradient Descent, sklearn (due Mon 7/21)
Tue July 15: Lecture 14 Feature Engineering; Lecture Participation 14 Slido; Project A1 A1: Housing I (due Wed 7/23)
Wed July 16: Lecture 15 HCE Case Study: CCAO; Lecture Participation 15 Slido; Discussion 7 Gradient Descent
Thu July 17: Midterm Exam See syllabus for midterm details.
Fri July 18: Midterm Exam

Mon July 21: Lecture 16 Cross-Validation & Regularization; Lecture Participation 16 Slido; Discussion 8 Feature Engineering, Housing; Lab 7 Model Selection (due 7/24)
Tue July 22: Lecture 17 Random Variables; Lecture Participation 17 Slido; Project A2 Housing II (due Fri 7/25)
Wed July 23: Lecture 18 Estimators, Bias & Variance; Lecture Participation 18 Slido; Discussion 9 Cross-Validation & Regularization
Thu July 24: Lecture 19 Parameter Inference & The Bootstrap; Lecture Participation 19 Slido; Lab 8 Probability (due Mon 7/28)
Fri July 25: Homework 6 Probability (due Wed 7/30)

Mon July 28: Lecture 20 SQL I; Lecture Participation 20 Slido; Discussion 10 Random Variables, Bias, Variance; Lab 9 SQL (due Thu 7/31)
Tue July 29: Lecture 21 SQL II; Lecture Participation 21 Slido; Homework 7 SQL (due Fri 8/1)
Wed July 30: Lecture 22 Logistic Regression I; Lecture Participation 22 Slido; Discussion 11 SQL
Thu July 31: Lecture 23 Logistic Regression II; Lecture Participation 23 Slido; Lab 10 Logistic Regression (due Mon 8/4)
Fri Aug 1: Project B1 Spam & Ham I (due Wed 8/6)

Mon Aug 4: Lecture 24 Principal Component Analysis I; Lecture Participation 24 Slido; Discussion 12 Logistic Regression; Lab 11 PCA (due Thu 8/7)
Tue Aug 5: Lecture 25 Principal Component Analysis II; Lecture Participation 25 Slido; Project B2 Spam & Ham II (due Mon 8/11)
Wed Aug 6: Lecture 26 Clustering; Lecture Participation 26 Slido; Discussion 13 PCA & Clustering
Thu Aug 7: Lecture 27 Closing; Lecture Participation 27 Slido; Lab 12 Clustering (due Mon 8/11)