Data 100: Principles and Techniques of Data Science
UC Berkeley, Summer 2023
Ed Datahub Gradescope Extenuating Circumstances
Welcome to Week 8!
Schedule
Week 1
 Jun 20

 Lecture 1 Course Overview
 Note 1
 Lab 1 Prerequisite Coding (due Jun 24)
 Homework 1A Plotting and the Permutation Test (due Jun 26)
 Homework 1B Prerequisite Math (due Jun 26)
 Jun 21

 Discussion 1 Math Prerequisites
 Solution
 Jun 22
Week 2
 Jun 26

 Lecture 4 Pandas III, EDA I
 Note 4

 Discussion 2 Pandas worksheet, worksheet notebook, groupwork notebook
 Solution
 Lab 2 Pandas (due Jul 1)
 Lab 3 Data Cleaning and EDA (due Jul 1)
 Homework 2 Pandas (due Jun 29)
 Jun 27
 Jun 28

 Lecture 6 Text Wrangling, Regex
 Note 6
 Jun 29

 Lecture 7 Visualization
 Note 7
 Homework 3 Tweets (due Jul 3)
 Jun 30
Week 3
 Jul 3
 Break (no lecture)

 Discussion 4 Regex (optional)
 Solution, Video Walkthrough
 Lab 4 Transformation (due Jul 8)
 Lab 5 Modeling, Summary Statistics, Loss Functions (due Jul 8)
 Homework 4 Bike Sharing (Visualization) (due Jul 6)
 Jul 4
 Independence Day (no lecture)
 Jul 5
 Jul 6

 Lecture 9 Modeling, SLR
 Note 9
 Homework 5A Sampling (due Jul 10)
 Homework 5B Modeling (due Jul 10)
 Jul 7

 Exam Prep 2 Regex, KDE Plots
 Solution
Week 4
 Jul 10

 Lecture 10 Constant model, loss, and transformations
 Note 10

 Discussion 6 Sampling, SLR
 Solution
 Lab 6 Ordinary Least Squares (due Jul 15)
 Lab 7 Gradient Descent, Feature Engineering (due Jul 15)
 Homework 6 Regression (due Jul 13)
 Jul 11

 Lecture 11 Ordinary Least Squares (Multiple Linear Regression)
 Note 11
 Jul 12

 Lecture 12 Gradient Descent
 Note 12

 Discussion 7 Transformations, OLS
 Solution
 Jul 13

 Lecture 13 Sklearn, Feature Engineering
 Note 13
 Project A1 Housing I (due Jul 17)
Week 5
 Jul 17

 Discussion 8 Gradient Descent, Feature Engineering
 Solution
 Lab 8 Model Selection (due Jul 22)
 Project A2 Housing II (due Jul 24)
 Jul 18

 Lecture 15 CrossValidation, Regularization
 Note 15
 Jul 19
 Break (no lecture)
 Discussion 9 Exam Review
 Jul 20
 Midterm Midterm Exam (57 PM)
Week 6
 Jul 24

 Lecture 16 Random Variables
 Note 16

 Discussion 10 CrossValidation, Regularization
 Solution
 Lab 9 Probability (due Jul 29)
 Lab 10 Logistic Regression (due Jul 29)
 Homework 7 Probability and Estimators (due Jul 27)
 Jul 25

 Lecture 17 Estimators, Bias, and Variance
 Note 17
 Jul 26

 Lecture 18 Logistic Regression I
 Note 18

 Discussion 11 Random Variables, BVT
 Solution
 Jul 27

 Lecture 19 Logistic Regression II
 Note 19
 Project B1 Spam & Ham I (due Jul 31)
 Jul 28
Week 7
 Jul 31

 Discussion 12 Logistic Regression
 Solution
 Lab 11 SQL (due Aug 5)
 Lab 12 PCA (due Aug 5)
 Project B2 Spam & Ham II (due Aug 3)
 Aug 1
 Aug 2
 Aug 3
 Homework 8 SQL, PCA (due Aug 7)
Week 8
 Aug 7

 Lecture 24 Decision Trees
 Note 24
 Lab 13 Decision Trees (optional)
 Aug 8
 Lecture 25 Conclusion
 Aug 9
 Break (no lecture)
 Discussion 15 Decision Trees, Final Review
 Aug 10
 Final Final Exam (57 PM)