# Principles and Techniques of Data Science

UC Berkeley, Summer 2020

### Week 1

- Jun 22
**Lecture 1**Course Overview (slides) (code) (video)**Homework 1**Prerequisites (due Jun. 24)**Discussion 1**Prerequisite Review (video) (solutions)- Jun 23
**Lecture 2**Data Sampling and Probability I**Lab 1**Prerequisite Coding (due Jun. 23)- Jun 24
**Lecture 3**Data Sampling and Probability II**Discussion 2**Random Variables**Homework 2**Trump Sampling- Jun 25
**Lecture 4**SQL**Lab 2**SQL (due Jun. 25)

### Week 2

- Jun 29
**Lecture 5**Pandas I**Project 1**Food Safety**Discussion 3**SQL- Jun 30
**Lecture 6**Pandas II**Lab 3**Pandas I- Jul 1
**Lecture 7**Data Cleaning and EDA**Discussion 4**Pandas II- Jul 2
**Lecture 8**Regular Expressions**Lab 4**Data Cleaning and EDA

### Week 3

- Jul 6
**Lecture 9**Visualization I**Homework 3**Bike Sharing**Discussion 5**Regex- Jul 7
**Lecture 10**Visualization II**Lab 5**Visualization & KDE- Jul 8
**Lecture 11**Modeling**Discussion 6**Visualizations and Transformations**Homework 4**Trump- Jul 9
**Exam**Midterm I**Lab 6**Modeling and Loss Functions

### Week 4

- Jul 13
**Lecture 12**Simple Linear Regression**Discussion 7**Correlation- Jul 14
**Lecture 13**Ordinary Least Squares**Lab 7**Regression- Jul 15
**Lecture 14**Feature Engineering**Discussion 8**Geometric Least Squares & One Hot Encoding**Homework 5**Regression- Jul 16
**Lecture 15**Bias-Variance Tradeoff**Lab 8**Feature Engineering

### Week 5

- Jul 20
**Lecture 16**Regularization & Cross-Validation**Homework 6**Housing**Discussion 9**Bias Variance & Cross Validation- Jul 21
**Lecture 17**Gradient Descent**Lab 9**Cross Validation- Jul 22
**Lecture 18**Logistic Regression I**Discussion 10**Gradient Descent & Logistic Regression**Homework 7**Gradient Descent & Logistic Regression- Jul 23
**Lecture 19**Logistic Regression II and Classification**Lab 10**Logistic Regression

### Week 6

- Jul 27
**Exam**Midterm II**Discussion 11**Cross Entropy Loss and Classification- Jul 28
**Lecture 20**Inference for Modeling**Lab 11**Bootstrap the model parameters- Jul 29
**Lecture 21**Decision Trees**Discussion 12**Decision Trees & Random Forests**Project 2**Spam/Ham- Jul 30
**Lecture 22**Dimensionality Reduction & PCA**Lab 12**Decision Trees

### Week 7

- Aug 3
**Lecture 23**PCA**Discussion 13**PCA- Aug 4
**Lecture 24**Clustering**Lab 13**Clustering- Aug 5
**Lecture 25**Guest Lecture**Discussion 14**Clustering**Homework 8**PCA- Aug 6
**Lecture 26**Conclusion

### Week 8

- Aug 10
**Lecture**Review- Aug 11
**Lecture**Review- Aug 12
**Exam**Final Part I- Aug 13
**Exam**Final Part II