# Principles and Techniques of Data Science

UC Berkeley, Fall 2020

**All announcements are on Piazza. Make sure you are enrolled and active there.**- Please read our course FAQ before contacting staff with questions that might be answered there.
- The Syllabus contains a detailed explanation of how each course component will work this fall, given that the course is being taught entirely online.
- The scheduling of all weekly events is in the Calendar.
- The Zoom links for all live events are in @15 on Piazza.

### Week 1

- Aug 26
N/A

- Aug 27
**Lecture 1**Introduction, Course Overview (QC due Aug. 31)- Aug 28
**Homework 1**Prerequisites (due Sept. 3)

### Week 2

- Aug 31
**Lab 1**Prerequisite Coding (due Aug. 31)- Sep 1
**Lecture 2**Data Sampling and Probability (QC due Sept. 8)- Sep 2
**Discussion 1**Linear Algebra and Probability (video) (solutions)- Sep 3
**Lecture 3**Random Variables (QC due Sept. 8)- Sep 4
**Homework 2**Trump Sampling (due Sept. 10)

### Week 3

- Sep 8
**Lab 2**SQL (due Sept. 8th)- Sep 8
**Lecture 4**SQL (QC due Sept. 14)- Sep 9
**Discussion 2**Random Variables and SQL (video) (solutions)- Sep 10
**Lecture 5**Pandas I (QC due Sept. 14)- Sep 11
**Project 1**Food Safety (due Sept. 24)

### Week 4

- Sep 14
**Lab 3**Pandas I (due Sept. 14)- Sep 15
**Lecture 6**Pandas II (QC due Sept. 21)- Sep 16
**Discussion 3**Pandas (video) (solutions)- Sep 17
**Lecture 7**Data Cleaning and EDA (QC due Sept. 21)- Sep 18
N/A

### Week 5

- Sep 21
**Lab 4**Data Cleaning and EDA (due Sept. 21)- Sep 22
**Lecture 8**Regular Expressions (QC due Sept. 28)- Sep 23
**Discussion 4**Regex (notebook) (video) (solutions)- Sep 24
**Lecture 9**Visualization I (QC due Sept. 28)- Sep 25
**Homework 3**Bike Sharing (due Oct. 1)

### Week 6

- Sep 28
**Lab 5**Transformations and KDEs (due Sept. 28)- Sep 29
**Lecture 10**Visualization II (QC due Oct. 5)- Sep 30
**Discussion 5**Visualizations (notebook) (video) (solutions)- Oct 1
**Lecture 11**Modeling (QC due Oct. 5)- Oct 2
**Homework 4**Trump Tweets (due Oct. 8)

### Week 7

- Oct 5
**Lab 6**Modeling, Summary Statistics, and Loss Functions (due Oct. 5)- Oct 6
**Lecture 12**Simple Linear Regression (QC due Oct. 12)- Oct 7
**Discussion 6**Modeling and Linear Regression (video) (solutions)- Oct 8
**Lecture 13**Ordinary Least Squares (QC due Oct. 12)- Oct 9
**Homework 5**Regression (due Oct. 22)

### Week 8

- Oct 12
**Lab 7**Simple Linear Regression (due Oct. 12)- Oct 13
**Review Sessions**Midterm Review- Oct 14
**Discussion 7**Least Squares (video) (solutions)- Oct 15
**Exam**Midterm (7-9PM PDT)- Oct 16
N/A

### Week 9

- Oct 19
N/A

- Oct 20
**Lecture 14**Feature Engineering (QC due Oct. 26)**Survey**Mid-Semester Survey (due Oct. 26)- Oct 21
**Discussion 8**Feature Engineering and Midterm Review (video) (solutions)- Oct 22
**Lecture 15**Bias and Variance (QC due Oct. 26)- Oct 23
**Homework 6**Housing (due Nov. 6)

### Week 10

- Oct 26
**Lab 8**Multiple Linear Regression and Feature Engineering (due Oct. 26)- Oct 27
**Lecture 16**Cross-Validation and Regularization (QC due Nov. 2)- Oct 28
**Discussion 9**Bias & Variance, Cross-Validation, & Regularization (video) (solutions)- Oct 29
**Lecture 17**Gradient Descent (QC due Nov. 2)- Oct 30
N/A

### Week 11

- Nov 2
**Lab 9**Feature Engineering & Cross-Validation (due Nov. 2)- Nov 3
N/A (Election Day)

- Nov 4
**Discussion 10**Gradient Descent (video) (solutions)- Nov 5
**Lecture 18**Logistic Regression I (QC due Nov. 9)- Nov 6
**Homework 7**Gradient Descent and Logistic Regression (due Nov. 12)

### Week 12

- Nov 9
**Lab 10**Logistic Regression (due Nov. 9)**Graduate Project**Graduate Project- Nov 10
**Lecture 19**Logistic Regression II, Classification (QC due Nov. 16)- Nov 11
**Discussion 11**Logistic Regression (video) (solutions)- Nov 12
**Lecture 20**Decision Trees (QC due Nov. 16)- Nov 13
**Project 2**Spam/Ham (due Nov. 30)

### Week 13

- Nov 16
**Lab 11**Decision Trees and Random Forests (due Nov. 16)- Nov 17
**Lecture 21**Inference for Modeling (QC due Nov. 23)- Nov 18
**Discussion 12**Decision Trees & Inference (video) (solutions)- Nov 19
**Lecture 22**Principal Components Analysis (QC due Nov. 23)- Nov 20
**Homework 8**PCA (due Dec. 3)

### Week 14

- Nov 23
**Lab 12**Principal Component Analysis (due Nov. 23)**Live Session**AMA with Professors (9-10AM PST)- Nov 24
**Lecture 23**Clustering (QC due Nov. 30)- Nov 25
N/A (Thanksgiving)

- Nov 26
N/A (Thanksgiving)

- Nov 27
N/A

### Week 15

- Nov 30
**Lab 13**Using the Bootstrap for Estimation (due Dec. 7)- Dec 1
**Lecture 24**Big Data (QC due Dec. 7)- Dec 2
**Discussion 13**PCA, Clustering, & Big Data (video) (solutions)- Dec 3
- Dec 4
**Survey**Final Survey and Official Course Evals (due Dec. 13)

### Week 16 (RRR Week)

- Dec 8
Review

- Dec 10
Review

- N/A
- N/A

### Week 17 (Finals Week)

- Dec 15
**Exam**Final Exam (7-10PM PST)