# Principles and Techniques of Data Science

UC Berkeley, Summer 2022

### Anirudhan Badrinath

Jump to current week: here.

**Frequently Asked Questions:**Before posting on the class Ed, please read the class FAQ page.- The Syllabus contains a detailed explanation of how each course component will work this summer, given that the course is being taught entirely online.
- Textbook readings are optional and actively in development. See the Resources for more details.
**Note:**The schedule of lectures and assignments is subject to change.

## Schedule

### Week 1

- Jun 21
**Lab 1**Prerequisite Coding (due Jun 27)**Lab 2**Pandas (due Jun 27)- Jun 22
**Lecture 2**Pandas ITextbook: Pandas Reference Table

Reference: Pandas API Documentation

- Jun 23
**Lecture 3**Pandas II**Discussion 0**(Optional) Fundamentals**Discussion 1**Sampling and Probability, Pandas, code**Homework 1**Intro + Prerequisites (due Jun 27)- Jun 23
**Exam Prep 1**Sampling and Probability, Pandas

### Week 2

- Jun 27
**Lecture 4**Data Cleaning, EDA**Weekly Check 2**Weekly Check 2**Lab 3**Data Cleaning and EDA (due Jul 2)**Lab 4**Transformations and KDE (due Jul 2)**Homework 2**Food Safety (due Jun 30)- Jun 28
**Lecture 5**Regex**Discussion 2**Pandas, Data Cleaning- Jun 29
**Lecture 6**Visualization ITextbook: Seaborn Reference Table

Textbook: Matplotlib Reference Table

- Jun 30
**Lecture 7**Visualization II**Discussion 3**Regex, Visualization**Homework 3**Tweets (due Jul 5)- Jul 1
**Exam Prep 2**Pandas, Visualization, Regex**Catch-up section 1**

### Week 3

- Jul 4
Independence Day

**Weekly Check 3**Weekly Check 3**Lab 5**Modeling, Loss Functions, and Summary Statistics (due Jul 9)**Lab 6**Linear Regression (due Jul 9)**Homework 4**Bike Sharing (due Jul 7)- Jul 5
**Discussion 4**Modeling and Visualization- Jul 6
- Jul 7
**Lecture 10**Ordinary Least Squares (Multiple Linear Regression)**Discussion 5**Linear Model and Loss Function**Homework 5**Regression (On paper) (due Jul 11)- Jul 8
**Exam Prep 3**SLR & OLR**Catch-up section 2**

### Week 4

- Jul 11
**Lecture 11**Gradient Descent, sklearn**Weekly Check 4**Weekly Check 4**Lab 7**Gradient Descent and Feature Engineering (due Jul 16)**Lab 8**Model Selection, Regularization, and Cross-Validation (due Jul 16)**Proj 1A**Housing I (due Jul 14)- Jul 12
**Lecture 12**Gradient Descent, Feature Engineering**Discussion 6**Geometry of Least Squares, Gradient Descent, HCE- Jul 13
**Lecture 13**Cross-Validation and Regularization- Jul 14
**Discussion 7**HCE, OHE, Ridge and Lasso Linear Regression**Proj 1B**Housing II (due Jul 25)- Jul 15
**Midterm Review**Midterm Review**Exam Prep 4**Gradient Descent, Weighted Least SquareSolution, no recording

**Catch-up section 3**Cancelled

### Week 5

- Jul 18
**Midterm**Midterm Exam**Weekly Check 5**Weekly Check 5**Lab 9**Probability and Modeling (due Jul 23)- Jul 19
Break (No Lecture)

- Jul 20
**Lecture 15**Probability I: Random Variables- Jul 21
**Discussion 8**Probability and Bias-Variance Trade-off- Jul 22
**Exam Prep 5**CV, Probability, BVTSolution, no recording

**Catch-up section 4**TBDRecording

### Week 6

- Jul 25
**Lecture 17**SQL I**Weekly Check 6**Weekly Check 6**Lab 10**SQL (due Jul 30)**Lab 11**PCA (due Jul 30)**Homework 6**Probability and Estimators coding, written pdf, written latex (due Jul 28)- Jul 26
**Lecture 18**SQL II and PCA I**Discussion 9**BVT & SQL- Jul 27
**Lecture 19**PCA II- Jul 28
Break (No Lecture)

**Discussion 10**SQL & PCA**Homework 7**SQL and PCA (due Aug 1)- Jul 29
**Exam Prep 6**SQL & PCA**Catch-up section 5**

### Week 7

- Aug 1
**Lecture 20**Classification and Logistic Regression I**Weekly Check 7**Weekly Check 7**Lab 12**Logistic Regression (due Aug 6)**Lab 13**Decision Trees & Random Forests (due Aug 6)**Proj 2A**Spam I (due Aug 4)- Aug 2
**Lecture 21**Logistic Regression II**Discussion 11**Logistic Regression- Aug 3
**Lecture 22**Decision Trees- Aug 4
**Lecture 23**Clustering**Discussion 12**Decision Trees, Clustering**Proj 2B**Spam II (due Aug 8)- Aug 5
**Exam Prep 7**Classifier and Clustering**Catch-up section 6**

### Week 8

- Aug 8
**Weekly Check 8**Weekly Check 8- Aug 9
- Aug 10
- Aug 11
**Optional Lecture**Neural NetworksReview

- Aug 12
**Final**Final Exam