# Principles and Techniques of Data Science

UC Berkeley, Spring 2023

Lecture Zoom Discussions Office Hour/Lab Help

### Lisa Yan

### Narges Norouzi

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 Spring, please take time to take a look.
**Note:**The schedule of lectures and assignments is subject to change.

## Schedule

### Week 1

- Jan 17
**Lecture 1**Introduction**Lecture Participation 1**Lecture Participation 1 **Survey**Pre-Semester Survey (due 1/20) - Jan 19
**Lecture 2**Pandas I**Lecture Participation 2**Lecture Participation 2 - Jan 20
**Lab 1**Prerequisite Refresher (due Jan 24) **Homework 1A**Plotting and the Permutation Test (due Jan 26)**Homework 1B**Prerequisite Math (due Jan 26)

### Week 2

- Jan 24
**Lecture 3**Pandas II**Discussion 1**Prerequisites**Lecture Participation 3**Lecture Participation 3 - Jan 26
**Lecture Participation 4**Lecture Participation 4- Jan 27
**Lab 2**Pandas (due Jan 31)**Homework 2**Food Safety (due Feb 2)

### Week 3

- Jan 31
**Lecture 5**Data Cleaning and EDA, Part 2**Discussion 2**Pandas worksheet, worksheet notebook, groupwork notebook**Lecture Participation 5**Lecture Participation 5- Feb 2
**Lecture 6**Text Wrangling and Regex**Lecture Participation 6**Lecture Participation 6- Feb 3
**Exam prep 1**Pandas**Lab 3**Data Cleaning, EDA, Regex (due Feb 7)**Homework 3**Tweets (due Feb 9)

### Week 4

- Feb 7
**Lecture 7**Visualization I**Discussion 3**EDA and Regex worksheet, worksheet notebook**Lecture Participation 7**Lecture Participation 7- Feb 9
**Lecture 8**Visualization II**Lecture Participation 8**Lecture Participation 8- Feb 10
**Exam prep 2**Data Cleaning, EDA and Regex**Lin Alg Review 1**Linear Algebra Review #1**Lab 4**Visualization, Transformations and KDEs (due Feb 14)**Homework 4**Bike Sharing (due Feb 16)

### Week 5

- Feb 14
**Lecture 9**Sampling**Discussion 4**Visualization and Transformation worksheet, worksheet notebook**Lecture Participation 9**Lecture Participation 9- Feb 16
**Lecture 10**Intro to Modeling, Simple Linear Regression**Lecture Participation 10**Lecture Participation 10- Feb 17
**Exam prep 3**Visualizations**Lin Alg Review 2**Linear Algebra Review #2**Lab 5**Modeling, Loss Functions, and Summary Statistics (due Feb 21)**Homework 5A**Modeling (due Feb 23)**Homework 5B**Modeling Handwritten (LaTeX template) (due Feb 23)

### Week 6

- Feb 21
**Lecture 11**Constant model, loss, and transformations**Lecture Participation 11**Lecture Participation 11- Feb 23
**Lecture 12**Ordinary Least Squares (Multiple Linear Regression)**Lecture Participation 12**Lecture Participation 12- Feb 24
**Exam prep 4**Sampling and SLR**Lin Alg Review 3**Linear Algebra Review #3 (Linear Regression)**Lab 6**OLS (due Feb 28)**Homework 6**Regression (due Mar 2)

### Week 7

- Feb 28
**Lecture 13**sklearn / Gradient descent I**Lecture Participation 13**Lecture Participation 13- Mar 2
**Lecture 14**Gradient descent II / Feature Engineering**Lecture Participation 14**Lecture Participation 14- Mar 3
**Exam prep 5**Ordinary Least Squares**Lab 7**Gradient descent / sklearn (due Mar 7)

### Week 8

- Mar 7
**Lecture 15**Cross-Validation / Regularization**Discussion 7**Gradient Descent, Feature Engineering**Lecture Participation 15**Lecture Participation 15- Mar 9
**Lecture 16**Regularization + Random Variables**Lecture Participation 16**Lecture Participation 16**midterm**Midterm Exam (7-9 PM)- Mar 10
**Lab 8**Model Selection (due Mar 14)**Project A1**Housing (due Mar 16)

### Week 9

- Mar 14
**Lecture 17**Estimators, Bias, and Variance**Discussion 8**Cross-Validation, Regularization and Random Variables**Lecture Participation 17**Lecture Participation 17- Mar 16
**Lecture 18**Case study (HCE): CCAO**Lecture Participation 18**Lecture Participation 18- Mar 17
**Exam prep 6**Cross Validation and Random Variables**Lab 9**Probability (due Mar 21)**Project A2**Housing II (due Mar 23)

### Week 10

- Mar 21
**Lecture 19**Case Study: Climate & Physical Data**Discussion 9**Housing II and Probability I worksheet, factsheet**Lecture Participation 19**Lecture Participation 19- Mar 23
**Lecture 20**Bias, Variance, and Inference**Lecture Participation 20**Lecture Participation 20- Mar 24
**Exam prep 7**Bias-Variance Tradeoff**Lab 10**Climate & Inference (due April 4)**Homework 7**Probability (due April 6)

### Spring Break

- Mar 28
Spring Break

- Mar 30
Spring Break

### Week 11

- Apr 4
**Lecture 21**SQL I**Discussion 10**Bias and Variance**Lecture Participation 21**Lecture Participation 21- Apr 6
**Lecture 22**SQL II / Data Serialization**Lecture Participation 22**Lecture Participation 22- Apr 7
**Exam prep 8**SQL**Lab 11**SQL (due April 11)**Homework 8**SQL (due April 13)

### Week 12

- Apr 11
**Lecture 23**Classification and Logistic Regression I**Lecture Participation 23**Lecture Participation 23- Apr 13
**Lecture 24**Logistic Regression II**Lecture Participation 24**Lecture Participation 24- Apr 14
**Exam prep 9**Logistic Regression**Lab 12**Logistic regression (due Apr 18)**Project B1**Spam & Ham I (due Apr 20)

### Week 13

- Apr 18
**Lecture 25**PCA I**Discussion 12**Logistic Regression**Lecture Participation 25**Lecture Participation 25- Apr 20
**Lecture 26**PCA II**Lecture Participation 26**Lecture Participation 26- Apr 21
**Exam prep 10**Logistic Regression II**Lab 13**PCA (due Apr 25)**Project B2**Spam & Ham II (due Apr 27)

### Week 14

- Apr 25
**Lecture 27**Clustering**Lecture Participation 27**Lecture Participation 27- Apr 27
**Exam prep 11**PCA and Clustering**Lecture 28**Guest Lecture and Conclusion**Lecture Participation 28**Lecture Participation 28- Apr 28
**Lab 14**Clustering (due May 2)

### Week 16

- May 1
RRR

- May 2
RRR

- May 3
RRR

- May 4
RRR

- May 5
RRR

### Week 17

- May 11
**final**Final Exam (8-11 AM)