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 Probability & Visualization II
Lecture Participation 8
- Feb 10
Exam prep 2 Data Cleaning, EDA and Regex
Lin Alg Review Linear Algebra Review #1
Lab 4 Transformations
Homework 4 Bike Sharing
Week 5
- Feb 14
Lecture 9 Sampling and probability II
Discussion 4 Visualization and Transformation
Lecture Participation 9
- Feb 16
Lecture 10 Modeling, SLR
Lecture Participation 10
- Feb 17
Lab 5 Modeling, Summary Statistics, and Loss Functions
Homework 5 Modeling
Week 6
- Feb 21
Lecture 11 Constant model, loss, and transformations
Discussion 5 Probability, Sampling, and SLR
Lecture Participation 11
- Feb 23
Lecture 12 OLS (multiple regression)
Lecture Participation 12
- Feb 24
Lab 6 OLS
Homework 6 Regression
Week 7
- Feb 28
Lecture 13 Gradient descent / sklearn
Discussion 6 Models and OLS
Lecture Participation 13
- Mar 2
Lecture 14 Feature Engineering
Lecture Participation 14
- Mar 3
Lab 7 Gradient descent / sklearn
Week 8
- Mar 7
Lecture 15 Cross-Validation / Regularization
Discussion 7 Gradient Descent, Feature Engineering, Housing I
Lecture Participation 15
- Mar 9
Lecture 16 Probability I
Lecture Participation 16
midterm Midterm Exam (7-9 PM)
- Mar 10
Lab 8 Model Selection
Project 1A Housing
Week 9
- Mar 14
Lecture 17 Probability II
Discussion 8 Cross-Validation and Regularization
Lecture Participation 17
- Mar 16
Lecture 18 Case study (HCE): CCAO
Lecture Participation 18
- Mar 17
Lab 9 Climate
Project 1B Housing
Week 10
- Mar 21
Lecture 19 Case Study: Climate & Physical Data
Discussion 9 Housing II and Probability I
Lecture Participation 19
- Mar 23
Lecture 20 Causal Inference and Confounding
Lecture Participation 20
- Mar 24
Lab 10 Probability & Inference
Homework 7 Probability
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
- Apr 6
Lecture 22 SQL II / Cloud Data
Lecture Participation 22
- Apr 7
Lab 11 SQL
Homework 8 SQL
Week 12
- Apr 11
Lecture 23 Logistic regression I
Discussion 11 SQL
Lecture Participation 23
- Apr 13
Lecture 24 Logistic regression II
Lecture Participation 24
- Apr 14
Lab 12 Logistic regression
Project 2A Spam & Ham I
Week 13
- Apr 18
Lecture 25 PCA I
Discussion 12 Logistic Regression
Lecture Participation 25
- Apr 20
Lecture 26 PCA II
Lecture Participation 26
- Apr 21
Lab 12 PCA
Project 2B Spam & Ham II
Week 14
- Apr 25
Lecture 27 KMeans Clustering
Discussion 13 PCA
Lecture Participation 27
- Apr 27
Lecture 28 Guest + Closing
Lecture Participation 28
- Apr 28
Lab 14 Clustering
Week 16
- May 1
RRR
Lab 15 Decision Trees (Optional, no due date)
- May 2
RRR
- May 3
RRR
- May 4
RRR
- May 5
RRR
Week 17
- May 11
final Final Exam (8-11 AM)