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)