CSC 380: Principles of Data Science (Spring 2023)
Tentative schedule
Slides credit: heavily built on Profs. Jason Pacheco and Kwang-Sung Jun’s CSC 380 slides used in their previous offerings.
| Date | Topics | Notes | Additional readings | Homework | |
|---|---|---|---|---|---|
| Jan 12 | Course mechanics, Intro to data science | slides | Robinson and Nolis, “What is Data Science?”; Download Probability and Statisics Cookbook | ||
| Jan 17 | Probability 1 | ||||
| Jan 19 | Probability 2 | WL: Ch. 1 / WJ: Ch. 5, 6 | HW1 | ||
| Jan 24 | Probability 3 | ||||
| Jan 26 | Probability 4 | WL: Ch. 2 / WJ: Ch. 7,9 | |||
| Jan 31 | Probability 5 | WL: Ch. 3 / WJ: Ch. 8 | HW2 | ||
| Feb 2 | Probability 6 | slides | |||
| Feb 7 | Statistics 1 | WL: Sec. 9.1, 9.2, Sec 6.3 / WJ Ch. 12 | |||
| Feb 9 | Statistics 2 | WJ 14.1-14.4, 15.1-15.2 | HW3 | ||
| Feb 14 | Statistics 3 | WJ 16.1-16.2 | |||
| Feb 16 | Statistics 4 | slides | WJ 20.1-20.4, Notes on Boostrap Confidence Intervals by Orloff and Bloom | ||
| Feb 21 | Statistics 5 / Data processing and visualization 1 | draft slides | HW4 (on Piazza) | ||
| Feb 23 | Midterm review | slides | |||
| Feb 28 | Data processing and visualization 2 | ||||
| Mar 2 | Midterm | ||||
| Mar 7 | Spring Recess | ||||
| Mar 9 | Spring Recess | ||||
| Mar 14 | Data processing and visualization 3 | slides | |||
| Mar 16 | Basics of Predictive modeling and classification 1 | MK : Sec. 1.4, Sec. 3.5 | HW5 out | ||
| Mar 21 | Basics of Predictive modeling and classification 2 | ||||
| Mar 23 | Basics of Predictive modeling and classification 3 | draft slides | |||
| Mar 28 | Linear Models 1 | MK : Sec. 7.1 - 7.3, 7.5 - 7.6 | |||
| Mar 30 | Linear Models 2 | MK: Sec. 8.1 - 8.3 | |||
| Apr 4 | Linear Models 3 | MK: Sec. 14.1 - 14.2, 14.4, 14.5 | |||
| Apr 6 | Nonlinear Models 1 | draft slides | HW6 out | ||
| Apr 11 | Nonlinear Models 2 | draft slides | MK: CH 7.2, Basis expansion, CH 14.5 (SVM), MK: CH 14.4.3 (Kernel Ridge), Neural net | ||
| Apr 13 | Clustering 1 | draft slides | notes, notes by Analytics Vidhya, MK: CH 11.1-11.4.1 | HW7 out, Final project out | |
| Apr 18 | Clustering 2 | slide | |||
| Apr 20 | Dimensionality reduction | slide | MK: 12.2.1, 12.2.3, 12.3 | ||
| Apr 25 | Advanced Machine Learning Algorithms | slide | random forest, recommendation, GAN | ||
| Apr 27 | Course Wrap-up 1 | ||||
| May 2 | Course Wrap-up 2 | draft slide | |||
| May 8 | Final Exam (3:30-5:30pm) |