MATH/COSC 3570 Introduction to Data Science (Spring 2026)
This schedule will be updated as the semester progresses, with all changes documented here.
| Week | Date | Topic | Materials | Lab Activity | AI Activity | Project |
|---|---|---|---|---|---|---|
| 1 | Tue, Jan 13 | Greetings; Overview of Data Science | 🖥️syllabus 🖥️overview | |||
| Thu, Jan 15 | Posit Cloud | 🖥️posit | 📋 posit 📋01 | |||
| 2 | Tue, Jan 20 | Git and GitHub | 🖥️git | 📋github | ||
| Thu, Jan 22 | Quarto: YAML and Markdown | 🖥️quarto | 📋02 📋03 | ✅ Team up! | ||
| 3 | Tue, Jan 27 | Quarto: Code Chunk | 📋04 | |||
| Thu, Jan 29 | R and Python Syntax | 🖥️syntax | 📋05 📋06 | Team up Due! | ||
| 4 | Tue, Feb 3 | R Tidyverse | 🖥️package | 📋07 📋08 | 🤖 AI Project Guideline | |
| Thu, Feb 5 | Python NumPy/Pandas | 📋09 | ||||
| 5 | Tue, Feb 10 | Data Importing | 🖥️import | 📋10 | ||
| Thu, Feb 12 | Data Visualization-ggplot2 | 🖥️ggplot | 📋11 📋Extra credit | |||
| 6 | Tue, Feb 17 | Data Visualization-categorical and numerical data | 🖥️visualization | 📋12 📋13 | Activity 1 | |
| Thu, Feb 19 | 🖥️interactive-viz | 📋14 (optional) | ||||
| 7 | Tue, Feb 24 | Data Wrangling - one data frame | 🖥️dplyr-1 | 📋15 | ||
| Thu, Feb 26 | Data Wrangling - two data frames | 🖥️dplyr-2 | 📋16 | elec_vote_y | ||
| 8 | Tue, Mar 3 | Mini Project 1 Presentation: Exploratory Data Storytelling | ||||
| Thu, Mar 5 | Data Wrangling - tidyr | 🖥️ tidyr | 📋17 | Activity 2 | ||
| 9 | Tue, Mar 10 | NO CLASS: Spring break | ||||
| Thu, Mar 12 | NO CLASS: Spring break | |||||
| 10 | Tue, Mar 17 | Probabilistic and Statistical Simulation | 🖥️probstat | 📋18 📋19 | ||
| Thu, Mar 19 | Linear Regression | 🖥️linear-regression | 📋20 | |||
| 11 | Tue, Mar 24 | Multiple Linear Regression | Activity 3 | |||
| Thu, Mar 26 | Mini Project 2 Presentation: Data Wrangling and Pipelines | |||||
| 12 | Tue, Mar 31 | Logistic Regression | 🖥️logistic-regression | 📋21 body.csv | Activity 4 | |
| Thu, Apr 2 | NO CLASS: Easter break | |||||
| 13 | Tue, Apr 7 | Logistic Regression; Data Splitting | 🖥️ K-Nearest Neighbors | |||
| Thu, Apr 9 | K-Nearest Neighbors | Activity 5 | ||||
| 14 | Tue, Apr 14 | Decision Trees | 🖥️ Decision Trees | 📋22 | ||
| Thu, Apr 16 | Principal Component Analysis | 🖥️Principal Component Analysis | ||||
| 15 | Tue, Apr 21 | Mini Project 3 Presentation: Supervised Learning | ||||
| Thu, Apr 23 | Principal Component Analysis | 📋23 | Activity 6 | 📂 Final Project Proposal Due | ||
| 16 | Tue, Apr 28 | K-Means Clustering | 🖥️K-means Clustering | |||
| Thu, Apr 30 | K-Means Clustering SDSS Conference | 📋24 | ||||
| 17 | Mon, May 4 | Final Project Presentation (10:30 AM - 12:30 PM) | 📂 Final Project Materials Due |
Dr. Yu reserves the right to make changes to the schedule.