STAT 5 Statistics
This course provides an introduction to machine learning concepts, algorithms, and applications. Students will learn about supervised and unsupervised learning, model evaluation, and practical implementations.
Term: Spring
Location: Main Campus, Room 301
Time: Tuesdays and Thursdays, 10:00-11:30 AM
Course materials
| Week | Date | Topic | Materials |
|---|---|---|---|
| 1 | Data Cleaning and Preprocessing Techniques for handling missing values, outliers, and data transformation. | ||
| 2 | Data Cleaning and Preprocessing Techniques for handling missing values, outliers, and data transformation. | ||
| 3 | Data Cleaning and Preprocessing Techniques for handling missing values, outliers, and data transformation. | ||
| 4 | Data Cleaning and Preprocessing | ||
| 5 | Data Cleaning and Preprocessing | ||
| 6 | Data Cleaning and Preprocessing |