Document Type
Syllabus
Publication Date
Fall 9-1-2024
Course Description
Data mining is the effort to reach useful conclusions from data by building interpretive and predictive computational models. This course prepares students to do this through hands-on exploration of data preparation, and model development, tuning, and validation. This is done in the context of various algorithms such as gradient-descent, ensemble methods, and linear regression. Coursework includes multiple significant programming projects and a large final project.
Recommended Citation
Bible, Paul W., "CSC 370A Data Mining Bible Fall 2024" (2024). All Course Syllabi. 718, Scholarly and Creative Work from DePauw University.
https://scholarship.depauw.edu/records_syllabi/718
COinS
Student Outcomes
A student that successfully completes this course will be able to … • Apply standard techniques for transforming, summarizing, and visualizing data. • Understand some basic methods of statistical inference and their application in data modeling and analysis. • Understand techniques for learning from and modeling data including supervised and unsupervised learning. • Explain generalization and overfitting in the context of data modeling. • Analyze and evaluate different data models and tuning configurations using appropriate cross-validation techniques.