3 credits
Fall 2025 Lecture Distance Learning Upper Division
This course will introduce students to the field of data mining and machine learning, which sits at the interface between statistics and computer science. Data mining and machine learning focuses on developing algorithms to automatically discover patterns and learn models of large datasets. This course introduces students to the process and main techniques in data mining and machine learning, including exploratory data analysis, predictive modeling, descriptive modeling, and evaluation.
Learning Outcomes1Identify key elements of data mining and machine learning algorithms.
2Understand how algorithmic elements interact to impact performance.
3Understand how to choose algorithms for different analysis tasks.
4Analyze data in both an exploratory and targeted manner.
5Implement and apply basic algorithms for supervised and unsupervised learning.
6Accurately evaluate the performance of algorithms, as well as formulate and test hypotheses.
Prerequisites
Restrictions
made by Purdue students.