Data Mining Course | University of Utah | Prof. Jeff Phillips

Comprehensive data mining course covering statistical principles, similarity measures, clustering, classification, and real-world data analysis projects.

Introduction

This course covers the fundamental concepts and techniques of data mining, including statistical principles, similarity measures, clustering, classification, and more. Students will learn to apply these techniques to real-world data analysis projects.

Highlights

• Covers a wide range of data mining topics, from statistical foundations to advanced algorithms
• Utilizes both theoretical and practical approaches, including lectures, hands-on assignments, and a data analysis project
• Provides access to video recordings of all lectures for flexible learning
• Suitable for students with a background in computer science, mathematics, and statistics

Recommendation

This course is recommended for undergraduate and graduate students interested in data analysis and machine learning. It provides a solid foundation in data mining principles and techniques, and the opportunity to apply them in a real-world project. The course is suitable for students from various backgrounds, as long as they have a strong grasp of basic probability, linear algebra, and programming.