COMP 5560 Data Mining Processes

Explores techniques for discovering patterns, correlations, and anomalies within large datasets.

About this course

Data Mining Processes explores techniques for discovering patterns, correlations, and anomalies within large datasets. This course builds on your foundation in statistical analysis and data visualization, moving from describing data to predicting future outcomes and uncovering hidden structures. You will work with industry-standard tools to clean, transform, and model data, gaining the practical skills needed to turn raw information into actionable insights.

You will learn to select the appropriate data mining technique for a given business problem, whether that involves segmenting customers, detecting fraud, or optimizing operations. The course emphasizes hands-on practice, with regular lab sessions where you apply algorithms to real-world datasets. You will also develop the ability to critically evaluate model results and communicate your findings effectively.

Who takes this course

• Data Analytics

Credits: 3 · Hours: 45

Prerequisites

• COMP 5370 Statistical Analysis for Data
• COMP 5180 Data Visualization Techniques

Learning outcomes

• Apply data mining algorithms such as clustering and classification to real-world datasets.
• Evaluate the effectiveness of different models using accuracy, precision, and recall metrics.
• Preprocess and clean raw data to prepare it for mining operations.
• Identify anomalies and outliers in complex data structures.
• Communicate findings and patterns to technical and non-technical stakeholders.

Evaluation