COMP 5490 Predictive Data Modeling

Utilizes machine learning algorithms to build models that forecast future trends based on historical data.

About this course

This course introduces the core principles of predictive analytics using machine learning. You will learn to prepare historical data, select appropriate algorithms, and build models that forecast future trends. The focus is on practical application, ensuring you can turn raw data into actionable insights.

You will work with real-world datasets to train models, tune parameters, and evaluate accuracy. The course also covers ethical considerations in data modeling, ensuring you understand the impact of your predictions on individuals and organizations.

Who takes this course

• Data Analytics (Graduate Certificate)

Credits: 3 · Hours: 45

Prerequisites

• COMP 5560 Data Mining Processes

Learning outcomes

• Apply supervised and unsupervised machine learning techniques to structured datasets.
• Evaluate model performance using appropriate metrics and validation strategies.
• Deploy predictive models to support data-driven decision-making in business contexts.
• Communicate model limitations and ethical considerations to non-technical stakeholders.

Evaluation