CYBR 5930 Machine Learning Basics

Introduction to algorithms for predictive data modeling.

About this course

This course introduces the core concepts and algorithms behind predictive data modelling. You will learn how to select, train, and evaluate machine learning models using real-world datasets. The focus is on practical application, teaching you to turn raw data into actionable insights.

You will work through supervised learning techniques, learning how to prepare data, train algorithms, and assess their accuracy. The course builds on the statistical foundations covered in CYBR 5820 Statistical Analysis, moving from theory to hands-on implementation.

Who takes this course

• Data Analytics

Credits: 3 · Hours: 45

Prerequisites

• CYBR 5820 Statistical Analysis

Learning outcomes

• Apply supervised learning algorithms to build predictive models
• Evaluate model performance using standard metrics and validation techniques
• Implement basic data preprocessing and feature engineering pipelines
• Interpret results to support data-driven decision-making

Evaluation