Focuses on statistical techniques and machine learning for risk analysis.

Teaches programming languages like R, Python, and SQL.

Covers predictive modeling, data visualization, and data mining.

Prepares students for emerging roles in actuarial data analytics.

Includes actuarial exam preparation relevant to data-driven roles.

Emphasizes real-world applications in insurance and finance sectors.

Integrates big data concepts and cloud computing tools.

Develops skills in handling large datasets and unstructured data.

Highlights ethical use of data and regulatory considerations.

Bridges traditional actuarial science with modern data science trends.