Prerequisites

• Proficiency in programming (Python or R).
• Knowledge of statistics and data preprocessing techniques.
• Familiarity with machine learning concepts and tools.

Course Objective

The course is designed to equip participants with knowledge on skills on machine learning models for financial
applications. Specifically at the end of the course, participants will be able to:
1. Build and evaluate machine learning models for financial applications.
2. Develop end-to-end workflows for ML applications in finance.
3. Deploy and monitor ML models in production systems.
4. Address ethical and regulatory considerations in financial AI.

Course Outline

• Introduction to Machine Learning in Finance
• Supervised Learning Models
• Unsupervised Learning Models
• Advanced Machine Learning Techniques
• Deployment and Monitoring
• Capstone Project and Ethical Considerations

Duration: 5 days

Target Audience: Data scientists, analysts, IT professionals in finance