Introduction to Finance Analytics

1.5 credits · GM

The purpose of this course is to give students a broad understanding of how artificial intelligence (AI) and machine learning (ML) can be used in financial analysis and decision-making. The emphasis is on helping students understand and apply modern analytical tools to extract information from financial data, identify patterns, generate predictions, and support investment and business decisions. The course format is a combination of examples, case studies, lectures, and hands-on applications. Potential topics include financial data sources, machine learning methods for financial prediction, natural language processing of financial documents and news, sentiment analysis, large language models (LLMs), financial forecasting, risk assessment, and AI-driven investment strategies. The course also examines the opportunities and limitations of AI and ML in financial applications, including issues of reliability, interpretability, and decision-making under uncertainty.