Mastering Quantitative Techniques and Data-Driven Insights for Financial Decision Making
In this session, prospective students will gain an understanding of the Quantitative methods and data analysis in finance involve using mathematical models, statistical techniques, and computational tools to analyze financial data and inform decision-making. These methods help in risk assessment, portfolio management, pricing of financial instruments, and forecasting market trends, enabling data-driven strategies in finance.
Statistical Analysis
Mathematical Modeling
Risk Management
Data Interpretation
Financial Theories and Frameworks
Software Tools
Algorithmic Trading
Enhanced Digital Literacy
Increased Cybersecurity Awareness
Access to SEED Scholarship Fund
Application Fee Waiver
Located in the vibrant and dynamic city of Washington, D.C., the American University's Kogod School of Business has been shaping future business leaders since its founding in 1955. By harnessing the power of American University's renowned reputation, it offers cutting-edge graduate programs renowned for integrating artificial intelligence, sustainability, and STEM-designated tracks. All master's students benefit from Kogod's award-winning AI curriculum, with specialized courses and credentials in machine learning and business analytics. The school's sustainability-focused programs such as the MS in Sustainability Management and the MBA with ESG and climate strategy pathways equip students to lead in responsible business. STEM-designated options, including the MS in Finance, MS in Accounting, MBA, and MS in Business Analytics and AI, blend technical expertise with business skills, allowing international graduates to extend their stay and work in the US. Kogod School of Business distinguishes itself through comprehensive integration of artificial intelligence across all programs, offering over 20 AI-focused courses and credentials, including majors, minors, certificates, and badges. The Institute for Applied AI engages faculty from multiple disciplines, delivering immersive, real-world learning and ensuring students master both foundational and advanced AI skills applicable to diverse business careers.
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05 March 2026
9:00 PM IST (Asia/Kolkata)
10 February 2026
8:30 PM IST (Asia/Kolkata)
17 February 2026
8:00 PM IST (Asia/Kolkata)