CHEME 4/5660: Financial Data, Markets, and Mayhem for Scientists and Engineers
A quantitative finance course that teaches scientists and engineers to make quantitative financial decisions in corporate and wealth management contexts. The course employs methods from engineering, statistics, AI, data science, and machine learning to examine and enhance financial systems and decision-making. Topics include quantitative asset pricing models, risk management, and portfolio optimization using real-time and static data.
CHEME 4/5800: Principles of Computational Thinking for Engineers
Engineering practice increasingly relies on computational tools and data analysis. This course integrates data science, statistics, linear algebra, artificial intelligence, and mathematical modeling using the Julia programming language. Students master software engineering paradigms, data structures, algorithms, and apply machine learning tools to analyze scientific and engineering datasets with weekly labs using real-world industrial data.
CHEME 5/5820: Machine Learning and Artificial Intelligence Methods for Engineers
An introduction to machine learning with emphasis on supervised learning in engineering contexts. Topics include regularized linear models, boosting, kernel methods, deep learning approaches, generative modeling tools, decision-making in stochastic systems, and reinforcement learning. Students implement methods with real datasets and develop understanding of applicability and limitations.
Professional Education
eCornell Certificate in Quantitative Finance
An online certificate program teaching computational finance using the Julia programming language. Students learn to analyze financial instruments, model risk, optimize portfolios, and build automated trading systems through hands-on practical learning. The six-course sequence covers fixed income securities and Treasury bond pricing, equity asset pricing using stochastic models, options pricing and derivatives, portfolio optimization and allocation strategies, and machine learning applications in financial decision-making.
eCornell Certificate in AI in Finance
A professional certificate preparing financial professionals to apply AI technologies in their field. The program progresses from AI fundamentals and tools through real-world applications in investment research, credit risk, fraud detection, and client engagement, to responsible AI principles and strategic leadership for organizational adoption. Features Cornell faculty alongside industry practitioners from leading financial firms.