The class includes lectures on concepts/frameworks related to information flows, stakeholder resistance, ecosystem dynamics, business models, operational workflows, and design thinking. There are also case discussions and guest lectures during which renowned practitioners come to share their experiences. Outside of class, students spend time in the field collecting data (e.g., interviews with patients and clinicians) and developing solutions to real-world problems.  For more information on the class: click here. 

This course provides the foundations of the qualitative traditions and methods and relevance for the new computational-qualitative methods, given the availability of digital trace data and computational tools. Students have to develop a research proposal, write peer reviews, and respond to reviewers’ comments. Link to syllabus and reading list. 

The course covers the fundamentals of the financial markets and available instruments and applies analytical tools to portfolio and credit risk management. Includes lectures, guest lectures, tutorials (application of financial models in Python, machine learning techniques), and projects (hands-on investing and risk management of SGD $1M in real time using simulation software).