English

This course examines a pertinent challenge of humankind: how to feed 12 billion people while maintaining the integrity and function of our planet. It challenges participants with contrasting viewpoints for a nuanced understanding of the multidimensional aspects of food production and consumption. Course participants explore the food debate as consumers and scholars, with focus on the science behind innovation of food and food systems, locally and globally. Course participants map the future of food and agriculture with view of the UN's Sustainable Development Goals.

This course focuses on understanding organizations in terms of structures, shared beliefs, identities and practices, concepts of efficiency and power and the implications of these insights for how we intervene to change organizations. The course helps students build their understanding of organizing beyond simplistic, functional frameworks and provides them with the necessary sociological and psychological concept to help them make sense of why organizations act in certain ways.

Reinforcement learning (RL) refers to a collection of machine learning techniques which solve sequential decision making problems using a process of trial-and-error. It is a core area of research in artificial intelligence and machine learning, and provides one of the most powerful approaches to solving decision problems. This course covers foundational models and algorithms used in RL, as well as advanced topics such as scalable function approximation using neural network representations and concurrent interactive learning of multiple RL agents.

This course consists of a survey and understanding of contemporary theories of justice. It engages with key texts as well as contemporary cases that reveal the key concepts and stakes of theorizing and practicing justice. Perspectives of Utilitarianism, Political Liberalism, Libertarianism, Communitarianism, Liberal Egalitarianism, Multiculturalism, Republicanism, and Feminism are covered. Students learn diverse approaches to justice and their theoretical foundations; learn how to analyze, understand, and critique contemporary political life through the lens of theories of justice and learn how to analytically and critically write argumentative essays on the topic of justice.

This course examines how art functions as collective expression of cultures, nations, and communities across history, and develops skills in visual literacy and analysis; image-based communication; and the psychology of visual perception.

This course explores major operations management techniques and how they are used to formulate competitive operations strategies. In addition, students are required to discuss how these operational strategies are applied to real-world problems. Through these discussions, students learn about various decision-making challenges that businesses face and how to address them using data-driven operational strategies. Topics include Review of EOQ Model, Review of Newsvendor Model, Applications of Newsvendor Model, Forecasting, Operations Optimization, Overview of Data Analytics, Descriptive Analytics, Review of Predictive Analytics, and Case Study in Operations and Application of Analytics Techniques.

Prerequisites: Production and Operations Management.

This course covers a range of areas within human biological sciences. The molecular, cellular, organ, and systems-based processes that link form and function are studied to provide an integrated overview. The course helps students consolidate and develop the skills required in human biology including in vitro and in vivo techniques, results analysis and presentation, interpretation of data, and statistics. 

This course offers a comprehensive exploration of scientific computing, covering essential topics crucial for solving mathematical problems encountered in scientific and engineering fields. Beginning with an introduction to the fundamentals of numerical methods, including error analysis and computational complexity, students explore solving systems of linear equations using various techniques such as direct and iterative methods. The course further aims to eigenvalue computation methods and approaches for solving nonlinear equations. Interpolation techniques for approximating functions from discrete data points are also covered in detail. Through hands-on exercises and computational assignments, students develop practical skills in numerical analysis, enabling them to tackle diverse mathematical challenges in scientific computing effectively.

Humans are a vital component of secure and private systems, they are also one of the most expensive components and the most challenging to reason about. In this course, students learn about how to create systems that are usable while still fulfilling their primary security or privacy mission. Students also learn about research topics such as designing user studies to critically evaluate interfaces and reading academic papers to create an academically-informed view of the topic.

We will cover the basic concepts in modern cryptography. The contents include one-way functions, encryption, pseudorandomness, digital signature, interactive protocols, zero-knowledge proofs, multiparty computation, homomorphic encryption, and program obfuscation.