CS-401: Applied data analysisThis course teaches the basic techniques, methodologies, and practical skills required to draw meaningful insights from a variety of data, with the help of the most acclaimed software tools in the dat
CS-448: Sublinear algorithms for big data analysisIn this course we will define rigorous mathematical models for computing on large datasets, cover main algorithmic techniques that have been developed for sublinear (e.g. faster than linear time) data
CS-423: Distributed information systemsThis course introduces the foundations of information retrieval, data mining and knowledge bases, which constitute the foundations of today's Web-based distributed information systems.
MGT-416: Causal inferenceStudents will learn the core concepts and techniques of network analysis with emphasis on causal inference. Theory and
application will be balanced, with students working directly with network data th
COM-308: Internet analyticsInternet analytics is the collection, modeling, and analysis of user data in large-scale online services, such as social networking, e-commerce, search, and advertisement. This class explores a number
PHYS-435: Statistical physics IIIThis course introduces statistical field theory, and uses concepts related to phase transitions to discuss a variety of complex systems (random walks and polymers, disordered systems, combinatorial o
MATH-260(a): Discrete mathematicsStudy of structures and concepts that do not require the notion of continuity. Graph theory, or study of general countable sets are some of the areas that are covered by discrete mathematics. Emphasis
MATH-476: Optimal transportThe first part is devoted to Monge and Kantorovitch problems, discussing the existence and the properties of the optimal plan. The second part introduces the Wasserstein distance on measures and devel