This course will introduce the latest practices and technologies for managing big data. It will first compare and contrast big data to relational data in both operational and analytical data systems. It will then explore modern technologies (e.g., Spark and NoSQL), cloud computing (e.g., AWS), and reference architectures for retrieving, storing, integrating and analyzing big data. Finally, it will demonstrate big-data-enabled AI applications.

Drawing on social science research, this course explores how public leaders contribute to problem identification, issue framing, policy adoption, crisis management, and organizational and societal change. The course will clarify the relationships among key concepts including leadership and followership, authority and influence, reciprocity and persuasion, and examine the role of contextual factors in shaping the strategies of 21st century leaders

Many problems in data science essentially boil down to some mathematical relationships that are to be solved numerically. But have you ever wondered how computers could do math? This graduate-level data science course aims to cover fundamental topics of scientific computing, specifically selected and curated for data scientists, including numerical errors, root finding algorithms, numerical linear algebra, and numerical optimization.

Course shapes public leaders to recognize & respond to competing value propositions & implement value objectives in specific public context. Course goes beyond concrete incentive systems & aims to shape decisions, behavior, & expectations through social norms & organizational culture. Leaders in the public arena must appreciate competing value propositions & articulate & advocate for principles & standards of behavior.

Introduces the development of Brazilian culture from 1500 to the present. This course is taught in English and does not fulfill the language requirement.

Prototyping and Product Development is an action-oriented and project-based course. You and your team will identify a problem, develop multiple prototypes that address the problem, and test prototypes through iterative experimentation. Class sessions will be a mix of hands-on exercises, selected readings, and guest speakers. The majority of class time will be devoted to project work to help teams complete their prototypes.

We cover natural language processing, deep learning, and artificial intelligence to apply them to text and image data. You will learn algorithms that are the backbone of technologies used by Google and Tesla. You will also learn about Transformers, a revolutionizing concept that has caused a paradigm shift in artificial intelligence. In teams, you will compete with peers to develop the best predictive models to process and analyze text data.

This course introduces students to the underlying histories and theoretical dimensions of urban design as a creative spatial practice. By exploring a wide range of urban interventions at multiple scales, the course contextualizes contemporary design practice within the social, environmental, and political forces acting on the urban environment.

Combines topics in data ethics, critical data studies, public policy, governance, and regulation. Address challenges by topic (Health, Education, Culture & Entertainment, Security & Defense, Cities, Environment, Labor). Research how data-centric systems are deployed within socioeconomic ecosystems and shape the world. Interrogate connections between data science, governments, industry, civil society organizations, and communities.

This class examines how citizens, leaders, interest groups and activists work to reshape our understanding of problems over time and investigates why some problems gain policy attention while others languish. The class emphasizes the complexity of understanding, designing, and implementing large scale policies that attempt to address problems that are ultimately experienced by people in specific contexts and communities.