In this class, students will acquire hands-on experience in diverse aspects of the research process in any field of Biology, from familiarizing themselves with a research topic, generating interesting questions, designing experiments, acquiring technical skills, collecting and analyzing data, to writing and/or presenting their results. To inquire about enrollment, students should approach a Biological Sciences faculty member to identify mutual areas of interest. Typically, these conversations should occur well before registration, and the decision by the faculty member will depend on lab capac

In this class, students will acquire hands-on experience in diverse aspects of the research process in any field of Biology, from familiarizing themselves with a research topic, generating interesting questions, designing experiments, acquiring technical skills, collecting and analyzing data, to writing and/or presenting their results. To inquire about enrollment, students should approach a Biological Sciences faculty member to identify mutual areas of interest. Typically, these conversations should occur well before registration, and the decision by the faculty member will depend on lab capac

This course introduces the use of computational methods for studying culture and society. We will learn how to transform textual and visual material into data, and how we can explore and analyze this data using machine learning and statistical models as both quantitative and qualitative tools. We will also survey and discuss how these methods are applied within the humanities and social sciences, as well as reflect on the challenges, limitations, and ethical issues that arise in the computational study of culture and society.

This course introduces the use of computational methods for studying culture and society. We will learn how to transform textual and visual material into data, and how we can explore and analyze this data using machine learning and statistical models as both quantitative and qualitative tools. We will also survey and discuss how these methods are applied within the humanities and social sciences, as well as reflect on the challenges, limitations, and ethical issues that arise in the computational study of culture and society. This course counts as an Elective toward the INFORM major.

The course provides an introduction to machine learning algorithms and applications. Machine learning algorithms answer the question: "How can a computer improve its performance based on data and from its own experience?" The course is roughly divided into thirds: supervised learning (learning from labeled data), reinforcement learning (learning via trial and error), and real-world considerations like ethics, safety, and fairness.

Algorithmic systems are at the center of today's digital world, and mediate communication processes in areas as diverse as social media, journalism, healthcare, and governments. How do algorithmic systems capture, represent, and transmit information about everyday interactions? How do they shape, and are shaped by, social, cultural, and political life? What kind of new issues and concerns arise from their ubiquitous use? This course provides a critical introduction to algorithmic systems, and how they relate to issues of communication, power and inequalities in society.