English

In this course, students develop their analytical and research skills, learning to work with physical and digital archives, objects, and performance ephemera and how to examine less tangible impacts of performance on history. Students develop more critical awareness of both the material and cultural traces of performance and their significance in both social and theatrical terms. In addition to the core learning objectives, this course develops historical awareness through case studies spanning three centuries of British theatre history; advance research skills by introducing students to a range of primary texts, material objects and secondary sources; and develop collaborative working skills.

This course analyzes the different steps of nervous system development during prenatal, postnatal, and adult life, and the pathological consequences of its alterations. Examples of key molecular and cellular processes are studied in several models (invertebrate, vertebrate, in vitro and organoids).

This course explores the development of intercultural competencies and the formation of a global vision. The course analyzes the identity of a nation through its cultural assets; observes the importance of cultural and artistic heritage in the integration of multiculturalism; implements aesthetic analysis on a cultural asset; identifies the organizations dedicated to the protection and safeguarding of heritage, and discerns the contexts and situations of risk in which the possession of heritage generates intercultural conflicts.

This course focuses on the cultural construction of revenge and revenge tragedy as a dramatic genre in the early modern period. Students engage with a thrilling and variously gruesome / funny / deeply moving play, not studied elsewhere on the program. The course spans the early modern period quite broadly, starting with translations of Seneca and Elizabethan attitudes toward revenge, and ending two-monarchs later on the Caroline stage. Typically, these plays enable students to explore, among other things: sexual revenge and gender politics; constructions of racial and national identity; ideas of parody and metatheatre; and madness and moral ambiguity. Students analyze both canonical and less well-known works to map the evolution of the genre. These plays present students with a limited author demographic, but the course draws on work by women and writers of color responding to early modern revenge drama, exploring performance (contemporary and early modern), adaptation and appropriation wherever possible. 

This course explores the various concepts, dynamics, debates, and challenges of cultural globalization. Most chapters start with a review of key writings and concepts that describe the process of globalization through a cultural lens. Guided by this understanding of culture, it questions the notion of globalization as largely the product of Western culture, modernity, and capitalism resulting in a worldwide, homogenized, consumer culture – a scenario often referred to as “McDonaldization.” The course focuses on diverse case studies to explore and discuss that possibility and also take into account emergent issues in relation to cultural globalization in the world we live in right now.

The course examines analytical and decision making skills in approaching practical and important social and business issues. In the course, students derive solutions or conclusions that require critical thinking, creativity, quantitative analysis, and common sense. Other course topics include: decision traps, quantitative decision models, statistical reasoning, computer tools, data-analysis techniques, and, more importantly, how these decision analysis concepts and tools can be applied in a broad set of social and business problems.

This course examines the multifaceted impact of artificial intelligence (AI) on contemporary society, exploring the intersection of AI's evolution with social issues such as personal identity, social relationships, privacy, surveillance, political order, the public sphere, mediatization, platformization, the attention economy, digital labor, and social polarization. Rather than uncritically embracing technology or relying on simple technological determinism, the course emphasizes the mutual shaping of AI and society.  

The course focuses on how AI creates new media environments and how individuals and communities adapt to, negotiate, and resist these changes. Students formulate critical and creative research questions suited to the AI era by engaging with diverse social theories and applying them to real-world cases. Students engage in in-depth discussions about the intricate relationship between AI and society and develop their own critical perspectives and research projects.  

Topics include AI-mediated social relationships, Interacting with AI, AI and privacy, AI and mediatization, AI and platform dependency, AI and surveillance, AI and disinformation, AI and attention economy, AI and digital labor, AI and social polarization.  

This course is a required course for Business Administration students.  Students grasp the big picture of how various academic knowledge learned in the field of business administration can be integrated and applied in practical settings. The course covers four authentic problem situations, both cooperative and conflicting types, that encompass major issues in the field of business administration at an introductory level, allowing students to explore various disciplines of business studies. This course is conducted using a competency-based, learner-centered teaching method that focuses on fostering team-based collaborative problem-solving skills. To address the presented problems, students engage in a series of learning activities, including self-directed learning and preparation, team discussions in a collaborative situation, team discussions and negotiations in a conflicting situation, and team presentations. 

This class surveys premodern Japanese art, looking at painting, sculpture, architecture, and material culture--particularly those related to Buddhism, kami worship, and Buddha-kami combinatory practices.

This course introduces the mathematical, statistical, and computational challenges in natural language processing. It covers the main applications of NLP techniques and a range of models in structured prediction and deep learning. Students gain a thorough introduction to cutting-edge machine learning and deep learning techniques for NLP. This course covers a broad range of topics including text classification, sentiment analysis, neural network, word embedding, sequence models, language models, machine translation, topic detection, and ChatGPT. The underlying techniques from probability, statistics, machine learning, transformer and deep learning are also introduced. Prerequisites: Pass in STAT2602 and COMP2119 or same level. Proficiency in Python.