English

This course goes beyond conventional lecture-based instruction and to the heart of the research process. Through hands-on scanning, data analysis, literature exploration, and seminar participation, students learn how MRI and fMRI are used to investigate the human brain – and apply knowledge to design, conduct, and present neuroimaging projects. The course integrates foundational concepts in neuroimaging and clinical neuroscience through hands-on, research-based learning. Through this process, students gain practical experience with MRI hardware and scanning, experimental design, basic image processing, and scientific writing and presentation.

This course covers systematizing organic reactions, examining the relationship between reaction mechanisms, molecular structure, reactivity, and chemical properties.  

Topics include Structure, reactivity, and mechanism, Energetics, Kinetics and investigation of mechanism, Strengths of acids and bases, Nucleophilic Substitution at a saturated carbon atom, Carbocations, electron-deficient N and O atoms and their reactions, Electrophilic and nucleophilic substitution in aromatic systems, Electrophilic and nucleophilic addition to C=C, Nucleophilic addition to C=O,  Elimination reactions, Carbanions and their reactions, Symmetry controlled reactions. 

The course considers the current theoretical conceptualizations of issues such as group decision making, performance, collaborative learning and intergroup conflict. Students look at the ways in which psychological theories relating to groups can be used to better understand and address issues across a range of applied settings, including the workplace and roles criminology graduates may enter. 

This course examines the experimental method in economics and explains how it differs from methods used in other social sciences. The course analyzes widely cited articles to illustrate best practices in experimental design and implementation. It evaluates the advantages and limitations of experiments relative to other empirical social science approaches, including the analysis of administrative data. The course also demonstrates how experiments test the robustness of the homo economicus assumption of a rational, self-interested decision-maker that underlies many economic models.

This course focuses on the interdisciplinary studies fields of public and global health, especially the contribution made to them by social sciences like political economy and medical sociology. The course addresses how our health is shaped by factors such as class, gender, race, profit-seeking behavior, climate change, and technology; it also questions what constitutes "medicine" and what role it plays in society, and how health policy shapes and is shaped by these considerations.

This course is a hands-on introduction to film and multi/new media production, focusing on fundamental techniques for creating effective presentations.

This course focuses on the philosophical issues which arise when the nature of aesthetic appreciation and judgement is considered. These are some of the questions which are discussed in the course: What is mimesis? Does art simply mirror nature? Is beauty merely “in the eye of the beholder”? What differences might there be between aesthetic appreciation of art and aesthetic appreciation of nature? What is the relation between art and society? What is the difference between the sublime and the beautiful? These and other questions are explored through the work of philosophers such as Plato, Aristotle, Hume, Kant, Dewey, Heidegger Foucault and Lyotard.

The course begins with quantum logic and examines how quantum advantages can be achieved in communication and computational tasks. Examples of quantum algorithms and quantum protocols are provided. Known approaches to implement quantum information processing are explained. Topics include Quantum logic state, dynamics, and measurements and observations, Quantum bit, fundamental theorems, Quantum logic gates and information processing, Quantum protocols, Quantum algorithm 1: the Deutsch algorithm, Entanglement, Quantum protocol 2: Pseudo-telepathy, Quantum computing concepts, Nonlocality.  

This course examines the main business areas of a modern full-service bank, including how banks generate profit across different activities, the principal risks they face, the methods used to manage those risks, and the ways in which the public can assess bank risk, evaluate performance, and understand the regulatory framework governing banking operations. The course focuses on (1) the financial statement analysis of banks and bank-like financial institutions, and (2) the accounting and disclosure rules for the financial instruments they hold, including interest rate risk disclosures, loan loss disclosures, fair value accounting for financial instruments, securitization accounting, derivatives and hedge accounting, and market risk disclosures. Analyzing these two aspects of a modern bank reveals much about the strategies followed by the bank given the various regulations under which it operates. The financial statements of financial institutions are increasingly based on fair value accounting and their financial reports include increasingly extensive risk and estimation sensitivity disclosures. Both fair value accounting and risk and estimation sensitivity disclosures are necessary ingredients for financial reports to convey financial institutions’ risk and performance in today’s world of complex, structured, value and risk-partitioning financial instruments and transactions. While financial institutions often report imperfect (or worse) fair value measurements and risk and estimation sensitivity disclosures, careful joint analysis of the information they do provide invariably yields important clues about their risks and performance.

This course introduces artificial intelligence (AI) applications, with particular attention to the current use of AI systems in the humanities. It reflects on the ethical implications of AI in teaching and learning contexts (e.g. for text production, translation, and language learning) as well as in a series of real-world cases. Contexts and cases focus on English language use, learning and teaching. The course introduces how generative AI systems work, including its reliance on the English language and Anglophone cultures, and the general issues covered in the course. The structure of the course consists of four blocks: bias, hallucinations and transparency; the workings of generative AI systems (LLMs and prompting), as well as data security and privacy; social inclusion and exclusion caused by the application of AI systems; and environmental impacts of using generative AI. Each block introduces students to a series of ethical issues surrounding AI use in the humanities and within the context of the English degree. These examples allow students to analyze the implications of AI in society. Throughout, important ethical issues concerning AI use are presented and critically discussed in class.