English

This course introduces the comparative study of European politics, a comparative analysis of political institutions, and political behavior in Europe. On successful completion of this course, students are able to: Analyze politics in a comparative manner; Describe the differences between the political systems in operation across Europe; Identify the role played by political parties in parliamentary democracies; Assess the necessity of political parties and the functions they fulfil; Evaluate the merits of different electoral systems; Differentiate between the workings of different political systems; Assess whether politics can be analyzed via comparative methods; Evaluate the role of non-party actors in parliamentary democracies.

This course pays special attention to issues of theory and method in the psychology of religion, in order to develop an understanding of personal identity, as well as mental and spiritual health in religious contexts. While recognizing the importance of gender, class, race, ethnicity and other social forms of identity, the course focuses on religious dynamics of personal identity and the formation of selfhood through case studies in consciousness, mysticism, embodiment, intertextual reading practices and cultural resources for being human. The course explores the various ways in which religion might inform personal, social and intersubjective notions of self, while providing conception of the good/the good life. Course entry requirements: Second-year status.

This course introduces basic facts and theoretical models regarding economic interconnections within an increasingly integrated world. The course provides students a global view and understanding of interdependence among all countries. Its content includes a current and an historical overview of trade and its impact on economic growth, the classic theory of free trade, recent developments in theoretical models and relevant empirical evidence and major policy issues arising in open economies that are becoming more relevant today. The course covers traditional (neoclassical) economics and also discuss various challenges presented to such a framework, especially based on experience of developing countries.

This course focuses on how gender is socially, economically, and politically constructed in the community/society and how gender matters in addressing development. The course also addresses the kinds of policy and project interventions to achieve sustainable development and gender equalities.

This course forms part of the third-year major in Applied Statistics. It is an introduction to the study of Operational Research (OR) and explores fundamental quantitative techniques in the OR armamentarium with a strong focus on computer-based application. The course is intended for students in the applied statistics stream but may be taken as an elective by students in the mathematical statistics stream. Topics covered include linear and non-linear programming where students will learn to find optimal solutions by characterizing problems in terms of objectives, decision variables and constraints, decision making under uncertainty through decision trees, decision rules and scenario planning, Queueing Theory simulation through modelling the operation of real-world systems as they evolve over time. Course entry requirements: STA2030S or STA2005S; STA3030F is recommended.

This course presents a history of music in film by examining the development of key trends and significant composers from the "silent" era to the present day. It considers the place of music, and the soundtrack more generally, in the film production process and in terms of the relationship between composer and director. A focus on Hollywood, with its proclivity for bespoke orchestral scores, are supplemented by investigating a range of other styles (e.g. pop, jazz, electronica) and international (primarily European) examples. It provides an overview of the field while alighting upon case studies, for which fundamental theoretical concepts are introduced. Major mainstream film composers are featured alongside more experimental recent practitioners and composers better known for their work in the concert hall.

This course explores the chemistry and biochemistry of fermentation and microbial metabolism, with a focus on their applications in metabolic engineering and enzymatic conversion. Students examine current trends and industrial examples involving the production of food biomaterials, biofuels, chemicals, and bioplastics through microbial fermentation. Emphasis is placed on both fundamental principles and applied strategies for microbial process development. Students gain a comprehensive understanding of fermentation chemistry and acquire applied knowledge in microbial metabolic engineering for the production of value-added products such as food additives, industrial chemicals, and renewable biofuels. 

Prerequisites: Prior coursework in biochemistry and microbiology is strongly recommended. 

This course is designed to advance conceptual and applied understanding of bottom-up approaches in sustainability governance. Students are offered theories and concepts to understand the emergence and persistence of unsustainable practices and are equipped to propose which elements of these practices should change to achieve more sustainable outcomes. This regards individual and household practices, as well as the degree to which actions, rules, norms and values applied by governments, international bodies and private rule-making authorities like NGOs and companies are equipped to shape everyday practices. Be introduced to theories and concepts that address the interaction between everyday practices, transformations, systemic change and governance. Students are expected to have basic knowledge about social science theories of the environment, e.g. those presented in Social-Scientific Analysis of Environmental Issues (ENP24803).

This course explores mathematical concepts that are useful and frequently used in machine learning. Students examine linear algebra (vector spaces, scalar products, orthogonal vectors, matrices as linear mappings, determinants, eigenvalue and eigenvectors), analysis (differentiation), and probability theory (multidimensional probability distributions, calculations with expected values and variances). The class also discusses some contemporary applications of mathematics in machine learning.