University College Dublin

This course examines the development of western popular music from the 1950s to the present day. Although the course content is arranged chronologically, the course is not an exhaustive survey. Rather, each week focuses on a selected genre or thread in modern popular music, from rock and roll to hip-hop to underground and dance music; by examining these genres and threads, students are introduced to theoretical frameworks by which they can analyze and understand the music in question. These frameworks include media theory, gender and performativity, and the critical examination of race and identity. The course also focuses more broadly on how popular music propagates itself over time via its relationship to technology, cultural and subcultural movements, and political currents. Although the course does introduce and employ a few basic musical-analytical concepts, it is an elective course and has no prerequisites.

This course is aimed at students with some previous programming experience, but not necessarily in Python. At the beginning, the course provides a "crash course" in the Python language. The remainder of the course covers a range of data science topics taught through Python, ranging from data collection and preparation, through to data analysis and visualization. Assessment for the course is based on individual project assignments which require programming.

Nowadays, parallel architectures are not only used for high performance computing. The advent of multicore processors, which can be found in all modern desktops, laptops, mobile, and embedded devices, has turned parallel architectures into the mainstream architecture for commodity computing. Correspondingly, parallel programming paradigm is becoming the predominant one in the mainstream programming practice. The course introduces parallel programming and covers the following topics: vector and superscalar processors: architecture and programming model, optimizing compilers (dependency analysis and code generation), array libraries (BLAS), and parallel languages (Fortran 90); shared-memory multi-processors and multicore CPUs: architecture and programming models, optimizing compilers, thread libraries (Pthreads), and parallel languages (OpenMP); distributed-memory multi-processors: architecture and programming model, performance models, message-passing libraries (MPI), parallel languages (HPF); and hybrid parallel programming for clusters of mutlicore CPUs with MPI+OpenMP.

This course charts the history of Northern Ireland from its foundation through state building, war, civil rights, sectarian conflict, and the peace process. Relative to its size, Northern Ireland is arguably the most studied and analyzed place on earth in the 20th century. Partition is by no means a phenomenon unique to Ireland. Germany, India, Korea, and Sudan are among the most prominent examples of a phenomenon that has been a major component of the 20th century world. The Northern Irish troubles witnessed the deaths of 3,636 people between 1966 and 1999. The conflict has been a defining moment in the modern histories of Northern Ireland, the Republic of Ireland, and Britain. In being a resolved conflict, the solution arrived at in 1998 has become a template for peace processes the world over. 1998 initiated a peace process rather than concluding a peace settlement. That peace has been at times unstable, fragile, and imperfect. This course progresses past the Good Friday Agreement, examining the history of near contemporary Northern Ireland to examine how power sharing, decommissioning, and cultural demobilization have shaped a new polity, asking what changed and what stayed the same.

Style in film for its own sake has little value. The real merit of film style is its ability to bring a film story to life in a distinctive audio visual manner. This course is an exploration of motion picture production and technique. Specifically, it addresses the core crafts of editing, cinematography, sound, production design, and directing. The course explores how these core crafts collaborate to shape what has become the most popular art form of our time.

This course brings together a discussion of sociological debates on inequality and latest empirical evidence to explore the gaps between rich and poor, included and excluded, advantaged and disadvantaged from a local, national, and global perspective. It encourages intersectional perspectives on different sources and forms of inequalities to highlight and challenge the assumptions on how they operate in contemporary societies. This course includes core sociological topics such as class, gender, and ethnicity and the emerging patterns of inequalities within social settings, such as education, income and wealth, health, citizenship, crime, and geography.

This course provides an introduction to the main areas of Linguistics and language study. It covers phonetics (the sounds used in human languages), phonology (the analysis of how sounds are organized in specific languages), morphology (how words are structured in languages), syntax (how phrases and sentences are made in languages), semantics (the study of meaning in words and phrases), and pragmatics (how meaning can be altered in context). It also provides an analysis of current theories of language acquisition.

This course presents important concepts of data mining and how these concepts are implemented and used in real-world applications. The course integrates the theory and practice of data mining with many references to real-world problems and cases to illustrate the concepts and the implementation issues throughout the lectures. The first chapter is devoted to a brief introduction to background information needed to understand the material. This is followed by data warehouse topics and how they differ from database concepts. The notion of data mining process is explained and how it relates to the complete KDD process, as it is very important to understand that data mining is not an isolated subject. The course reviews techniques used to implement data mining algorithms. The course then explores some core topics of data mining: classification, clustering, and association rules. Other concepts, such as prediction, regression, and pattern matching, are also covered, but viewed as special cases of the three core topics.

This course introduces the concepts of nutritional epidemiology, the methods employed to analyze the relationship between diet and nutrition status, focusing on specific nutrient deficiencies, dietary patterns, and growing chronic disease. The role of nutrition at each stage of the lifecycle is examined while considering approaches to promote health and prevent adverse health outcomes. The effect of policy on dietary intake is also considered and its impact on over and undernutrition in both developing and developed countries. Psycho-social and cultural factors influencing dietary intake are explored throughout the course particularly in the context of developing strategies for improving nutrition at the population level.