English

The course covers methods for data mining and business analytics and their usage in making strategic business decisions. It concentrates on the modelling aspects of data mining and provides tools for better understanding key methods of data exploration, visualization, classification, prediction, and clustering. The course starts with data visualization and getting to know features hidden in the data. Traditional regression models and hypothesis testing are practiced using real data. This introduction to traditional approaches then leads to the discussion of more advanced methods such as, discriminant analysis, classification and clustering methods, which are useful in finding patterns hidden in the data. The course deals with various types of data such as categorical data, time series, text data, and network data, among others. The fundamentals of building suitable models are discussed. Illustrations are carried out using the statistical package R. 

 

This course introduces students to photography as a tool for communication and encourages students to reflect critically on issues of form and content to convey meaning. Students will learn key technical processes in contemporary image making and consider existing photographic theories alongside emerging digital practices. Students will work individually to realise set exercises in and out of class and produce a completed series of images to a set brief.

This course begins by exploring the intellectual interventions and traditions that have emerged in the anthropology in and of Britain over the last 50 years, and then swiftly moves into exploring the ways in which interdisciplinary ethnographic research has been conducted across Britain. While reading ethnographies in cross cultural, global contexts, in this course students place a particular emphasis on the urban context of Greater Manchester. Students explore ethnographies that have been based on ethnographic research across Greater Manchester, and which raise and address urgent questions of social, political, and economic change in Manchester and beyond. The course tackles the concept of "the urban’" by exploring ethnographic examples from anthropology, sociology, human geography, and business studies that focus on social and cultural lives and relations. Students take two fieldtrips (Cheetham’s Library and Manchester Airport) and two walking tours (Fallowfield and Rusholme) to visit and reflect on the ethnographic locations of the materials and readings they engage with. 

Data science and machine learning are exciting new areas that combine scientific inquiry, statistical knowledge, substantive expertise, and computer programming. One of the main challenges for businesses and policy makers when using big data is to find people with the appropriate skills. Good data science requires experts that combine substantive knowledge with data analytical skills, which makes it a prime area for social scientists with an interest in quantitative methods. This course extends the foundation of probability and statistics with an introduction to the most important concepts in applied machine learning, with social science examples. It covers the main analytical methods from this field with hands-on applications using example datasets, so that students gain experience with and confidence in using the methods covered. 

The course consists of an integrated historical and a philosophical part. In the historical part, the period ca. 1900 until the present and concentrate on the development of biology as a separate scientific discipline, characterized by research programs that took shape over time is covered. In this section the following topics are reviewed Kant’s Critic of Judgment and the emergence of the teleological understanding of living beings; The Cuvier-Geoffroy debate and its influence in the development of Darwin’s theory of evolution; Darwin's theory of evolution; The rise of experimentalism in the nineteenth-century biology; The eclipse of Darwinism and discussion of neo-Lamarckism in early twentieth century; The emergence of the synthetic theory of evolution; The foundations of genetics and molecular biology; and The postgenomic turn in 21th century. The historical part ties in with several of the themes covered in the philosophical part. Some of the philosophical debates discussed in the class are Philosophy of biology and its relation to biology; The central concepts of Darwin’s theory of evolution; Adaptationist debate; Species, genes, race, classification, and taxonomies; Causality and explanation in biology; and Experimental biology and epistemic objects. The course includes lectures and tutorials. Participants are expected to have carefully read the required material and have completed the weekly assignment in advance of the meeting. The weekly assignment is a reading report or a critical question depending on the week. Entrance requirements included enrollment in a degree programme of the Faculty of Science.

In this course, students use probability theory to model uncertainty; design simple probabilistic models that facilitate prediction; conduct sound scientific analysis of data, and study the mathematical foundations of probabilistic modelling with Markov chains and simulation.

This course introduces key concepts and frameworks in public policy, focusing on how policies are formulated, implemented, and evaluated. It provides insights on how issues make it onto the political agenda; when and how public policies are made; how their effects can be assessed; what makes them successful; and how public policies can be compared. The course explores different types of policies, the policy instruments governments use to influence societal outcomes, and the factors that drive policy change or stability to familiarize students with analytical tools used in policy research. In doing so, the course also examines the challenges of addressing complex, "wicked" problems that confront governments with particular challenges. In addition to general theories and approaches in public policy research, the course introduces selected policy areas, such as health, education, environmental, and social policy. The course equips students with the tools to analyze policy processes, assess government effectiveness, and critically engage with real-world policy challenges.

This course focuses on the applications of game theoretical and empirical approaches to the understanding of contemporary political issues. During the lectures, students cover some seminal and some most recent models to think critically about the topics studied. In addition, they go over papers testing or related to the theories we cover. Students learn to assess critically the usefulness and limitations of theories and empirics alike. As such, this course allows students to understand how the tools they acquired in GV225 – Public Choice (or equivalent course) and GV249 – Research Design (or equivalent course) can be combined to study important political questions. Themes covered change every year as a function of current debates in the scholarly community and of pressing problems in the world at large. In recent years, the topics studied in the course have included, among others, populism, media and democracy, autocratic politics, terrorism. Questions covered during the lectures have included the sources of populists’ success, the effect of biased media on political outcomes, the role of violence in securing autocratic regimes, or the evaluation of counter-terrorist policies, among many others.

This course examines a variety of theoretical perspectives on the reasons why people commit crime, what constitutes crime, and how states respond to crime. Students explore a range of theories from classical and positivist approaches, to sociological theories, to feminist approaches, and contemporary research. The relevance of these theories to the case of Ireland, and aspects of criminal justice internationally are also assessed.