CH923: Statistics for Data Analysis

The main aim of the module is to provide an understanding of the fundamental principles of mobile robotics and related concepts. The module introduces various mechanisms of mobility for different kinds of mobile robots, algorithms and data structures for safe navigation of the robot, and some techniques for equipping the robot with an intelligent vision system.

The module is primarily addressed at Computer Scientists and Computer Systems Engineers, but it is also taken by Electrical Engineers, Physicists and Mathematicians, so the learning outcomes may vary. After successful completion of this module, students should be able to demonstrate an understanding of the underlying principles of mobile robotics, a knowledge of its applications, and apply these to analyse and solve related real-world problems.

The course will provide students with a detailed knowledge of the New Keynesian model which provides the foundation for the macroeconomic policy models used in the worlds leading central banks. The course will also equip students with modern econometric techniques with which to investigate macroeconomic data, to assess the adequacy of theoretical models and to pose new questions. The New Keynesian approach will be briefly placed in the wider literature of optimizing rational agent models, with some discussion of the evolution from the Real Business Cycle to models with nominal rigidities. Modern topics are likely to include credit frictions and policy at the zero lower bound. Key skills developed include intertemporal optimisation and Structural VAR analysis. 

This course takes you through all the things you need to know in order to use the 2000FX TEM, from the principles of its operation and where different controls are found, to the alignments needed to get good data.

There is a quiz at the end of the course and you will need to pass this test before progressing to hands-on training.

There is an accompanying lecture, held once a term, to give more context and detail.

There is also a booklet describing the different alignments that you should have received in the email notifying you that you are on this course. It can be downloaded from http://www2.warwick.ac.uk/fac/sci/physics/research/condensedmatt/microscopy/em-rtp/training.

ES94N-20/21 FTMSc

FTMSc 19/20

FTMSc 18/19

FTMSc ES94N

FTMSc - ES94N-16/17

ES94N01MCS

ES94N02SI-18/19

This module provides the opportunity to integrate and apply the knowledge and understanding gained in the other core modules of the programme and demonstrate the skills required of professional engineers in an industrial context.

This is by means of a group design project, which is inspired by an industrial partner and prepares students for professional practice. The project provides experience of team working whilst being assessed on an individual basis. Students will integrate their knowledge and understanding in order to specify and solve a complex engineering problem (or user need) related to tunnelling, through the creation and development of a designed infrastructure or system. The project also allows students to develop their understanding of project management, time management, ethics, sustainability and environment, health and safety and risk. Students will develop effective communication and leadership skills and are encouraged to reflect upon the skills they have and are developing.

By the end of the module a student should be able to:

• Extrapolate existing knowledge and experience and apply them in an integrated systems approach to solve a complex and unfamiliar engineering problem
• Extract and critically evaluate relevant data in order to apply engineering analysis and advanced problem solving skills, in order to complete an engineering project to the satisfaction of a customer and/or user
• Use innovative techniques, materials or methods in delivering the project.
  
• Consider the wider context of the project including, risk, ethics, environmental and sustainability limitations, intellectual property rights, codes of practice and standards, health and safety and liability, to inform the project specification (problem brief) as relevant to the project.
  
• Plan and manage a project from the initial brief to a deliverable outcome
  
• Demonstrate effective communication, both verbal and written, to a technical and non-technical audience.
  

This module provides intensive instruction in six core domains of linguistics: phonetics, phonology, morphology, syntax, semantics, and pragmatics. It expands substantially on concepts you were introduced to during ET118: Linguistics: Understanding Language. You will work from a wide-range of language data to develop your knowledge of findings, theories, and methodologies from these domains. You will build core disciplinary knowledge that is essential to any field of linguistic inquiry, and establish a necessary foundation for advanced linguistic research.

This module provides intensive instruction in six core domains of linguistics: phonetics, phonology, morphology, syntax, semantics, and pragmatics. It expands substantially on concepts you were introduced to during ET118: Linguistics: Understanding Language. You will work from a wide-range of language data to develop your knowledge of findings, theories, and methodologies from these domains. You will build core disciplinary knowledge that is essential to any field of linguistic inquiry, and establish a necessary foundation for advanced linguistic research.

This module engages you in empirical studies of real-world speech communities. You will describe regional and social dialects of English in Britain, and work in emerging approaches to dialectology in English as a lingua franca and “new” Englishes. You will gather language data through a variety of methodologies, including collecting written surveys, conducting face-to-face interviews, and datamining social media. You will deepen your knowledge about types of language change, motivations for it, and models to describe it. You will be challenged to create high-quality research outputs that advance knowledge, and hone qualitative and quantitative analytic skills that will be essential to your dissertation and other linguistic work.

This module engages you in empirical studies of real-world speech communities. You will gather language data through a variety of methodologies, including collecting written surveys, conducting interviews, and datamining social media. You will deepen your knowledge about types of language change, motivations for it, and models to describe it. You will be challenged to create high-quality research outputs that advance knowledge, and hone qualitative and quantitative analytic skills that will be essential to your dissertation and other linguistic work.

With an emphasis on the development of students’ scientific skills, this module will focus on competences such as evidence based reasoning, the application of quantitative analysis to interpret chemical data and the evaluation of experimental design. Chemistry is an evidence based science discipline and there will be a strong experimental element to this module. In this progressive module students will also look at how Chemical applications can be used to solve societal problems. Students undertaking this module will develop the academic experience required for a range of undergraduate science programmes, including chemistry and chemical engineering.

This module offers an in-depth examination of Sustainable Development Goal 3 (“good health and well-being”) and the broader field of global health. The module will involve a blend of conceptual foundations, case study analysis, and work with real-life qualitative and quantitative data. Teaching and case studies will be interdisciplinary, drawing on medical as well as social science research.

This module offers an in-depth examination of Sustainable Development Goal 3 (“good health and well-being”) and the broader field of global health. The module will involve a blend of conceptual foundations, case study analysis, and work with real-life qualitative and quantitative data. Teaching and case studies will be interdisciplinary, drawing on medical as well as social science research.

In the era of networks, big data and the digital turn, traditional objects, such as documents, pictures, data, groups, events or patterns, open up to new methods of research. Emerging digital research methods also become means through which such objects are sustained, thus co-creating dynamic objects, such as networks, databases, platforms, data visualizations, maps and many other new forms of social, cultural and public life. This module offers an insight into these new and emerging societal and cultural entities and methodologies.

For further information please contact cim@warwick.ac.uk or go to https://warwick.ac.uk/fac/cross_fac/cim/apply-to-study/cross-disciplinary-postgraduate-modules/im904-digital-objects-digital-methods/

In the era of networks, big data and the digital turn, traditional objects, such as documents, pictures, data, groups, events or patterns, open up to new methods of research. Emerging digital research methods also become means through which such objects are sustained, thus co-creating dynamic objects, such as networks, databases, platforms, data visualizations, maps and many other new forms of social, cultural and public life. This module offers an insight into these new and emerging societal and cultural entities and methodologies.

For further information please contact cim@warwick.ac.uk or go to https://warwick.ac.uk/fac/cross_fac/cim/apply-to-study/cross-disciplinary-postgraduate-modules/im904-digital-objects-digital-methods/

Urban science is a rapidly growing field that investigates the way people interact within and are influenced by urban systems. It is dedicated to harnessing the wealth of social information available in our modern information society. In this way, urban science uses large amounts of heterogeneous data to better understand cities and other types of complex urban systems, as well as the integration of new technologies with them.

The aim of this module is to present the theoretical and practical methodological and substantive foundations of urban science.

For further information please contact cim@warwick.ac.uk or go to https://warwick.ac.uk/fac/cross_fac/cim/apply-to-study/cross-disciplinary-postgraduate-modules/im913-urban-science/

This module introduces the rapidly growing field of urban science with a focus on concepts and methods for understanding modern cities and the integration of emerging technologies in the urban space. It provides a broad and systematic exposure to a range of topics and methods on urban science with emphasis given to spatial analysis.

This is achieved through the combination of three inter-related components:

1. theoretical foundations of urban science;

2. a methodological approach to the urban space with emphasis to theory and methods for spatial analysis; and

Cities have traditionally adapted to the raise of new technologies, like cars or telephones, for instance. Nowadays, digital technologies and data in particular are transforming the material, cultural, social and political spheres of the urban realm.

These transformations require new theories and research methods to understand the spaces, scales, and agents involved in the relationships between data and the urban. This module offers an insight into some of these current theories and methodologies, to question the notion of data itself, to challenge controversial notions like the smart city, and to expand the realms of inquiry of urban data.

For further information please contact cim@warwick.ac.uk or go to https://warwick.ac.uk/fac/cross_fac/cim/apply-to-study/cross-disciplinary-postgraduate-modules/im919-urban-data/

Cities have traditionally adapted to the raise of new technologies, like cars or telephones, for instance. Nowadays, digital technologies and data in particular are transforming the material, cultural, social and political spheres of the urban realm.

These transformations require new theories and research methods to understand the spaces, scales, and agents involved in the relationships between data and the urban. This module offers an insight into some of these current theories and methodologies, to question the notion of data itself, to challenge controversial notions like the smart city, and to expand the realms of inquiry of urban data.

For further information please contact cim@warwick.ac.uk or go to https://warwick.ac.uk/fac/cross_fac/cim/apply-to-study/cross-disciplinary-postgraduate-modules/im919-urban-data/

Visualisations have become a fundamental currency for the exploration of data and the exchange of information. In this module we will explore this highly interdisciplinary subject from a wide variety of views - from cartography to statistics, to architecture and information design, and from science to the arts. Some of the labs and activities will involve coding and sketching activities, but there are no pre-requisites for this course. We encourage students from diverse backgrounds to bring their own perspective and skills to this exciting and interdisciplinary topic.

For further information please contact cim@warwick.ac.uk or go to https://warwick.ac.uk/fac/cross_fac/cim/apply-to-study/cross-disciplinary-postgraduate-modules/im921-visualisation/

Visualisations have become a fundamental currency for the exploration of data and the exchange of information. In this module we will explore this highly interdisciplinary subject from a wide variety of views - from cartography to statistics, to architecture and information design, and from science to the arts. Some of the labs and activities will involve coding and sketching activities, but there are no pre-requisites for this course. We encourage students from diverse backgrounds to bring their own perspective and skills to this exciting and interdisciplinary topic.

For further information please contact cim@warwick.ac.uk or go to https://warwick.ac.uk/fac/cross_fac/cim/apply-to-study/cross-disciplinary-postgraduate-modules/im921-visualisation/

Syllabus

Week 1 – Introduction: Genealogies of the Interface

Week 2 – The Interface as Socio-Technical Assemblage

Week 3 – What is a User?

Week 4 – [Graphics] – The Operational Image

Week 5 – [Workflow] – Governance of Actions

Week 6 – [Processing] – Time and Cognition

Week 7 – [Analytics] – Trace Data, Optimization and Social Media Platforms

Week 8 – [Storage] – From Web Archives to Digital Folklore

Week 9 – Conclusion: The Mediation of Behaviour 

For further information please contact cim@warwick.ac.uk or go to https://warwick.ac.uk/fac/cross_fac/cim/apply-to-study/cross-disciplinary-postgraduate-modules/im923-user-interface/

The module is aimed at introducing interdisciplinary perspectives on current challenges faced by cities and urban science, in order to develop a critical understanding of the role of digital technologies, big data and urban analytics for promoting sustainable urban development in “smart city” initiatives worldwide. This is achieved through a series of invited talks featuring both academic and professional experts, which is accompanied by a discursive seminar. 

For further information please contact cim@warwick.ac.uk or go to https://warwick.ac.uk/fac/cross_fac/cim/apply-to-study/cross-disciplinary-postgraduate-modules/im927-digital-cities/

This intensive module is aimed at introducing the topics of disaster risks and urban resilience with an emphasis on the use of innovative digital technologies to gather and analyse urban data for improving disaster resilience. It approaches, theoretically and practically, the main issues involved in disaster resilience and the way in which social media, mobile technologies and the web 2.0 are related to our collective experience of disasters and crisis events. By means of a practical project and field work conducted in the city of Coventry, students will learn how to collect urban data using open-source mobile data collection software (OpenDataKit), process and analyse this data with Geographic Information Systems (QGIS) and produce an interactive digital map to visualise urban aspects related to disaster resilience. 

For further information please contact cim@warwick.ac.uk or go to https://warwick.ac.uk/fac/cross_fac/cim/apply-to-study/cross-disciplinary-postgraduate-modules/im928-urban-resilience/

This module serves as an interdisciplinary introduction to contemporary machine learning research and applications, specifically focusing on the techniques of deep learning which use convolutional and/or recurrent neural network structures to both recognize and generate content from image, text, signals, sound, speech, and other forms of predominantly unstructured data. Using a combination of theoretical/conceptual/historical analysis and practical programming projects in the R programming language, the module will teach both the basic application of these techniques while also conveying the historical origins and ethical implications of such applications.

For further information please contact cim@warwick.ac.uk or go to  https://warwick.ac.uk/fac/cross_fac/cim/apply-to-study/cross-disciplinary-postgraduate-modules/im931-interdisciplinary-approaches-to-machine-learning/

This module serves as an interdisciplinary introduction to contemporary machine learning research and applications, specifically focusing on the techniques of deep learning which use convolutional and/or recurrent neural network structures to both recognize and generate content from image, text, signals, sound, speech, and other forms of predominantly unstructured data. Using a combination of theoretical/conceptual/historical analysis and practical programming projects in the R programming language, the module will teach both the basic application of these techniques while also conveying the historical origins and ethical implications of such applications.

For further information please contact cim@warwick.ac.uk or go to  https://warwick.ac.uk/fac/cross_fac/cim/apply-to-study/cross-disciplinary-postgraduate-modules/im931-interdisciplinary-approaches-to-machine-learning/

Syllabus

Week 1: Art, media, and activism—how we got to today (lecture and seminar)

Sets the scene through a brief history of art- and media-activist practices leading up to today, examining the impact of social and technological change; also looks at the impact of networks on art’s autonomy, and the relation between theory and practice, as well as the specificity of the digital as a medium

Week 2: Capital, labour, and value in a digital age (lecture and seminar)

Looks at the ways contemporary political economy has been theorized, together with the possibilities and difficulties that communicative capital poses for organising, popular resistance, and subversive artistic praxis

Week 3: Tactical media, performance, design (lecture and seminar)

Looks at a variety of critical and aesthetic interventions, including electronic civil disobedience, DOS attacks, cybersquatting, Floodnet applications, tactical cartography and visualization, and so forth; also looks at the media activism as performance and aesthetic practice the role of art and design in critical media interventions, especially the role of speculative design fiction

Week 4: The Twitter Revolution (lecture and seminar)

Looks at the role of social media activism in protests and unrest in Moldova, Iran, and the Arab spring examining the relation between twitter and the streets, and the limits and possibilities of digital participation

Week 5: Media squares (lecture and seminar)

Looks at technologies of communication and participation in the Occupy, 15-M and Nuit Debout movements, examining the relation between digital and real-world organising, as well as connections between smart mobs and DIY artistic production

Week 7: Designing media activism (workshop)

In-class crits with pecha kucha presentations of group design projects

Week 8: Digital populisms and far-right co-options (lecture and seminar)—with visiting speaker Dr Paolo Gerbaudo (KCL)

Looks at the use of digital strategies by populist movements today, such as the gilets jaunes, and at the appropriation of critical and tactical-media approaches by the far right, evaluating the political ramifications of these developments for the theory and practice of media activism

Week 9: Digital parties and democratic reformations (lecture and seminar)

Looks at how digital technologies are transforming democratic forms and institutions, with a focus on the potential for social media to reconfigure representation and the relation between leader and base, and on how big data is changing campaigning

Week 10: Whither media activism? (workshop)

A hands-on exploration of online interventions, micropractices, and design fictions that speculate about or advocate for digital futures.

For further information please contact cim@warwick.ac.uk or visit https://warwick.ac.uk/fac/cross_fac/cim/apply-to-study/cross-disciplinary-postgraduate-modules/im933-media-activism/

This module introduces students to the fundamental techniques, concepts and contemporary discussions across the broad field of data science. With data and data related artefacts becoming ubiquitous in all aspects of social life, data science gains access to new sources of data, is taken up across an expanding range of research fields and disciplines, and increasingly engages with societal challenges. The module provides an advanced introduction to the theoretical and scientific frameworks of data science, and to the fundamental techniques for working with data using appropriate procedures, algorithms and visualisation. Students learn how to critically approach data and data-driven artefacts, and engage with and critically reflect on contemporary discussions around the practice of data science, its compatibility with different analytics frameworks and disciplinary, and its relation to on-going digital transformations of society. As well as lectures discussing the theoretical, scientific and ethical frameworks of data science, the module features coding labs and workshops that expose students to the practice of working effectively with data, algorithms, and analytical techniques, as well as providing a platform for reflective and critical discussions on data science practices, resulting data artefacts and how they can be interpreted, actioned and influence society.

This module uses transdisciplinary Problem-Based Learning approaches to support students to generate problems arising from a range of narratives about the end of the world, and to consider how these problems reflect complex concerns about individuality, morality, the social contract, and the afterlife. Beginning with historical mythological narratives and encompassing religious, political, and ecological apocalyptic theories and scenarios through to the modern day, this module will encourage students to think in transdisciplinary ways about the roles played by apocalyptic narratives in historical and modern societies. The module will make use of literary, religious, philosophical and historical texts, films, music, images, environmental science data, news and social media, and political narratives to encourage students to develop comparative analytical skills and think across disciplinary boundaries.

This module provides an overview of the main contemporary issues in international development law and human rights. It provides an introduction to topics that all students are expected to have an understanding of and thus provides the background for all modules and the dissertation. Students who read and understand the module materials are more likely to achieve higher grades. Group work is an important part of the module as experience shows that participatory study is a successful pedagogical method.

Module Aims

Module Aims

LL336 French 3 for finalists is a combination of: 

LL236 French 3 - 2 hours in person Thursday 1– 3 pm

+ An independent project component. 

For the language content of this module, all information, links and submissions are on Moodle LL236: Course: LL236:French 3 | Moodle@Warwick

For the independent project, incl. the workshops, all information, links and submissions are on Moodle Independent project for finalists: Course: Independent project for finalists | Moodle@Warwick

LL343 French 5 for finalists is a combination of: 

LL209 French 5 -  2 hours in person Wednesday 10am – 12 pm

+ An independent project component. 

For the language content of this module, all information, links and submissions are on Moodle LL209: Course: LL209:French 5 | Moodle@Warwick

For the independent project, incl. the workshops, all information, links and submissions are on Moodle Independent project for finalists: Course: Independent project for finalists | Moodle@Warwick

For the independent project, incl. the workshops, all information, links and submissions are on Moodle Independent project for finalists: Course: Independent project for finalists | Moodle@Warwick 

LL364 module title is a combination of: 

LL264 module title -  3 hours in person Tuesday 2-5pm, Wednesday 1-3pm + Thursday 4-5pm or Fridays 12-1pm + 2-4pm 

+ An independent project component. 

For the language content of this module, all information, links and submissions are on Moodle LL264 

For the independent project, incl. the workshops, all information, links and submissions are on Moodle Independent project for finalists: Course: Independent project for finalists | Moodle@Warwick 

https://www.mathematical-modelling.science/index.php/lectures/warwick-2020-2021

Topological Data Analysis (TDA) is an approach to data analysis based on techniques from algebraic topology. Topology is the study of properties of sets that are invariant under continuous deformations; it is concerned with concepts such as ``nearness'', ``neighbourhood'', and ``convergence''. Nowadays, topological ideas are an indispensable part of many fields of mathematics, ranging from number theory to partial differential equations. Algebraic topology, in particular, aims to understand topological properties of spaces through algebraic invariants. The premise of topological data analysis is that data there is an underlying topological structure to data. Familiar examples include clustering, where the aim is to subdivide data into different clusters, or ``connected components'', and connectivity in networks. In this module we introduce persistent homology, a powerful method for studying the topology of data. We discuss the theoretical foundations, as well as computational and algorithmic aspects and various applications. While the course is mainly theoretical in nature, you are encouraged to experiment using a range of available software and applications. The lecture material will be available as video recording and slides, and exercises will be published semi-regularly.

Intended Learning Outcomes

Upon completion of this module you should be able to:

• understand how topological information can be extracted from discrete data;
• use persistent homology to compute persistence diagrams and barcodes;
• explain the different parts of the persistent homology pipeline and the computational challenges involved;
• evaluate the stability and robustness of persistent homology computations;
• summarize different approaches to the topology of data and discuss applications

Literature

1. Steve Oudot. Persistence Theory: From Quiver Representations to Data Analysis. AMS 2015
2. Herbert Edelsbrunner and John Harer. Computational Topology, An Introduction. AMS 2010
3. Nina Otter, Mason A Porter, Ulrike Tillmann, Peter Grindrod & Heather A Harrington. A roadmap for the computation of persistent homology. 2017

More specialised sources and papers will be made available in time.

MD913 

This module will help you to gain a systematic understanding of the key issues in the design, statistical analysis and interpretation of the common types of epidemiological study.

• This module builds on the material covered by the module Epidemiology and Statistics (a prerequisite unless you can show evidence of equivalent knowledge/expertise), allowing you to further develop your research skills
• Learn about issues in the design, analysis and interpretation of: case-control studies; cohort studies; randomized controlled trials; and trial data meta-analyses
• Also, other practical issues in common epidemiological study designs (such as survey methods)
• This further module is of particular relevance to those studying a Masters in Public Health (MPH) and an MSc Research Methods in Health Sciences for whom Epidemiology and Statistics is a core module.

Welcome to the Research Methods in Clinical Education Module.

This module aims to ensure that you have a critical understanding of research methodology appropriate to clinical education, including qualitative, quantitative, multi-/mixed methods and ethical considerations.

You will need to draw on knowledge and skills from past modules, especially learning theories and your understanding of effective learning environments.

The Physical Biology of the Cell module is a core module of the MSc IBR, which underpins the MRC-funded IBR DTP.

The module aims to provide a physical sciences perspective to cellular biology and equip postgraduate students to begin a research career at the interface of biology and physics.

You will explore the basic physical concepts underlying the behaviour of biomolecules, dynamic cell processes, cellular structure and signalling events. You will learn how to estimate sizes, speed and energy requirements for a variety of biological processes and build simple explicit models to fit experimental data from cell biological experiments.

PBoC is about learning to ask and answer quantitative scientific questions in the realm of biophysical cell biology.

It is arguably possible to sask scientific questions that are not quantitative*, but in general, useful scientific ideas make quantitative predictions that can be tested by observation and experiment. And arguably again, the most powerful scientific ideas are those that make the firmest quantitative predictions, and can thereby be definitively disproved.

Our goal with this course is to equip you with a basic set of tools to think quantitatively about the biological world, design better (more incisive) experiments, and analyse and interpret your data in useful and formally correct ways.

On completing the module, you should be able to analyse and quantify physical biological properties and behaviours of living systems; formulate scientific questions by harnessing the core concepts of physical biology and design experiments that effectively address your scientific questions.

PBoC is designed to help you to think!  Your instructors will aim to make the material challenging, but accessible, and above all, interesting.

ST221 covers concepts and methods of statistical modelling and model exploration. After this module you should be able to 

• explain the theoretical background of linear statistical models and their extensions;
  
• fit a model to a given data set using R and interpret the resulting output;
  
• define, explore, evaluate and improve a fitted model. 
  

FTMSc 19/20

FTMSc - WM00H-16/17

FTMSc WM00H

WM00H-20/21 FTMSc

FTMSc 18/19

Dyson

WM919-18/19 FTMSc

WM919-20/21 FTMSc

FTMSc 19/20

WM931-20/21  FTMSc

FT MSc 22/23

WM931-19/20 FTMSc

FT MSc 22/23

FT MSc 22/23

FT MSc 22/23