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Take advantage of one of our 100 Master’s Scholarships to study Health Data Science at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Read more
Take advantage of one of our 100 Master’s Scholarships to study Health Data Science at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Postgraduate loans are also available to English and Welsh domiciled students. For more information on fees and funding please visit our website.

Healthcare, with an already established strong relationship with Information & Communication Technologies (ICT), is continuously expanding the knowledge forefront as new methods of acquiring data concerning the health of human beings are developed.

Processing this data to extract valuable information about a population (epidemiological applications) or the individual (personalised healthcare applications) is the work of health data scientists. Their work has the potential to improve quality of life on a large scale.

Swansea University is the first institution in the UK to offer this taught masters programme designed to develop the essential skills and knowledge required of the Health Data Scientist.

The Health Data Science course provides an integrated programme of studies tailored to the essential skill set required for Data Scientists operating within healthcare organisations covering key topics in computation, data modeling, visualisation, machine learning and key methodologies in the analysis of linked health data. The Health Data Science course also provides hands on experiential learning from the professionals behind the Secure Anonymised Information Linkage (SAIL) Databank, a UK-exemplar project for the large scale mining of healthcare data within a secure environment.

The Health Data Science course is based within the award winning Centres for Excellence for Administrative Data and eHealth Research of Swansea University, awarded by the Economic and Social Research Council (ESRC) and Medical Research Council (MRC), enhancing the quality of the course.

Modules on the Health Data Science programme typically include:

Health Data Science & Scientific Computing in Healthcare
Health Data Manipulation
Analysis of Linked Health Data
Machine Learning Applications in Health Data
Health Data Visualisation
Advanced Analysis of Linked Health Data
Health Data Analysis Dissertation

Who should study MSc Health Data Science?

This course is suitable for those working in healthcare with roles involving the analysis of health data and also computer scientists with experience in working with data from the healthcare domain, as well as biomedical engineers and other similar professions.

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Students will become expert in linking and analysing large complex datasets, using techniques which are transforming medical research and creating exciting new commercial opportunities. Read more
Students will become expert in linking and analysing large complex datasets, using techniques which are transforming medical research and creating exciting new commercial opportunities. Graduates will be equipped for roles in the pharmaceutical industry, the NHS and technology start-ups, as well as academia.

Degree information

Students learn how to design and carry out complex and innovative clinical research studies that take advantage of the increasing amount of available data about the health, behaviour and genetic make-up of small and large populations. The content is drawn from epidemiology, computer science, statistics and other fields, including genetics.

Students undertake modules to the value of 180 credits.

The programme consists of five core modules (75 credits), three optional modules (45 credits) and a dissertation/report (60 credits). A Postgraduate Diploma (120 credits) is offered. A Postgraduate Certificate (60 credits) is offered.

Core modules
-Principles of Epidemiology Applied to Electronic Health Records Research
-Data Management for Health Research
-Statistics for Epidemiology and Public Health
-Statistical Methods in Epidemiology
-Topics in Health Data Science

Optional modules
-Advanced Statistics for Records Research
-Database Systems
-Information Retrieval and Data Mining
-Principles of Health Informatics
-Machine Learning in Healthcare and Biomedicine
-Statistics for Interpreting Genetic Data

Dissertation/report
All students undertake an independent research project which culminates in a dissertation.

Teaching and learning
The programme is delivered by clinicians, statisticians and computer scientists from UCL, including leading figures in data science. We use a combination of lectures, practical classes and seminars. A mixture of assessment methods is used including examinations and coursework.

Careers

Students on this programme will be passionate about research and know that, in the 21st century, some of the most exciting, stimulating and productive research is carried out using large collections of data acquired in big collaborative endeavours or major public or private initiatives. Graduates will build on that passion and the experience gained on the programme and develop careers as entrepreneurs, scientists and managers, working in industry, academia and healthcare.

Employability
The programme is designed to meet a need, identified by the funders of health research and by a number of industrial organisations and healthcare agencies, for training in the creation, management and analysis of large datasets. This programme is practical, cross-disciplinary and closely linked to cutting-edge research and practice at UCL and UCL’s partner organisations. Data science is arguably the most rapidly growing field of employment at the moment and employers recruiting in health data science include government agencies, technology companies, consulting and research firms as well as scientific organisations. A number of employers are supporting the programme in different ways, including providing paid internships to selected students.

Why study this degree at UCL?

The staff delivering the teaching are international experts in health data science and students will learn about cutting-edge research projects.

The collaboration is part of the Farr Institute, a network of centres of excellence created to enhance the UK’s strength in data-intensive research. This MSc will draw on that collaboration, giving students access to the most advanced research in the field.

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Are you looking for a distance learning course that gives you the flexibility to combine your existing job, or other commitments, with a Masters-level qualification in the field of data analytics? This course combines core modules in information science with specialised modules in Database Modelling as well as Statistics and Business Intelligence. Read more
Are you looking for a distance learning course that gives you the flexibility to combine your existing job, or other commitments, with a Masters-level qualification in the field of data analytics? This course combines core modules in information science with specialised modules in Database Modelling as well as Statistics and Business Intelligence.

Compared to the full-time on-campus version of this course, this Masters is taught via a flexible distance learning mode and it has a slightly extended duration of 16 months. This makes it very suitable for those who are already employed as information professionals, in addition to those looking to break into the sector for the first time.

All of Northumbria’s information science postgraduate courses are accredited by the Chartered Institute of Library and Information Professionals. This accreditation makes our courses stand out and enhances their credibility and currency among employers, and is also crucial for progressing to Chartership status once qualified.

Learn From The Best

Our teaching staff include cutting-edge researchers whose specialisms overlap with the content of this course, helping ensure that teaching is right up-to-date. Specialisms include big data, data mining, decision-making, digital literacy, information behaviour, information retrieval systems, recommender systems, and the link between information science and cognitive psychology.

Our eminent academics have written books that regularly appear on reading lists for information science courses at universities all over the world. They also work as external examiners and reviewers of courses at other UK and non-UK universities.

Our course is delivered through the Northumbria iSchool, which is one of only six iSchools in the UK. A hallmark of an iSchool is an understanding that expertise in all forms of information is required for progress in science, business, education and culture. This expertise must cover the uses and users of information, the nature of information itself, as well as information technologies and their applications.

Information Science at Northumbria was established over 70 years ago and has developed in close collaboration with the profession. That dynamic working relationship has allowed us to not only reflect professional requirements, but also to be instrumental in understanding and shaping those requirements.

Teaching And Assessment

Our teaching is linked to what you want to learn and also to what you need to learn in order to achieve greater success in information science. Our long established relationship with employers ensures that you receive the most relevant and up-to-date knowledge to bring innovation, relevance, ethical sensitivity and currency to all you do. There is an emphasis on learning by doing; coursework will include projects, portfolios of work, reports and presentations as well as essays. All this helps you to make sense of the subject, getting a clear understanding of important concepts and theories.

While some assessments contribute to your final grade, there are other assessments that are provided purely to guide your progress and reinforce your learning. You can expect both your tutors and your peers to provide useful comments and feedback throughout the course.

Learning Environment

As a distance learner you will have full access to our eLearning Portal, ‘Blackboard Learn’, which includes lecture materials, web conferencing, study notes, discussion boards, virtual classrooms and communities. Blackboard Learn brings together all aspects of course management as well as assessment and feedback. Simpler technology is also effective and there’s still the option to reach tutors through a quick telephone call!

You will also have online access to Northumbria’s library, which has half a million electronic books that you can read whenever or wherever you need them. Our library was ranked #2 in the Times Higher Education Student Experience Survey for 2015 and, since 2010, it has been accredited by the UK Government for Customer Service Excellence.

The University has advanced search software and database tools, including NORA Power Search that allows you to use a single search box to get fast results from across a wide and reliable range of academic resources. The use of such software and tools is an important aspect of our information science courses.

Research-Rich Learning

In fast-moving fields like information science it’s particularly important for teaching to take account of the latest research. Northumbria is helping to push out the frontier of knowledge in a range of areas including:
-Digital consumers, behaviours and literacy
-Digital socio-technical design
-Digital libraries, archives and records

As a student, you will be heavily engaged in analysing recent insights from the field of information science. You will undertake a major individual study that will require you to evaluate relevant literature as well as to develop your ideas within the context of existing research. Your study will be tailored to your particular interests but the underlying theme will be the relationships between information, people and technology. Many of our students publish their own research and present at professional and academic conferences, before or soon after graduating.

Give Your Career An Edge

This course is accredited by the Chartered Institute of Library and Information Professionals. This reflects the relevance of the curriculum, which is informed by contact with employers and close professional links.

The topics and activities in the course have a strong emphasis on employability. For example you will develop skills in how to analyse, monitor and evaluate user behaviour. You will also learn how to evaluate and use a range of appropriate technologies for solving problems and supporting decision-making in organisations. Your knowledge and practical skills will help you take a lead on research-informed approaches that give organisations and professionals a valuable advantage.

Your Future

Data analytics is firmly in the spotlight due to transformations in information science and the emergence of big data. As we look to the future, which will be marked by ever greater capabilities for data processing, and a rising expectation that major decisions should be based on data-driven insights, data analytics will become increasingly valued and rewarded.

On graduation, you will be well placed to take advantage of this trend. Employers are looking for information professionals who can develop new insights through mastery of their subject and critical scholarship. With your Masters qualification, you will be equipped to make a difference, advance your practice and make well-balanced judgements. You could work for a wide range of employers in the field of data analytics or you could progress in a career that you have already started. Your Masters qualification can also form the basis for further postgraduate studies at a higher level.

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This programme aims to develop a high level understanding of quantitative and computational geographical methods. This includes skills in GIS software and statistical programming languages, such as R or Python. Read more
This programme aims to develop a high level understanding of quantitative and computational geographical methods. This includes skills in GIS software and statistical programming languages, such as R or Python.

Within an applied setting, emphasis is placed on developing skills in the visualisation, modelling and statistical analysis of spatial data using both web-based and traditional techniques.

Human activity are increasingly associated with the generation of large volumes of data. For example, transactional data are collated by retailers for marketing and store location purposes, administrative data are assembled to help with the efficient running of public services, data shadows are created through social media use, and an increased prevalence of smart-card linked transport systems record our travel behaviours.

Many grand human challenges concern problems of a geographical nature; be this how we can mitigate the human impact of climate change; ensure global food and water security; design energy systems that are resilient within the context of future population dynamics; or, how to design future cities where spatial inequities in health and wellbeing might be eradicated? The growing volumes of big data about the form, function and dynamics of human activities and their contexts are providing new opportunities to advance such debates within a framework of Geographic Data Science.

Why Geography?

We’ve exceptional academic staff with expertise in a range of areas:

Geographies of Population and the Lifecourse
Globalisation, Development and Place
Advanced Environmental Analytical Techniques
The study of Environmental and Climate Change.

Career prospects

Our degrees provide pathways into rewarding careers and our graduates have found employment in a wide range of industries and organisations, both in the UK and abroad. Graduates of the Environment and Climate Change MSc have gone on to continue their studies towards a PhD, or are employed in a wide range of positions, including environmental, energy and engineering consultancies, multinational companies (energy), local government, environmental bodies, research positions and teaching.

PhD graduates are now working in academic life as lecturers in Geography, Environmental Science, Economic History, Development Studies and Statistics at universities in the UK and overseas. Others are employed in applied fields, working in Europe, Africa and across the world, for example as professional statisticians (one is now Director of Statistics in Zambia, another working in the Health Service in the UK), development professionals (including a member of staff on the WHO malaria programme in East Africa), and scientists at climate and environmental research centres around the world.

Students will be well placed to undertake a career in social science research at the end of their studies, both in an academic and a non-academic environment.

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Are you looking for a Masters-level qualification that will open doors to jobs and promotions in the field of data analytics? This 2-year Masters course combines core modules in information science with specialised modules in Database Modelling as well as Statistics and Business Intelligence. Read more
Are you looking for a Masters-level qualification that will open doors to jobs and promotions in the field of data analytics? This 2-year Masters course combines core modules in information science with specialised modules in Database Modelling as well as Statistics and Business Intelligence.

As part of the focus on data analytics, you will cover topics such as how to design and manipulate databases with relational algebra and SQL. You will also analyse (big) data in order to improve organisational decision-making, using techniques such as regression analysis, clustering, distance measures, probability and distributions.

In the second year, for one semester, you’ll undertake an internship, study in another country or join a research group. This valuable experience will enhance your employability and further develop your theoretical and practical skills.

Internship
This option offers the opportunity to spend three months working full-time in one of the many companies/industries with which we have close links. You may be able to extend this over more than one semester in cases where it is adjacent to a vacation period. We will endeavour to help those who prefer this option to find and secure a suitable position but ultimately we are in the hands of the employers who are free to decide who they take into their organisation.

Research
If you take this option, you will be assigned to our Computer Science and Informatics Research Group. There is every possibility that you may contribute to published research and therefore you may be named as part of the research team, which would be a great start to a research career.

Study Abroad
We have exchange agreements with universities all over the world, including partners in Europe, Asia, the Americas and Oceania. If you take the Study Abroad option, you will spend a semester at one of these partners, continuing your studies in English but in a new cultural and learning environment. Please note that this option may require you to obtain a visa for study in the other country.

All of Northumbria’s information science postgraduate courses are accredited by the Chartered Institute of Library and Information Professionals. This accreditation makes our courses stand out and enhances their credibility and currency among employers, and is also crucial for progressing to Chartership status once qualified.

Learn From The Best

Our teaching staff include cutting-edge researchers whose specialisms overlap with the content of this course, helping ensure that teaching is right up-to-date. Specialisms include big data, data mining, decision-making, digital literacy, information behaviour, information retrieval systems, recommender systems, and the link between information science and cognitive psychology.

Our eminent academics have written books that regularly appear on reading lists for information science courses at universities all over the world. They also work as external examiners and reviewers of courses at other UK and non-UK universities.

Our course is delivered through the Northumbria iSchool, which is one of only six iSchools in the UK. A hallmark of an iSchool is an understanding that expertise in all forms of information is required for progress in science, business, education and culture. This expertise must cover the uses and users of information, the nature of information itself, as well as information technologies and their applications.

Information Science at Northumbria was established over 70 years ago and has developed in close collaboration with the profession. That dynamic working relationship has allowed us to not only reflect professional requirements, but also to be instrumental in understanding and shaping those requirements.

Teaching And Assessment

Our teaching is linked to what you want to learn and also to what you need to learn in order to achieve greater success in information science. Our long established relationship with employers ensures that you receive the most relevant and up-to-date knowledge to bring innovation, relevance, ethical sensitivity and currency to all you do. There is an emphasis on learning by doing; coursework will include projects, portfolios of work, reports and presentations as well as essays. All this helps you to make sense of the subject, getting a clear understanding of important concepts and theories.

The Advanced Practice semester will be assessed via a report and presentation about your internship, study abroad or research group activities.

While some assessments contribute to your final grade, there are other assessments that are provided purely to guide your progress and reinforce your learning. You can expect both your tutors and your peers to provide useful comments and feedback throughout the course.

Module Overview

Year One
KC7013 - Database Modelling (Core, 20 Credits)
KC7020 - Information Organisation and Access (Core, 20 Credits)
KC7021 - Statistics and Business Intelligence (Core, 20 Credits)
KC7022 - Information Systems and Technologies (Core, 20 Credits)
KC7023 - Research Methods and Professional Practice (Core, 20 Credits)
KC7024 - User Behaviour and Interaction Design (Core, 20 Credits)

Year Two
KC7026 - Masters Dissertation (Core, 60 Credits)
KF7005 - Engineering and Environment Advanced Practice (Core, 60 Credits)

Learning Environment

Northumbria uses a range of technologies to enhance your learning, with tools including web-based self-guided exercises, online tests with feedback, videos and tutorials. These tools support and extend the material that is delivered during lectures, and are available anywhere anytime. Group work and peer interaction feature prominently in our learning and teaching, this reflects the practices you’re likely to encounter within the working environment.

You will have 24/7 term-time access to Northumbria’s library, which has over half a million print books as well as half a million electronic books available online. Our library was ranked #2 in the Times Higher Education Student Experience Survey for 2015 and, since 2010, it has been accredited by the UK Government for Customer Service Excellence.

The University has advanced search software and database tools, including NORA Power Search that allows you to use a single search box to get fast results from across a wide and reliable range of academic resources. The use of such software and tools is an important aspect of our information science courses.

Give Your Career An Edge

This course is accredited by the Chartered Institute of Library and Information Professionals. This reflects the relevance of the curriculum, which is informed by contact with employers and close professional links.

The topics and activities in the course have a strong emphasis on employability. For example you will develop skills in how to analyse, monitor and evaluate user behaviour. You will also learn how to evaluate and use a range of appropriate technologies for solving problems and supporting decision-making in organisations. Your knowledge and practical skills will help you take a lead on research-informed approaches that give organisations and professionals a valuable advantage.

The Advanced Practice semester will help you develop a track record of achievement that will help you stand out from other job applicants.

A two-year master’s course, like this one, will carry particular weight with employers. They’ll understand that you’ll have a deeper understanding of topics as well as more hands-on practical experience.

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This course will commence. The PgDip/MSc course in Environmental Management and Geographic Information Systems is PART-TIME and offered by DISTANCE LEARNING. Read more
This course will commence

September 2017

The PgDip/MSc course in Environmental Management and Geographic Information Systems is PART-TIME and offered by DISTANCE LEARNING. It is accredited by the Institution of Environmental Sciences (https://www.the-ies.org)

This course aims to satisfy an industrial and public sector demand for science-­qualified environmental management personnel who can analyse environmental issues and propose viable solutions in fields such as conservation, agriculture, forestry, industry and countryside planning.

It provides a balanced programme studying the core elements of Environmental Management combined with a more detailed study of the techniques of the principles and practice of GIS. It enables students to develop an advanced understanding of the functioning of ecosystems through the study of biodiversity and pollution monitoring and to equip them with the analytical GIS tools to enable effective ecosystem analysis. The GIS elements of the course develop an enhanced understanding of theoretical material relating to data models, data sources and quality, data management, GIS functionality and data analysis. The course provides students with hands-­‐on experience of key GIS packages and other analytical software. Examples are drawn from across the spectrum of physical and social environmental contexts.

Students resident in the UK and Ireland will be provided with a student copy of Esri ArcGIS software free of charge.

Modular Structure

Principles of GIS

This module introduces the theory and practice of Geographic Information Systems, and is intended to provide an understanding of the breadth of potential GIS applications and to equip students with key concepts and skills relating to the input, management, manipulation, analysis and output of spatial data. Lecture-based teaching of key concepts is reinforced by linked practical exercises which allow students to develop competence in ESRI’s ArcGIS package. The module assumes no prior knowledge or experience of GIS.

Spatial Data Management

This module builds on the knowledge and practical skills gained in the Principles of GIS module to provide students with further experience in the acquisition, manipulation and analysis of spatial data. Methods for generating and collecting digital spatial data from primary and secondary sources are considered, and data processing, selection, integration and analysis extensively practiced. Lecture and practical sessions include digitising, geo-registration, GPS, accessing and using secondary sources, spatial join and overlay, network analysis and 3D modelling, and incorporate experience of a variety of large and small scale vector and raster datasets. The module also incorporates practice in statistical analysis and interpretation. Development of GIS software skills focuses on ArcGIS and extensions.

Biodiversity Management

Biodiversity managers make decisions based on understanding ecosystems and by applying ecological principles to achieve their objectives. This module covers key scientific topics, which are crucial for developing effective biodiversity management plans in different ecosystems. It exemplifies how ecological-social-economic factors interact to influence our ability to conserve and manage biodiversity.

Pollution Monitoring

This module provides the knowledge and skills necessary to monitor pollution of the environment. The topics included are: the key elements of the monitoring programmes for air, water and land; sample collection; chemical methods of analysis, including quality assurance; biological methods of analysis, including toxicity tests and bio-assessment; use of environmental models; statistics, data analysis and assessing compliance and; critical loads.

Spatial Analysis

This module builds on the introductory material of the previous GIS modules studied, covering key concepts of spatial data analysis and modelling, and providing extensive practical experience of ESDA and spatial modelling within a GIS environment.

GIS for Environmental Managers

This module examines the application of GIS to environmental management, modelling and impact assessment. It aims to enable students to appreciate the need for properly researched information to support strategic and operational environmental management decisions, and to be aware of the means by which such information can be obtained and evaluated.

Environmental Management Project

This module provides the opportunity for the student to demonstrate the skills acquired during the course, in the form of a final project. The project is presented in the form of a scientific paper on an area agreed with the student’s supervisor.

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75% of our research into Social Work and Social Policy was awarded 3* for our environment - 'conducive to producing research of internationally excellent quality, in terms of its vitality and sustainability' - Research Excellence Framework (REF) 2014. Read more
75% of our research into Social Work and Social Policy was awarded 3* for our environment - 'conducive to producing research of internationally excellent quality, in terms of its vitality and sustainability' - Research Excellence Framework (REF) 2014.

This Masters in Social Policy and Social Research Methods is particularly significant if you are currently working in local authorities or the voluntary sector. The skills you learn will progress your career in social welfare policy development, delivery or research. Or it is also relevant if you are thinking of starting a career related to social policy in the public, voluntary or private sectors.

The focus of this course is on contemporary substantive issues in social policy development and delivery, and social policy research methods. You'll develop your theoretical, policy and technical understanding of key issues related to policy-making, social welfare delivery, equality and social justice, and research methods.

You'll gain an advanced understanding of national and international factors influencing policy development and implementation. The changing relationship between the State, voluntary sector and private sector in terms of social welfare delivery. You'll also explore how ideas of equality, diversity, justice and human rights shape institutions and the programmes they offer.

You'll engage with recent research linked to changing family forms and how family policy impacts on children and families. You'll be equipped to design and implement social scientific research using a broad range of methodologies, consider research ethics then analyse and present the material such research generates.

The course fosters a critical awareness of the relationship between theory, policy and practice and enables you to utilise your research knowledge and research skills and translate these into research practice in the field of social policy and broader social science research professions.

Flexible modes of study:
You can choose between three modes lasting one, two or three years allowing you to study whilst maintaining other life commitments.

See the website http://www.lsbu.ac.uk/courses/course-finder/social-policy-and-social-research-methods

Modules

- Social policy analysis
This module will help you understand the policy making process and the factors that influence the formation and implementation of social policy, for example, demographic changes or policy transfer. You'll discuss current debates about policy making and delivery, including user involvement, localism and sustainability.

- The voluntary sector and the state: protagonist or partner
You'll explore the contemporary role of the voluntary sector in the delivery of social welfare, and the challenges they face in terms of management, capacity building and funding. You'll examine the role of the voluntary sector as partner or protagonist to the state, as well as its relationships with the private sector.

- Methods for social research and evaluation: philosophy, design and data collection
This module is an introduction to core concepts in social research and how they can be used to address social scientific questions and practical issues in policy evaluation. You'll engage with central topics in the philosophy of social sciences and the effect they have on research choices and explore the different ways research can be designed, and the way design affects permissible inferences. You'll also be introduced to the theory of measurement and sampling. The final third of the module focuses on acquiring data ranging from survey methods through qualitative data collection methods to secondary data.

- Approaches to social change: equality, social justice and human rights
In this module you'll explore a number of different goals, and the theoretical underpinnings which aim to achieve social change. These goals include: equality, diversity, social justice, social inclusion, multiculturalism, social cohesion and human rights. You'll examine a range of different initiatives to promote these goals in both employment and social welfare delivery. Finally, the module will explore strategies: to identify inequality, injustice and forms of discrimination; to monitor policy development and implementation; and to evaluate outcomes and 'success'.

- Family policy
This module is taught by internationally recognised researchers from the Weeks Centre for Social and Policy Research. You'll be introduced to demographic changes in families and changes in State-family relationships and developments in 'family policy'. You'll explore early intervention into families, child welfare including adoption, fostering and child maintenance, child poverty, and childcare. Finally, cross cultural perspectives in family formation will be discussed.

- Data analytic techniques for social scientists
In this module you are introduced to a range of analytic techniques commonly used by social scientists. It begins by introducing you to statistical analysis, it then moves to techniques used to analyse qualitative data. It concludes by looking at relational methods and data reduction techniques. You'll also be introduced to computer software (SPSS, NVivo and Ucinet) that implements the techniques. You'll gain both a conceptual understanding of the techniques and the means to apply them to your own research projects. An emphasis will be placed on how these techniques can be used in social evaluation.

- Dissertation
The aim of the dissertation is to enable you to expand and deepen your knowledge on a substantive area in social policy, whilst simultaneously developing your methodological skills. You'll choose an area of investigation and apply the research skills of design and process, modes of data generation and data analysis techniques to undertake a 15,000 word dissertation.

Employability

This MSc will enable you to pursue a range of professional careers in areas linked to social policy and social welfare. You'll be able to access work in the statutory, commercial or voluntary sectors and operating at central, and local government levels, for example, local government; MORI, NSPCC and DEMOS. The acquisition of specific social policy and research methods knowledge will also enhance your career opportunities if you are currently working in the field in social policy development and delivery or in undertaking social policy related research. The specialist focus on research methods also offers an excellent foundation for those interested in undertaking subsequent doctoral research in the field.

LSBU Employability Services

LSBU is committed to supporting you develop your employability and succeed in getting a job after you have graduated. Your qualification will certainly help, but in a competitive market you also need to work on your employability, and on your career search. Our Employability Service will support you in developing your skills, finding a job, interview techniques, work experience or an internship, and will help you assess what you need to do to get the job you want at the end of your course. LSBU offers a comprehensive Employability Service, with a range of initiatives to complement your studies, including:

- direct engagement from employers who come in to interview and talk to students
- Job Shop and on-campus recruitment agencies to help your job search
- mentoring and work shadowing schemes.

Placements

If you are not already working in an environment which is linked to social welfare you'll be encouraged to undertake voluntary work which will give you useful experience alongside the degree. In addition it may become used as a location where you can undertake primary research for your master's dissertation. The Employability team at LSBU can help students find voluntary placements.

Teaching and learning

Modules are assessed by coursework. There are different kinds of writing required which include: a critical reading log, a self-reflective essay, a methodological critique of a research article, a research proposal, extended essays, an evaluation of social change and a dissertation.

Modules are supported by Moodle, the LSBU virtual learning environment where most course reading will be made available. The classroom is envisaged as a core learning environment where you can discuss new ideas but also to think how they can be applied to previous or current work or voluntary experiences. Attendance is crucial for building your knowledge and skills. You'll be making use of computer laboratories in order to develop your use of a range of programmes that can be used to analyse quantitative and qualitative methods.

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The GIS (Geographical Information Science) MSc provides an education in the theoretical, scientific and practical aspects of GIS. Read more
The GIS (Geographical Information Science) MSc provides an education in the theoretical, scientific and practical aspects of GIS. It prepares students for technical and analytical GIS roles and is in high demand; we have very close links with industry and the majority of our students find employment prior to contemplating their degree.

Degree information

Students gain a solid grounding in the scientific principles underpinning the computational and analytical foundations of GISc. Our staff are world-leading experts in the areas of programming location-enabled Apps, spatial and 3D databases, big spatio-temporal analytics, citizen science and and human computer interaction, and the MSc therefore is able to offer a wide range of options and specialisations.

Students undertake modules to the value of 180 credits. The programme consists of four core modules (60 credits), four optional modules (60 credits) and a research project (60 credits). A Postgraduate Diploma, four core modules (60 credits), four optional modules (60 credits), full-time nine months is offered.

Core modules - core modules introduce the theory underpinning GIS, along with programming skills (python) and the basics of spatial analysis and statistcs. You'll learn to critically engage with GIS rather than just pushing buttons - how does the way data is captured and modelled influence the results of your analysis? Do you get the same results from two different GIS packages? Knowing what is inside the 'black box' means you understand analytical results and their limitations.
-GIS Principles and Technology
-Principles of Spatial Analysis
-Mapping Science
-Representations, Structures and Algorithms

Optional modules - term two is where you start to specialise, chosing modules that fit your interests, intended career choice and/or prepare you for your dissertation. At this point you can chose a heavilty technical route (e.g. databases, programming, human computer interaction) a more analytical route (spatio-temporal data mining, network and locational analysis, databases) or a mixture of the two routes. You will need to chose four modules in total. At least 30 credits of optional modules selected from :
-Geographical Information System Design
-Spatio-Temporal Analysis and Data Mining
-Web and Mobile GIS – Apps and Programming
-Spatial Databases and Data Management

Plus no more than 30 credits of optional modules (all term two) selected from :
-Airborne Data Acquisition
-Applied Building Information Modelling
-Network and Locational Analysis
-Image Understanding
-Ocean and Coastal Zone Management
-Positioning
-Research Methods
-Terrestrial Data Acquisition

Dissertation/report
All students undertake an independent research project which culminates in a dissertation of 10,000–15,000 words. Where appropriate, this may be undertaken in conjunction with one of our many industrial partners, including Arup, Joint Research Centre, British Red Cross, Transport for London.

Teaching and learning
The programme is delivered through lectures, practical classes, demonstrations and tutorials, and is supported by a series of external speakers from industry and visits to industrial who give weekly seminars describing how GIS is used in their field as well as what they are looking for when recruiting graduate GIS students. Assessment is through unseen examinations, group and individual coursework, formal and oral presentations, and the dissertation.

Careers

There are excellent employment prospects for our graduates, with starting salaries of around £25,000. Recent GIS graduates have found openings with large engineering design firms (such as Arup or WSP), specialist consultancy firms such as Deloitte or Informed Solutions, in leading professional software companies (such as ESRI or Google), with local authorities, for organisations such as Shell, Tesco, the Environment Agency, Transport for London, NHS and the Ordnance Survey.

Employability
Students will develop specific skills including a fundamental understanding of GIS and its application to real-world problems, through theoretical lectures covering the foundations of the science – how data is captured, map creation, generalisation, spatial data management, spatial analysis, data quality and error, and spatial algorithms. Students will develop strong technical (python, R, Java, HTML, Javascript, SQL) and analytical skills (data mining, human computer interaction and usability), and in order to fully understand the principles behind GIS will make use of multiple GIS packages, both proprietary and free/open source (ArcGIS, QGIS).

Why study this degree at UCL?

This highly regarded MSc has been running for nearly 30 years and is taught by internationally recognised academics. Our specialist GIS laboratory offers the latest open source and proprietary software and our unique dual focus on the computer science and analytical aspects of GIS means that you will be able to develop your skills in multiple directions.

Our close links with industry (a strong alumni group and weekly industrial seminars) mean that you will be able to directly link your classroom learning with your future career as a GIS professional; you can also undertake your dissertation with an industrial partner.

As well as weekly industrial seminars, you will have the option to do an industry-linked project, and you will be able to attend our annual GIS careers event, which is co-organized with the UK Assocation of Geographic Infrormation.

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New to LJMU, this cutting edge programme aims to train scientists, engineers and mathematicians in the new field of Data Science. Read more
New to LJMU, this cutting edge programme aims to train scientists, engineers and mathematicians in the new field of Data Science. It combines lectures, hands-on practical experience and an extended research project, delivered by experts from two university departments.

•Study a ground-breaking curriculum linked to industry needs
•Use industry standard tools and methodologies
•Undertake an extended project using real world data science problems
•Learn from academics who are world-leading researchers
•Use the programme as a basis for PhD study


SUBJECT TO VALIDATION

The programme comprises six core modules covering statistical and computing techniques plus an extended research project.

​This MSc is designed to give you the knowledge to move into the world of work as a qualified Data Scientist or to carry out further research through a PhD or equivalent. It is delivered via a combination of lectures, tutorials and and hands-on computer laboratory sessions.

A major component of the MSc programme is the research project module, which will give you the opportunity to work on a high-level original research topic, with guidance from an experienced researcher and supervisor.

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This course is your opportunity to specialise in the development of web-based software systems that use databases. Read more
This course is your opportunity to specialise in the development of web-based software systems that use databases. During your time with us, you will gain a critical awareness of the methodologies, tools and techniques used for the development of web-based computer systems and an advanced understanding of the techniques used for the development, evaluation and testing of databases.

The course also develops an awareness of the latest developments in the field of advanced databases, data mining and data warehousing. You will also gain substantial knowledge and skills in the deployment of SAS business intelligence software leading towards SAS data miner accreditation, and learn what the Semantic Web and Linked Data are, together with what these technologies enable.

Key benefits:

• The course gives you hands-on experience in design and implementation of databases in both Oracle and Microsoft SQL Server DBMS and prepares you to obtain DBA certification
• You learn how to design and implement a web application using ASP.NET, Microsoft SQL Server, and PHP with My SQL
• You learn the data mining techniques to mine data in different application domains using most popular data mining tools.

Visit the website: http://www.salford.ac.uk/pgt-courses/databases-and-web-based-systems

Suitable for

This course is for students who want to become trained professionals:

• In designing and implementing database systems in Oracle Micro Soft SQL Server DBMS and who want to be prepared to obtain DBA certification
• In designing and implementing a web application using ASP.NET, Microsoft SQL Server, and PHP with My SQL
• With hands-on experience in data mining techniques to mine data in different application domains using the most popular data mining tools.

Programme details

This course covers a very comprehensive range of topics split in to four large modules worth 30 credits each plus the MSc Project. External speakers from blue-chip and local companies will give seminars to complement your learning, that will be real-world case studies related to the subjects you are studying in your modules. These are designed to improve the breadth of your learning and often lead to ideas that you can develop for your MSc Project.

Format

Teaching on this course takes the form of lectures, individual and group class work, topical class discussions and critical case study evaluation.

You will gain hands-on lab experience of using and setting up databases and web-based systems. What’s more, tutorials will give you practice in solving the theoretical and design problems associated with these systems.

Module titles

• Advanced Databases
• Web-Based Software Development
• Semantic Web and Information Extraction
• Business Intelligence
• MSc Project

Assessment

• Coursework 60%
• Examinations 40%

Career potential

With this qualification, you’ll be equipped as web/database designer and programmer, data analytics and miner among other roles. Your experience will be in high demand across all industrial and commercial sectors.

Previous students have gone on to work with companies including British Airways, Google, Hewlett-Packard, Oracle and other IT firms.

How to apply: http://www.salford.ac.uk/study/postgraduate/applying

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The MPH in Palliative Care Research is designed for students wishing to pursue a service or academic career in palliative care. It will provide you with an excellent understanding of both research and public health issues, thus increasing your career opportunities. Read more
The MPH in Palliative Care Research is designed for students wishing to pursue a service or academic career in palliative care. It will provide you with an excellent understanding of both research and public health issues, thus increasing your career opportunities.

Why study Palliative Care Research at Dundee?

Dundee is ideally placed to deliver the MPH in Palliative Care. The Division of Population Health Sciences has several internationally recognised research programmes, with associated academic and research staff, and the Division also houses the renowned Health Informatics Centre (HIC) which provides researchers access to anonymised record-linked data. This includes routinely collected NHS patient datasets for the whole population.

The MPH degree has been run successfully in Dundee for over 25 years and our past students now contribute to the global public health workforce. Building on this success, we are ideally placed to offer a new exit - in palliative care research - from the core MPH. The MPH Palliative Care Research presents an opportunity to integrate public health with quality palliative care research and the clinical palliative care services. This provides a rich learning environment for prospective students.

Research led supervision

The Co-Director of the course, Dr Deans Buchanan, was recently appointed Consultant in Palliative Medicine. The Tayside Palliative Care Service is well placed to support excellence in research and in research training. The varied clinical settings throughout Tayside provide an excellent basis for research projects. Clinicians from within the palliative care service will supervise dissertations and include: Dr Rosie Conway, Dr Claire Douglas, Dr Fiona McFatter, Dr Martin Leiper and Dr Alison Morrison. In addition, Dr Bridget Johnston, Reader in Palliative Care (School of Nursing and Midwifery) will also contribute to the teaching and supervision of students.

Aims of the Programme

This course will provide you with:

* The necessary skills and expertise to enable you to undertake well designed research and interpret research data.
* The requisite communication skills and understanding of the importance of such communication.

Teaching & Assessment

This course is based in the School of Medicine. The MPH in Palliative Care Research degree course starts in September each year and lasts for 12 months on a full time basis, or 24 months on a part time basis.

How you will be taught

A variety of teaching methods will be used including traditional lectures; tutorials; discussion sessions; self directed learning including the use of internet based resources; and supervised research.

The MPH programme of studies provides teaching within a supportive environment and students are encouraged to contact lecturers to raise specific questions.

What you will study

Semester 1:
Epidemiology (15 SCQF credits)
Introduction to Clinical Statistics (15 SCQF credits)
Palliative care: Foundations and research part 1 (7 SCQF credits)

Semester 2, part 1
Research methods (15 SCQF credits)
Applied Statistics with Routine Health Datasets (15 SCQF credits)
Palliative care: Foundations and research part 2 (3 SCQF credits)

Semester 2, part 2
Spatial Epidemiology (5 SCQF credits) OR Data Visualization (5 SCQF credits)
Systematic reviews (5 SCQF credits)

Dissertation
The purpose of the dissertation is to enable students to write a dissertation which utilises all of the knowledge and expertise that they have acquired during the taught component of the course.

How you will be assessed

Performance is monitored by formal examinations and continuous assessment. Formative assessment is delivered through group and individual feedback during the tutorials, discussion sessions and on coursework. Summative assessment is based on assignments and examinations. Examinations are marked by two independent members of the School who are blinded to student identity. Guidelines for markers are provided. The dissertations are also double marked.

Careers

An MPH (Palliative Care Research) will enhance the employability of professionals interested in palliative care research.

For Specialty Trainees in Palliative Medicine this will add distinct skills sets and an essential understanding of both research and public health issues. Such qualifications will open job opportunities in academic medicine and at policy development levels. This course is compatible with the Palliative Medicine Curriculum and dissertation projects could be undertaken in candidates own localities.

Non-medical staff (including nursing staff) will benefit from the same skill set and enhanced ability to enter academic palliative care. Multi-professional learning is encouraged and dissertation projects can be tailored to specific backgrounds.

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1. Big Challenges being addressed by this programme – motivation. Globally, there is a reported shortage of data analytics talent, particularly of individuals with the required deep technical and analytical skills. Read more

About the Course

1. Big Challenges being addressed by this programme – motivation

• Globally, there is a reported shortage of data analytics talent, particularly of individuals with the required deep technical and analytical skills.
• Accenture, Gartner and McKinsey have all identified Data Analytics as one of the fastest growing employment areas in computing and one most likely to make an impact in the future.
• The Irish Government’s policy is for Ireland to become a leading country in Europe for big data and analytics, which would result in 21,000 potential new employment opportunities in Ireland alone.
• CNN has listed jobs in this area in their Top 10 best new jobs in America.

2. Programme objectives & purpose

This is an advanced programme that provides Computing graduates with advanced knowledge and skills in the emerging growth area of Data Analytics. It includes advanced topics such as Large-Scale Data Analytics, Information Retrieval, Advanced Topics in Machine Learning and Data Mining, Natural Language Processing, Data Visualisation and Web-Mining. It also includes foundational modules in topics such as Statistics, Regression Analysis and Programming for Data Analytics. Students on the programme further deepen their knowledge of Data Analytics by working on a project either in conjunction with a research group or with an industry partner.

Graduates will be excellently qualified to pursue careers in national and multinational industries in a wide range of areas. Our graduates currently work for companies as diverse as IBM, SAP, Cisco, Avaya, Google, Fujitsu and Merck Pharmaceuticals as well as many specialised companies and startups. Opportunities will be found in:
• Multinational companies, in Ireland and elsewhere, that provide services and solutions for analytics and big data or whose business depend on analytics and big data technologies;
• Innovative small to medium-sized companies and leading-edge start-ups who provide analytics solutions, services and products or use data analytics to develop competitive advantage
• Companies looking to extend their research and development units with highly trained data analytic specialists
• PhD-level research in NUI Galway, elsewhere in Ireland, or abroad

3. What’s special about CoEI/NUIG in this area:

• The MSc in Computer Science (Data Analytics) is being delivered by the Discipline of Information Technology in collaboration with the Insight Centre for Data Analytics (http://insight-centre.org) and with input from the School of Mathematics, Statistics and Applied Mathematics in NUI Galway
• The Discipline of Information Technology at NUI Galway has 25-year track record of education, academic research, and industry collaboration in the field of Computer Science
• The Insight centre at NUI Galway is Europe’s largest research centre for Data Analytics

4. Programme Structure – ECTS weights and split over semester; core/elective, etc.:

• 90ECTS programme
• one full year in duration, beginning September and finishing August
• comprises:
- Foundational taught modules (20 ECTS)
- Advanced taught modules (40 ECTS)
- Research/Industry Project (30 ECTS).

5. Programme Content – module names

Sample Foundational Modules:

• Tools and Techniques for Large Scale Data Analytics
• Programming for Data Analytics
• Machine Learning and Data Mining
• Modern Information Management
• Probability and Statistics
• Discrete Mathematics
• Applied Regression Models
• Digital Signal Processing

Sample Advanced Modules:

• Advanced Topics in Machine Learning and Information Retrieval
• Web Mining and Analytics
• Systems Modelling and Simulation
• Natural Language Processing
• Data Visualisation
• Linked Data Analytics
• Case Studies in Data Analytics
• Embedded Signal Analysis and Processing

6. Testimonials

Ms. Gofran Shukair, MSc, Research Engineer at ZenDesk, Ireland

After graduating with an MSc at NUI Galway, Gofran worked with Fujitsu’s Irish Research Lab as a research engineer before moving to a software engineering position at Zendesk, Ireland.

“The mix of technical and soft skills I gained through my Masters studies at NUI Galway is invaluable. I had the chance to work with great people and to apply my work on real world problems. With the data management and analysis skills I gained, I am currently pursuing my research in an international research project with one of the leading IT companies. I will be always thankful for studying at NUI Galway, a great historic place based in a culturally-rich vibrant city with an international mix of young and ambitious students that made me eager to learn and contribute back the moment I graduated.”

For further details

visit http://www.nuigalway.ie/courses/taught-postgraduate-courses/msc-in-computer-science-data-analytics.html

How to Apply:

Applications are made online via the Postgraduate Applications Centre (PAC) https://www.pac.ie
Please use the following PAC application code for your programme:

M.Sc. Computer Science – Data Analytics - PAC code GYE06

Scholarships :

Please visit our website for more information on scholarships: http://www.nuigalway.ie/engineering-informatics/internationalpostgraduatestudents/feesandscholarships/

Visit the M.Sc. Computer Science – Data Analytics page on the National University of Ireland, Galway web site for more details!

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Make your input really count as a postgraduate student in the Department of Computer Science and Engineering. Traditional computer science research covers the hardware and software of computer systems and their applications. Read more
Make your input really count as a postgraduate student in the Department of Computer Science and Engineering. Traditional computer science research covers the hardware and software of computer systems and their applications. Computer science programs at HKUST emphasize an integrated approach to the study of computers and computing methods to collect, process, analyze and transmit information to support relevant and useful applications in modern life.

The Department's goal is to offer a full range of postgraduate courses and research projects to meet the needs and interests of our students and to help solve relevant problems for society. Our world-class faculty members engage in cutting-edge research at the heart of the information technology revolution and our postgraduate students are involved in both applied and fundamental research. The Department has 50 full-time faculty members and 180 postgraduate students.

Computer science is still a young field. The world is only just beginning to realize the potential of information technology. The Department and its programs prepare students to meet the exciting challenges that await and to generate new advances in computing that will fuel future progress.

The MPhil program seeks to strengthen students' knowledge in computer science and expose them to issues involved in the development, scientific, educational and commercial applications of computer systems. Students are required to undertake coursework and successfully complete a thesis to demonstrate competence in research.

Research Foci

The Department's research involves many different areas:
Artificial Intelligence
Machine learning, data mining and pattern recognition, knowledge representation and reasoning, robotics and sensor-based activity recognition, multi-agent and game theory, and speech and language processing.

Data, Knowledge and Information Management
Large-scale data management, modeling and distribution encompassing web query processing, information retrieval and web search, data mining, enterprise systems, high-performance data management systems on modern computers, and database support for science applications.

Human-Computer Interaction
Augmented reality, multi-touch interaction, crowdsourcing, multimodal communication, affective computer, visual analytics of big data, intelligent interface for robots, E-learning, healthcare and e-commerce.

Networking and Computer Systems
Pervasive computing and sensor networks, peer-to-peer computing, grid computing, high-performance switches and routers, video delivery and multicasting, multimedia networking, MAC protocols for ad-hoc networks, web cache management, DDOS detection and defense, and resource management and allocation in optical networks.

Software Technology and Applications
Software engineering, data mining for software analysis and debugging, computer music, cryptography and security, internet computing.

Theoretical Computer Science
Combinatorial optimization, performance analysis techniques, computational geometry, formal languages and machines, graph algorithms, and algorithmic combinatorial game theory.

Vision and Graphics
Computer vision, computer graphics, medical image analysis, biometric systems, and video processing.

Facilities

The Department has excellent facilities to support its programs and is committed to keeping its computing facilities up to date. There are about 700 workstations and PCs, including those in four teaching laboratories, three MS Windows Labs and one Linux lab. The Department also runs several research laboratories with specific facilities, including the computer engineering, database, Human-Computer Interaction Initiative, vision and graphics labs. Specialized project laboratories include:
-The HCI lab, has a 360 degree circular CCD-camera capturing system with a 4x3 large display array and 120" rear projected 3D active stereo system, and large-sized multi-touch panels, linked with various physiological sensors for gesture/body tracking;
-The Human Language Technology Center, with various corpora and a Linux cluster;
-The System and Media Laboratory, partially funded by Deutsche Telekom, focusing mobile computing and any interesting topics related to social network; and
-The Networking group, that maintains different sets of network cluster for Data center and cloud computing research.
-Different research groups maintain their own CPU/GPU cluster customized for different research need.

In addition, the Department manages a pool of Linux servers as CPU/GPU cluster for general research projects demanding significant system resources, and acquires a GPU cluster for the whole University. The file servers are connected with one HDS AMS2100 and one HDS HUS110 Storage Area Network (SAN), with a total capacity of more than 60TB. There is also a pool of high performance servers with GPUs dedicated for undergraduate courses on parallel computing and Big Data analysis.

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This programme is recognised by the ESRC as a research training programme designed to provide participants with a sound background on overall research design and the most up-to-date training in methods and data collection and analysis. Read more
This programme is recognised by the ESRC as a research training programme designed to provide participants with a sound background on overall research design and the most up-to-date training in methods and data collection and analysis.

The core elements of this programme are delivered by staff from across the College of Social Sciences, many of them engaged in cutting-edge research in their own fields.

The MA programme includes assessed core modules and short courses (120 credits) and the completion of a 14,000 word dissertation (60 credits), while the Postgraduate Diploma includes the assessed courses only (120 credits).

Modules

Introduction to Social Research
This module aims to provide a general introduction to studying and research methods and prepares you for your dissertation, emphasising key skills such as searching literature, finding datasets and presenting and criticising arguments. It also covers ethics of research, the role of theory and philosophical bases for understanding the social world.

Research Design
This module links the introductory module and data collection module through consideration of research design, questions, warranting practices and sampling methods. All the elements of research design are linked into an over-arching theme of the full cycle of research activity.

Social Research Methods I
This module introduces the principles and practices of data collection and explores rationales of the various methods. It will focus on the different stages of data collection, including various methods used to gather textual and numerical data.

Social Research Methods II
This module introduces students to a range of approaches for analysing and handling data. It will include covering statistical methods for quantitative data and methodological approaches for qualitative data. It emphasises that the method of analysis is not determined by the method of collection.

British Social Policy - Beyond Welfare?
This module provides students with an understanding of recent trends in social policy development and of the current social and economic context of policy making in the UK. The question underpinning the module is 'Where is British Social Policy heading?'

Researching Social Policy
This module is concerned with the politics of social research, rather than research methods and methodology. It addresses issues such as: how are certain topics identified as subjects for research, how is research commissioned and funded, and what are the relationships between research and the policy process. It draws on real-life experiences of doing research and being researched to explore these issues.

The modules on Social Research Methods I and Social Research Methods II cover a wide range of approaches, including the 'qualitative' traditions, plus mixed methods.

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This Master of Public Health course is offered by coursework and dissertation. Students can choose to pursue one of two specialisations offered - Public Health Practice, or Research Methods. Read more

Introduction

This Master of Public Health course is offered by coursework and dissertation. Students can choose to pursue one of two specialisations offered - Public Health Practice, or Research Methods.

Course description, features and facilities

Both specialisations offered within this course will provide graduates with a suitable background and generalist qualification for a career in public health research or practice.

The course provides a foundation in the research discipline of epidemiology, biostatistics, qualitative research methods, health economics and health promotion, as well as the broader social context in which public health programs are planned, delivered and evaluated.

Structure

Key to availability of units:
S1 = Semester 1; S2 = Semester 2; S3 = summer teaching period; N/A = not available in 2015;
NS = non-standard teaching period; OS = offshore teaching period; * = to be advised

All units have a value of six points unless otherwise stated.

Note: Units that are indicated as N/A may be available in 2016 or 2017.

Take all units (30 points):

S1, S2 PUBH4401 Biostatistics I
S1 PUBH4403 Epidemiology I
S2 PUBH5749 Foundations of Public Health
S2 PUBH5752 Health Systems and Economics
S1 PUBH5754 Health Promotion I

Practice specialisation

Take all units (24 points):

S2 PUBH5758 Public Health Practicum (24 points)

Take unit(s) to the value of 24 points:

Group A

S1, S2 PUBH5712 Dissertation (full-time) (24 points)
S1, S2 PUBH5714 Dissertation (part-time) (24 points)

Take unit(s) to the value of 18 points:

Group B

NS AHEA5755 Aboriginal Health
S2 PAED4401 Research Conduct and Ethics
S1 PUBH5751 Disease Prevention in Population Health
NS PUBH5757 Clinical Epidemiology
NS PUBH5759 Epidemiology II
NS PUBH5761 Epidemiology and Control of Communicable Diseases
S1 PUBH5763 Leadership and Management of Health Services
S2 PUBH5769 Biostatistics II
S1 PUBH5783 Health in an Era of Environmental Change
N/A PUBH5784 Special Topics in Public Health
NS PUBH5785 Introductory Analysis of Linked Health Data
NS PUBH5801 Economic Evaluation of Health Care
NS PUBH5802 Advanced Analysis of Linked Health Data
NS PUBH5804 Food and Nutrition in Population Health
N/A PUBH5805 Qualitative Research Methods in Health
NS RMED4403 Health Program Evaluation

Research Methods specialisation

Take all units (24 points):

S2 PAED4401 Research Conduct and Ethics
NS PUBH5759 Epidemiology II
S2 PUBH5769 Biostatistics II
N/A PUBH5805 Qualitative Research Methods in Health

Take unit(s) to the value of 24 points:

Group A

S1, S2 PUBH5712 Dissertation (full-time) (24 points)
S1, S2 PUBH5714 Dissertation (part-time) (24 points)

Take unit(s) to the value of 18 points:

Group B

NS AHEA5755 Aboriginal Health
S1 PUBH5751 Disease Prevention in Population Health
NS PUBH5757 Clinical Epidemiology
NS PUBH5761 Epidemiology and Control of Communicable Diseases
S1 PUBH5763 Leadership and Management of Health Services
S1 PUBH5783 Health in an Era of Environmental Change
N/A PUBH5784 Special Topics in Public Health
NS PUBH5785 Introductory Analysis of Linked Health Data
NS PUBH5801 Economic Evaluation of Health Care
NS PUBH5802 Advanced Analysis of Linked Health Data
NS PUBH5804 Food and Nutrition in Population Health
NS RMED4403 Health Program Evaluation

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