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Masters Degrees (Decision Science)

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The UCL MSc in Health Economics and Decision Science spans the disciplines of economics, statistics and epidemiology - training students in applied problems, while providing the theoretical foundations expected of an outstanding UCL postgraduate degree. Read more
The UCL MSc in Health Economics and Decision Science spans the disciplines of economics, statistics and epidemiology - training students in applied problems, while providing the theoretical foundations expected of an outstanding UCL postgraduate degree. Strong links to industry and a severe shortage of skills in this area will ensure that graduates of this program are highly employable.

Degree information

Students choose between a decision science or economics stream and complete eight taught modules and a project. Some students will have the opportunity of an industry internship. All graduates will understand how the political, economic and physical context of health systems, frames the application of economics and decision science. Graduates will be able to conduct rigorous cost effectiveness analyses of health technologies and interventions.

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).

Core modules - at least four modules (60 credits) must be selected from the following list. The selection of core modules is specific to the student's preferred stream.
-Health Systems in a Global Context
-Health Policy and Reform
-Economic Evaluation
-Introductory Microeconomics
-Medical Statistics
-Econometrics
-Key Principles of Health Economics
-Modelling for Decision Science
-Microeconomics for Health

Optional modules
-Bayesian Methods in Economic Evaluation
-Health Economics
-Social Determinants of Health
-Concepts and Controversies in Global Health
-Climate Change and Health
-The PPE of Health
-Medical Statistics II
-Research Methods and Evidence for Global Health
-Economics of Health and Population
-Urban Health

In addition to the modules listed, student may selected one optional module from any department in UCL.

Dissertation/report
All students undertake an indepedant research project, which culminates in a dissertation of up to 10,000 words (60 credits). Some students may conduct their research project together with industry partners.

Teaching and learning
Teaching will be delivered using a wide range of methods including classroom teaching, peer-led seminars, online lectures and practical exercises, moderated debates, group exercises and reading and writing tasks. Assessment varies from written examinations, to essays, portfolios and oral presentations.

Placement
A number of students will have the opportunity to undertake an industry placement. This will not be assessed as part of the course and access to placements is voluntary and based on open competition.

Careers

There is currently a significant shortage of specialists in health economics and decision science. Graduates of the MSc in Health Economics and Decision Science may go on to work within the pharmaceutical industry, local, national government departments, international organizations, think tanks, consultancy or in academia among other opportunities.

Why study this degree at UCL?

UCL offers a unique, multidisciplinary environment in which to study health economics and decision science. The teaching team comprises economists, statisticians, epidemiologists, mathematicians and public health doctors among others. As a world-leading university, we research, publish and consult in the topics we teach. Our strong links to industry, policy and academia enhance the relevance of our teaching and the employment opportunities of our graduates.

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This course explores recent developments in theories of behavioural decision-making science. It will enable you to critically examine theories of judgement and decision-making motivated by research in memory, perception, categorisation, reasoning, social psychology, economics, political and management sciences. Read more
This course explores recent developments in theories of behavioural decision-making science. It will enable you to critically examine theories of judgement and decision-making motivated by research in memory, perception, categorisation, reasoning, social psychology, economics, political and management sciences. The career-focused modules are designed to build on your workplace skills and develop new skills.

-This course will enable you to develop the skills to evaluate research findings and to relate these findings to practical applications and solutions. It facilitates and encourages interaction between theory, policy and practice in relation to people's judgements and choices in politics, business, retail, health, leisure and sport.
-You will benefit from regular public lectures organised by the Group for Decision, Thinking and Risk and delivered by internationally recognised researchers in the fields of decision-making, thinking and risk. In addition, you can attend weekly departmental research seminars, where international scholars and staff members present recent research findings.

What will you study?

You will cover recent developments in normative, descriptive and experience-based theories of choice, as well as the impact of experience and expertise on judgements and choice. You will be introduced to applications of judgement and decision-making research in areas such as consumer behaviour, politics, sports, economics and health, providing a firm basis in both the theory and practice of cognitive science and decision-making. You will also explore a selection of current research topics relevant to individual and managerial decision-making, wellbeing and policy-making.

Assessment

Assessment methods include essays, in-class tests, unseen examinations, laboratory reports and a dissertation.

Course structure

Please note that this is an indicative list of modules and is not intended as a definitive list.

Core modules
-Applications of Behavioural Decision Science
-Psychology Dissertation
-Research Design and Analysis
-The Psychology of Thinking, Judgement and Decision-Making
-Applications of Psychological Research
-The Psychology of Health and Well Being

Optional modules to be confirmed.

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Goal of the pro­gramme. Data science combines computer science and statistics to solve exciting data-intensive problems in industry and in many fields of science. Read more

Goal of the pro­gramme

Data science combines computer science and statistics to solve exciting data-intensive problems in industry and in many fields of science. Data scientists help organisations make sense of their data. As data is collected and analysed in all areas of society, demand for professional data scientists is high and will grow higher. The emerging Internet of Things, for instance, will produce a whole new range of problems and opportunities in data analysis.

In the Data Science master’s programme, you will gain a solid understanding of the methods used in data science. You will learn not only to apply data science: you will acquire insight into how and why methods work so you will be able to construct solutions to new challenges in data science. In the Data Science master’s programme, you will also be able to work on problems specific to a scientific discipline and to combine domain knowledge with the latest data analysis methods and tools. The teachers of the programme are themselves active data science researchers, and the programme is heavily based on first-hand research experience.

Upon graduating from the Data Science MSc programme, you will have solid knowledge of the central concepts, theories, and research methods of data science as well as applied skills. In particular, you will be able to

  • Understand the general computational and probabilistic principles underlying modern machine learning and data mining algorithms
  • Apply various computational and statistical methods to analyse scientific and business data
  • Assess the suitability of each method for the purpose of data collection and use
  • Implement state-of-the-art machine learning solutions efficiently using high-performance computing platforms
  • Undertake creative work, making systematic use of investigation or experimentation, to discover new knowledge
  • Report results in a clear and understandable manner
  • Analyse scientific and industrial data to devise new applications and support decision making.

The MSc programme is offered jointly by the Department of Computer Science, the Department of Mathematics and Statistics, and the Department of Physics, with support from the Helsinki Institute for Information Technology (HIIT) and the Helsinki Institute of Physics (HIP), all located on the Kumpula Science campus. In your applied data science studies you can also include multidisciplinary studies from other master's programmes, such as digital humanities, and natural and medical sciences.

Further information about the studies on the Master's programme website.

Pro­gramme con­tents

The Data Science MSc programme combines elements from computer science and mathematical sciences to provide you with skills in topics such as machine learning, distributed systems and statistical methods. You might also find that knowledge in a particular scientific field is useful for your future career. You can obtain this through elective studies in the MSc programme, or it might already be part of your bachelor-level degree.

Studies in the Data Science MSc programme include both theoretical and practical components, including a variety of study methods (lectures, exercises, projects, seminars; done both individually and in groups). Especially in applied data science, we also use problem-based learning methods, so that you can address real-world issues. You will also practise academic skills such as scientific writing and oral presentation throughout your studies. You are encouraged to include an internship in your degree in order to obtain practical experience in the field.

Elective studies give you a wider perspective of Data Science. Your elective studies can be an application area of Data Science (such as physics or the humanities), a discipline that supports application of Data Science (such as language technology), or a methodological subject needed for the development of new Data Science methods and models (such as computer science, statistics, or mathematics).



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The fields of science communication and public engagement are currently enjoying unprecedented growth. Read more

The fields of science communication and public engagement are currently enjoying unprecedented growth. This is being driven by a greater need to demonstrate the impact of publicly funded research, the need for science to be valued, increased government scrutiny and a desire for a stronger evidence base for policy decisions. Many career opportunities are emerging at the interface between science and various stakeholder groups and ever more creative methodologies for science engagement are being explored.

Our part-time online distance learning programme provides an opportunity to gain a formal qualification in science communication without having to leave your job or move to a different location. You may elect to begin with the Post-Graduate Certificate in the first instance and then decide to study for a Diploma and/or a Master’s degree. You will engage with other students from around the world, from a variety of different academic and professional backgrounds and you will enjoy a rich learning experience while studying on the programme.

You will experience a variety of science communication and public engagement methodologies and issues. In the process, you will develop critical thinking and self-evaluation skills through reflective practice. Your learning in individual courses is transferable, ensuring interconnection across the programme, thus providing opportunities for deeper learning and for the application of key principles in different contexts.

The programme attracts students from across the globe, from a range of academic and professional backgrounds and provides a formal qualification for those working in science communication and public engagement or a conversion route for those interested in moving into this field.

Online learning

Our online learning technology is fully interactive, award-winning and enables you to communicate with our highly qualified teaching staff from the comfort of your own home or workplace.

Our online students not only have access to Edinburgh’s excellent resources, but also become part of a supportive online community, bringing together students and tutors from around the world.

Programme structure

The programme can be studied to PG Certificate, PG Diploma or Masters level – if you are interested, in a formal qualification in science communication then sign up for our Post Graduate Certificate. You can then opt to continue to the Diploma and the Masters degree.

Year 1 (Certificate) - courses currently on offer include:

  • Introduction to Science Communication and Public Engagement
  • Science and Society A
  • Science and Society B
  • Principles and Practice in Public Engagement with Science
  • Science Education
  • The Role of Social Media in Science Communication

Year 2 (Diploma) - courses currently on offer include:

  • Dialogue for Science Communication and Public Engagement
  • Science, Policy and Practice
  • Science and the Media
  • Effective Exhibit and Programme Development
  • Creative Arts in Science Engagement
  • Principles and Practice in Public Engagement with Science

Year 3 (Masters)

Dissertation project.

Career opportunities

To address the need for effective science communication and public engagement with science, there has been a significant rise in opportunities available for professionals with the specialist knowledge, skills and attributes necessary to pursue roles at the interface between scientific research and public.

These roles can be found in, for example, Higher Education Institutions, Research Centres, Museums, Science Centres, Learned Societies and consultancies for democratic decision-making. Examples of specific roles are engagement managers, information and education officers, policy and knowledge brokers, in addition to the traditional science communicator role.



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The digital revolution has led to an unprecedented volume of information about consumers, which progressive organisations are eager to understand and use. Read more

The digital revolution has led to an unprecedented volume of information about consumers, which progressive organisations are eager to understand and use. This innovative masters degree will give you the practical skills to analyse consumer data and provide insights for successful marketing strategies.

Taught by leading academics from Leeds University Business School and School of Geography, you’ll explore a range of analytical techniques including applied Geographic Information Systems (GIS) and retail modelling, consumer and predictive analytics and data visualisation. You’ll also develop the softer skills to use the results of these analyses to inform decisions about marketing strategy.

Thanks to our connections with businesses worldwide, you’ll have access to emerging trends in topics such as consumer behaviour, decision science and digital and interactive marketing. You’ll further develop your practical skills with the opportunity to work on a live data project provided by a company.

Academic excellence

This courseoffers you a rare combination of teaching expertise; the Business School’s academic excellence in Marketing alongside world-class teaching from the School of Geography, which draws on the knowledge of the Centre for Spatial Analysis and Policy.

The University of Leeds is a major centre for big data analytics and you’ll benefit from affiliation with the UK’s Consumer Data Research Centre. The centre aims to make data that are routinely collected by businesses and organisations accessible for academic purposes. Coordinating and analysing this large and complex data has the potential to increase productivity and innovation in business, as well as to inform public policy and drive development.

Read an interview with the academic team to learn more about our expertise and the growing importance of this emerging subject area.

Course content

Core modules will introduce you to a range of analytical methods, ensuring you develop a solid foundation in the essential skills for consumer analytics and marketing strategy.

You’ll learn how to analyse geographic data using GIS software and understand the application of this in retail modelling, to evaluate new markets and locations. You’ll study predictive analytics, big data and consumer analytics, business analytics and decision science, and learn how to communicate results through data visualisations.

Alongside this, you’ll learn how to deploy data to inform decisions about marketing strategy. Marketing modules include marketing strategy, consumer behavior and direct, digital and interactive marketing. You’ll also deliver your own data-driven marketing research project for a company.

Optional modules allow you to further your knowledge in a related area of interest, either corporate social responsibility, internal communications and managing change, or applied population and demographic analysis.

By the end of the course, you’ll submit an independent project. You can either research a topic in-depth and submit a dissertation, or gain practical experience through a consultancy project working with an external organisation.

Course structure

Compulsory modules

You’ll take the nine compulsory modules below, plus your dissertation, which can be a choice of either a research dissertation or marketing consultancy project.

  • Geographic Data Visualisation & Analysis 15 credits
  • Big Data and Consumer Analytics 15 credits
  • Predictive Analytics 15 credits
  • Applied GIS and Retail Modelling 15 credits
  • Business Analytics and Decision Science 15 credits
  • Consumer Behaviour 15 credits
  • Marketing Research Consultancy Project 15 credits
  • Direct, Digital and Interactive Marketing 15 credits
  • Marketing Strategy 15 credits
  • Dissertation OR Marketing Consultancy Project 30 credits

Optional modules

You'll take one further optional module.

  • Applied Population and Demographic Analysis 15 credits
  • Corporate Social Responsibility and Sustainability 15 credits
  • Internal Communications and Change Management 15 credits

For more information on typical modules, read Consumer Analytics and Marketing Strategy MSc in the course catalogue

Learning and teaching

We use a range of teaching methods so you can benefit from the expertise of our academics, including lectures, workshops, seminars, simulations and tutorials. Company case studies provide an opportunity to put your learning into practice.

Independent study is also vital for this course, allowing you to prepare for taught classes and sharpen your own research and critical skills.

Assessment

Assessment methods emphasise not just knowledge, but essential skills development too. You’ll be assessed using a range of techniques including exams, group projects, written assignments and essays, in-course assessment, group and individual presentations and reports.

Career opportunities

As a graduate of this course you will be equipped with advanced skills in consumer analytics and marketing strategy, ideal for those wishing to pursue a career in consumer data analytics, marketing and/or management.

Due to the digital revolution, companies from around the world and in many industrial sectors have access to greater amounts of data.

The most progressive companies in the world are particularly interested in marketing graduates with strong analytical skills, and typical roles could include marketing or consumer data analyst, direct marketing manager, marketing manager, retail manager, or marketing or management consultant.

Careers support

As a masters student you will be able to access careers and professional development support, which will help you develop key skills including networking and negotiating, and put you in touch with potential employers.

Our dedicated Professional Development Tutor provides tailored academic and careers support to marketing students. They work in partnership with our academics to help you translate theory into practice and develop your interpersonal and professional business skills.

You can expect support and guidance on career choices, help in identifying and applying for jobs, as well as one-to-one coaching on interpersonal and communication skills.

Read more about careers support at the Business School.



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With a master’s degree in Web Science you will be able to study and solve problems on the web. Our interdisciplinary curriculum emphasises computer science and builds bridges to social sciences, economics, studies of the law, linguistics and mathematics. Read more

About the Program

With a master’s degree in Web Science you will be able to study and solve problems on the web. Our interdisciplinary curriculum emphasises computer science and builds bridges to social sciences, economics, studies of the law, linguistics and mathematics. All mandatory courses are taught in English.

In general, our programme aims at people with a bachelor’s degree or a minor in computer science. Our programme even is free of tuition. The medium of instruction is English.

More information under: http://west.uni-koblenz.de/en/mws

Employment Outlook

Graduates from the institute WeST have found interesting positions at successful companies, started their own businesses or continued towards a Ph.D. Institute WeST has a limited number of places available each year for pursueing a Ph.D. If you excel earning a master's degree in Web Science you will be in pole position for continuing with doctoral studies.

Studying in Koblenz

Koblenz is one of the oldest and most attractive cities in Germany with its surroundings honoured as UNESCO World Cultural Heritage. The university of Koblenz-Landau has close contacts to leading companies, offering possibilities for internships, collaboration and project experiences.

Program Structure

Our interdisciplinary curriculum emphasises computer science and builds bridges to social sciences, economics, law, linguistics and mathematics. All mandatory courses are taught in English.

The curriculum is organized in seven module groups:

Foundations of Web Science (two modules) establishes the main idea of Web Science. It provides an interdisciplinary primary view of the web and of more abstract web structures.

The Computer Science track (three modules) teaches the essential technical aspects, namely web engineering, semantic web and web retrieval.

Web and Society (two out of four modules) considers interaction of the web and different user groups: citizens, customers, entrepreneurs, and interest groups.

The module group Elective Courses in Computer Science provides a wide range of technical topics. Modules may be choosen freely from all Master courses in computer science with relevance to the web given at the University of Koblenz-Landau (three modules or more, mininum 18 ECTS).

Elective Interdisciplinary Courses contain web-related modules offered by our university from other disciplines (such as economy, social sciences, linguistics, anthropology, communication theory etc.). Students have to freely elect at least two modules (12 ECTS).

Topics for seminars and research lab can be freely chosen from Web Science subjects. Furthermore, this module group contains a social skills and leadership training..

The topic of the master's thesis can also be freely chosen from any Web Science subjects.

More information about the curriculum can also be found under: http://west.uni-koblenz.de/en/mws/curriculum

Requirements

Higher Education Entrance Qualification -

It is a legal requirement in Germany that students own a Higher education entrance qualification („Hochschulzugangsberechtigung“) respectively a Master entrance qualification („Masterzugangsberechtigung“), proven by school leaving certificates or studies completed at secondary education level.

Entrance qualification is not checked by us, but uni-assist (see application process), therefore please refrain from asking us if your diploma will be accepted. Uni-assist provides some further information on higher education entrance qualification.

Academic Background in Computer Science -

You need some academic background in computer science, such as a

bachelor's degree in computer science, business informatics, Computervisualistik (as offered by the University of Koblenz-Landau), Information management (as offered by the University of Koblenz-Landau until 2012 if 60 ECTS in computer science were acquired) or similar.

Students with a minor in computer science (at least 60 European Credit Points) can apply, too. Here we have to make a decision on a by-case-basis. To get an educated guess please contact the course guidance.

Only diplomas of international accredited universities will be accepted. If you are unshure if your academic background fulfils our requirements, do not hesitate to contact us: . Non-academic, practical experience in computer science alone does not qualify you for our programme.

Sufficient Grades in Previous Studies -

The German grading system ranges from 1 ("very good") to 6 ("insufficient"). Lower numbers mean better grades. To be eligible for our programme, the grades from your previous studies must be between 1 and 2.5. Grade conversion into the German system is done by uni-assist (cf. application procedure), so we cannot tell you if your GPA fis sufficient. For a first, non-binding estimation on your eligibility you might want to check the calculator provided by the University of Paderborn.

English Language Proficiency -

The medium of instruction for all required courses is English, some additional electives can be taken in German. Thus, we require a certain level of English proficiency such that studies can be undertaken successfully. Thus, a standardised language certificate is required – proof that your previous studies were held in English are not sufficient and not negiotiable. We accept three types of language proficiency certificates:

a TOEFL result of at least 79 (internet based), 550 (paper based) or 213 (computer based)

IELTS test with 6.5 points mininum

Cambridge certificate at level B2 or higher (find an exam center)

Proficiency of German language is not a requirement for application. However, additional elective courses are available in German, and we recommend to learn some basic German for daily life. Some hints on learning German can be found at Deutsche Welle.

Motivational Letter -

Applicants need to supply a motivational letter. Please do not send lenghty standard letters describing your general interest in computer science and your appreciation of the German education system. Instead, refer only to our specific programme and follow these guidelines:

Length should be between 150 and 300 words.

The letter must be written in English.

Specify what you learnt and found particularly interesting in your previous studies or practical experiences. Tell us how you want to deepen these previous experience in our master's programme. You can also describe what you expect to learn here for your future job. You should always refer to our curriculum, especially the module groups Foundations of Web Science, Major Subject Computer Science und Major Subject Web and Society. Make clear that you know our curriculum and point out why you have chosen our programme above others.

Further information under: http://west.uni-koblenz.de/en/mws/requirements

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Technologies based on the intelligent use of data are leading to great changes in our everyday life. Data Science and Engineering refers to the know-how and competence required to effectively manage and analyse the massive amount of data available in a wide range of domains. Read more
Technologies based on the intelligent use of data are leading to great changes in our everyday life. Data Science and Engineering refers to the know-how and competence required to effectively manage and analyse the massive amount of data available in a wide range of domains.

We offer a two-year Master of Science in Computer Science centered on this emerging field. The backbone of the program is constituted by three core units on advanced data management, machine learning, and high performance computing. Leveraging on the expertise of our faculty, the rest of the program is organised in four tracks, Business Intelligence, Health & Life Sciences, Pervasive Computing, and Visual Computing, each providing a solid grounding in data science and engineering as well as a firm grasp of the domain of interest.

By blending standard classes with recitations and lab sessions our program ensures that each student masters the theoretical foundations and acquires hands-on experience in each subject. In most units credit is obtained by working on a final project. Additional credit is also gained through short-term internship in the industry or in a research lab. The master thesis is worth 25% of the total credit.

TRACKS

• Business Intelligence. This track builds on first hand knowledge of business management and fundamentals of data warehousing, and focuses on data mining, graph analytics, information visualisation, and issues related to data protection and privacy.
• Health & Life Sciences. Starting from core knowledge of signal and image processing, bioinformatics and computational biology, this track covers methods for biomedical image reconstruction, computational neuroengineering, well-being technologies and data protection and privacy.
• Pervasive Computing. Security and ubiquitous computing set the scene for this track which deals with data semantics, large scale software engineering, graph analytics and data protection and privacy.
• Visual Computing. This track lays the basics of signal & image processing and of computer graphics & augmented reality, and covers human computer interaction, computational vision, data visualisation, and computer games.

PROSPECTIVE CAREER

Senior expert in Data Science and Engineering. You will be at the forefront of the high-tech job market since all big companies are investing on data driven approaches for decision making and planning. The Business Intelligence area is highly regarded by consulting companies and large enterprises, while the Health and Life Sciences track is mainly oriented toward biomedical industry and research institutes. Both the Pervasive and the Visual Computing tracks are close to the interests of software companies. For all tracks a job in a start-up company or a career on your own are always in order.

Senior computer scientist.. By personalizing your plan of study you can keep open all the highly qualified job options in software companies.

Further graduate studies.. In all cases, you will be fully qualified to pursue your graduate studies toward a PhD in Computer Science.

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Many of the most pressing issues facing New Zealand and the world today—climate change, the loss of biodiversity, and how to respond to new technologies—can't be solved using traditional scientific approaches. Read more

Many of the most pressing issues facing New Zealand and the world today—climate change, the loss of biodiversity, and how to respond to new technologies—can't be solved using traditional scientific approaches.

In the age of social media, clickbait headlines and 'fake news', new means of communicating science and engaging different groups and communities are required.

The 180-point Master of Science in Society is a cross-disciplinary programme that combines taught courses, research projects and your choice of final project to give you a practical understanding of the role of science in society.

You'll learn how to engage New Zealanders in conversations about the science that impacts their lives so they can make informed decisions. Find out how you can influence policy change and research priorities.

Broad perspectives

Develop your understanding of contemporary scientific issues, and draw from a range of diverse fields such as philosophy, history and the creative arts to gain a broader and more nuanced perspective on science.

Gain an insight into the range of perspectives different communities have on scientific and environmental issues, and explore the important role of mātauranga Māori and other indigenous knowledge in science decision-making.

The Master of Science in Society is suited to students who are interested in science but don't want to pursue a traditional postgraduate science research programme. If you're interested in more effective public engagement around key scientific issues like conservation and pest eradication, or you're keen to pursue a career in science policy or advocacy, this degree is a good choice for you.

Learn from the best

Learn from award-winning academics and professionals who are leaders in the field of science communication, public engagement with science, natural and social science, the humanities and the arts. You'll also be exposed to a wide range of expertise from across the university and from visiting experts.

How you’ll study

The Master of Science in Society has two parts. The first part takes place in Trimester One, is based on-campus and is compulsory for all students.

In Part 1, you'll focus on developing your critical thinking and communication skills in four taught courses. Look at the theory and practice of science communication, and gain a grounding in contemporary scientific issues and theories. Explore perspectives on science from different cultures and from across the humanities and social sciences.

You'll choose from three of four core 400-level courses, and complete an additional approved course worth 15 points.

The field component of SCIS 589, the Science Communication Project, also takes place during Trimester One.

You'll go on to put your learning into practice in Part 2 by completing your science communication project and a research essay. You'll also choose to do a work placement or a research project, or choose other relevant courses from another discipline of your choice, such as Māori Studies, Public Policy or Conservation Biology.

While working on your final projects you'll be supervised by subject experts from within and outside of the university, and will continue to meet regularly with your fellow students in tutorials or seminar sessions.

Study off-campus

You can complete Part 2 of your Master's remotely if your placement or research project takes place outside Wellington. You'll need to have sufficient internet access to take part in online seminars, lectures and workshops.

Duration and workload

The Master of Science in Society will take you three trimesters (one year) of full-time study, or up to three years if you are studying part time.

If you are studying full time, you can expect a workload of 40–45 hours a week for much of the year.

If you're a part-time student, you can estimate your workload by adding up the number of points you'll be doing. One point is roughly equal to 10–12 hours work.



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Our MSc in Social Science Research Methods aims to provide advanced training in research methods across the full range of the social sciences. Read more
Our MSc in Social Science Research Methods aims to provide advanced training in research methods across the full range of the social sciences. 

You will be provided with a thorough theoretical and practical knowledge of how to construct effective research studies, of the variety of data collection methods available to the social scientist and of the principal methods of analysing social scientific data. You will also be introduced to the political and ethical frameworks within which social science research is conducted, and to some of the ways in which the results of social science research are disseminated.

The course pathways have ESRC recognition and they each provide the appropriate training basis for proceeding to a PhD. These programmes provide extensive opportunities for interdisciplinary study, the application of social research expertise for occupational career development, and the pursuit of substantive areas of interest at postgraduate level. 

Science and Technology Studies pathway:

The Science and Technology Studies pathway through the Social Science Research Methods MSc is suitable for all students with an interest in the social dimensions of science and technology. We have research expertise in a range of substantive and methodological approaches and can offer supervision and training for students interested in:

• Sociology of science and technology, including natural sciences, biotechnology, medicine and genomics
• Nature, distribution and classification of expertise
• Public understanding of, and engagement with, science and technology
• Use of scientific advice and other forms of expertise in decision-making

Structure

The course can be completed in one year with full-time study or in three years by part-time study.

You will be required to complete six 20-credit modules - five core research modules and one specialist pathway module. In all modules, you will have the opportunity to engage with literature and research relevant to your pathway.

On successful completion of the taught component, you will prepare a dissertation of a maximum 20,000 words. The 60-credit dissertation component requires independent study. You will choose your dissertation topic in agreement with your supervisor.

Core modules:

Developing Core Research Skills
Foundations of Social Science Research
Qualitative Research Methods
Quantitative Research Methods
Research Applications
Introduction to Science, Technology and Society
Dissertation

Teaching

Your programme will be made up of scheduled learning activities (including lectures, seminars, tutorials and practical sessions) and guided independent study.

You will be expected to actively engage in all the educational activities on your programme of study, to prepare for and attend all scheduled teaching activities, and continue your development as an independent and self-directed learner.

Assessment

You will have to successfully complete the taught component which comprises of 120 credits.

On successful completion of the taught component, you will prepare a dissertation of a maximum 20,000 words

Career prospects

This programme provides knowledge and expertise suitable for careers in research and development, business, market studies, public agencies at international, national and local levels, education, teaching and other public services work, and voluntary organisations.

It also provides appropriate training for proceeding to a PhD.

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Learning how to make new discoveries that will contribute to a better understanding of normal and dysfunctional human behaviour and how to influence that behaviour. Read more

Overview

Learning how to make new discoveries that will contribute to a better understanding of normal and dysfunctional human behaviour and how to influence that behaviour.

Have you always wanted to discover what it is that makes people tick? Do you have questions about human behaviour that have not yet been tackled? Whether you are driven by scientific curiosity or are intrigued by the potential for more accurate diagnoses and for effective interventions in health or education, the Research Master’s in Behavioural Science is for you.

See the website http://www.ru.nl/masters/bs

Multidisciplinary approach

At Radboud University, we believe that a multidisciplinary approach is necessary to gain the best understanding of human behaviour. We combine knowledge and research methods from the fields of psychology, educational sciences and communication science. These disciplines are not taught separately but instead are brought together in most of our courses, making our approach unique.

Half of the programme consists of research experience. There are many issues you could tackle and a large research faculty you could work with. For example, there are over fifty staff members at the Behavioural Science Institute. The institute has internationally renowned researchers with expertise in a very wide range of topics. And that's not counting the other top scientists we invite to give workshops.

Why study Behavioural Science at Radboud University?

- Students get substantial hands-on research with a minor and major research project on different topics.
- We teach our students research methods and statistics, which we bring to life by revealing their applications to current hot issues in the field.
- Students are free to choose courses and research topics to create their own unique programme.
- Students can do the internship for their major research project abroad. Financial support for international research internships is available within Radboud University and the Behavioural Science Institute.
- You will participate in group-oriented education and be part of a small, select group of highly motivated national and international students.
- Master’s students are free to use any of the state-of-the-art equipment and labs found on campus, including the Virtual Reality Lab, Observational Lab and eye-tracking equipment.
- We have three Faculty Assistant positions for ambitious students to work alongside their course.
- A majority of our graduates gain PhD and other research positions and many students publish their Master’s thesis in peer-reviewed journals.

Discovering more

Due to our interdisciplinary approach, we accept Bachelor’s students from a wide variety of related fields, like psychology, pedagogy, educational science, biology, artificial intelligence and communication science. Simply put, this programme is for social scientists who want to discover the how and why behind human behaviour.

Quality label

The Master's in Behavioural Science was recently awarded the quality label ‘Top Programme' in the Keuzegids Masters 2015 (Guide to Master's programmes), which indicates the programme belongs to the very best programmes in Dutch Master's education, across the entire range of disciplines.

Our approach to this field

The staff of the Behavioural Science Institute at Radboud University originate from the fields of psychology, educational sciences and communication science. Together they tackle issues regarding human behaviour. We believe that in order to fully understand human behaviour you need to use knowledge from all these fields together instead of separately. For example, looking at a psychological issue from a communication perspective could offer new and valuable insights that will lead to better diagnosis or interventions.

At Radboud University we will not just teach you existing research methods in the different fields. You will also learn to look beyond conventions and combine or adjust methods from other disciplines to enable you to do research that will answer your questions. You will not only become a highly skilled researcher but also an innovative one.

Our research in this field

More than half of the Master’s programme in Behavioural Science consists of research. In the first year you’ll do a minor project in which you choose from a list research themes that are provided by staff members or PhD students.

In the second year, you’ll do a major project in the form of a nine month internship which provides you with the experience - and data - needed to write your Master’s thesis. Most internships are carried out within the Behavioural Science Institute (BSI), working closely with colleagues, many of whom are internationally renowned researchers. However, there is also the option to arrange an internship abroad.

To broaden your scope, we expect you to choose different research themes for the minor and major projects, preferably in different groups within the BSI.

Examples of Major Projects in the field of Behavioural Science
- Differential behaviours of teachers toward boys and girls in science classes
- The role of maternal pregnancy stress and other general children’s health issues
- The recovery potential of within-workday break activities
- The effectiveness of an intervention promoting water consumption via children’s social networks
- The effectiveness of video games to reduce anxiety in children using a randomised controlled trail
- The role of experience on clinical diagnostic decision-making
- Exploring the underlying cognitive mechanisms to learn more about the ability to learn to categorise new face groups

Career prospects

The career prospects of a graduate of Behavioural Science are good; almost 100% of our alumni have a job.

- Skills and knowledge
Besides the necessary theoretical knowledge about behavioural science and training in advanced quantitative data analysis, this programme also offers courses (7 EC in total) that will teach you additional skills that every researcher needs: to understand the ethics of research, to understand the process of academic publishing and grant proposals, and to comment on papers and proposals of others. We also encourage students to participate in workshops, colloquia, symposia and conferences to gain experience in the international academic field of behavioural science.

See the website http://www.ru.nl/masters/bs

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Data Science brings together computational and statistical skills for data-driven problem solving. Read more
Data Science brings together computational and statistical skills for data-driven problem solving. This rapidly expanding area includes machine learning, deep learning, large-scale data analysis and has applications in e-commerce, search/information retrieval, natural language modelling, finance, bioinformatics and related areas in artificial intelligence.

Degree information

The programme comprises core machine learning methodology and an introduction to statistical science, combined with a set of more specialised and advanced options covering computing and statistical modelling. Projects are offered both within UCL Computer Science and from a wide range of industry partners.

Students undertake modules to the value of 180 credits.

The programme consists of three compulsory modules (45 credits), five optional modules (75credits) and a dissertation/report (60 credits).

Core modules
-Applied Machine Learning
-Introduction to Supervised Learning
-Introduction to Statistical Data Science

Optional modules - students choose a minimum of 30 credits and a maximum of 60 credits from the following optional modules:
-Cloud Computing (Birkbeck)
-Machine Vision
-Information Retrieval & Data Mining
-Statistical Natural Language Processing
-Web Economics

Students choose a minimum of 0 credits and a maximum of 30 credits from these optional Statistics modules:
-Statistical Design of Investigations
-Applied Bayesian Methods
-Decision & Risk

Students choose a minimum of 15 credits and a maximum of 15 credits from these elective modules:
-Supervised Learning
-Graphical Models
-Bioinformatics
-Affective Computing and Human-Robot Interaction
-Computational Modelling for Biomedical Imaging
-Stochastic Systems
-Forecasting

Dissertation/report
All students undertake an independent research project which culminates in a dissertation of 10,000-12,000 words.

Teaching and learning
The programme is delivered though a combination of lectures, seminars, class discussions and project supervision. Student performance is assessed through a combination of unseen written examination, coursework (much of which involves programming and/or data analysis), practical application, and the research project.

Careers

Data science professionals are increasingly sought after as the integration of statistical and computational analytical tools becomes more essential to organisations. A thorough understanding of the fundamentals required from the best practitioners, and this programme's broad base, assists data scientists to adapt to rapidly evolving goals. This is a new degree and information on graduate destinations is not currently available. However, MSc graduates from across the department frequently find roles with major tech and finance companies including:
-Google Deepmind
-Microsoft Research
-Dunnhumby
-Index Ventures
-Last.fm
-Cisco
-Deutsche Bank
-IBM
-Morgan Stanley

Why study this degree at UCL?

The 2014 Research Excellence Framework ranked UCL first in the UK for computer science. 61% of its research work is rated as world-leading and 96% as internationally excellent.

UCL Computer Science staff have research interests ranging from foundational machine learning and large-scale data analysis to commercial aspect of business intelligence. Our extensive links to companies provide students with opportunities to carry out the research project with an industry partner.

The department also enjoys strong collaborative relationships across UCL; and exposure to interdisciplinary research spanning UCL Computer Science and UCl Statistical Science will provide students with a broad perspective of the field. UCL is home to regular machine learning masterclasses and big data seminars.

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Data science brings together computational and statistical skills for data-driven problem solving, which is in increasing demand in fields such as marketing, pharmaceutics, finance and management. Read more
Data science brings together computational and statistical skills for data-driven problem solving, which is in increasing demand in fields such as marketing, pharmaceutics, finance and management. This MSc will equip students with the analytical tools to design sophisticated technical solutions using modern computational methods and with an emphasis on rigorous statistical thinking.

Degree information

The programme combines training in core statistical and machine learning methodology, beginning at an introductory level, with a range of optional modules covering more specialised knowledge in statistical computing and modelling. Students choosing the statistics specialisation will take one compulsory module and up to two additional modules from computer science, with the remaining modules (including the research project) taken mainly from within UCL Statistical Science.

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 dissertation/report (60 credits).

Core modules
-Introduction to Statistical Data Science
-Introduction to Supervised Learning
-Statistical Design of Investigations
-Statistical Computing

Optional modules - st least two from a choice of Statistical Science modules including:
-Applied Bayesian Methods
-Decision & Risk
-Factorial Experimentation
-Forecasting
-Quantitative Modelling of Operational Risk and Insurance Analytics
-Selected Topics in Statistics
-Stochastic Methods in Finance I
-Stochastic Methods in Finance II
-Stochastic Systems

Up to two from a choice of Computer Science modules including:
-Affective Computing and Human-Robot Interaction
-Graphical Models
-Statistical Natural Language Processing
-Information Retrieval & Data Mining

Dissertation/report
All students undertake an independent research project, culminating in a dissertation usually comprising 10,000-12,000 words. Workshops running during the teaching terms provide preparation for this project and cover the communication of statistics.

Teaching and learning
The programme is delivered through a combination of lectures, tutorials and classes, some of which are dedicated to practical work. Assessment is through written examination and coursework. The research project is assessed through the dissertation and a 15-minute presentation.

Careers

Graduates from UCL Statistical Science typically enter professional employment across a broad range of industry sectors or pursue further academic study.

The Data Science MSc is a new programme with the first cohort of students due to graduate in 2017. Recent career destinations for graduates of the related Statistics MSc include:
-Towers Watson, Actuary Analyst
-Proctor & Gamble, Statistician
-Ernst & Young, Audit Associate
-Collinson Group, Insurance Analyst
-UCL, PhD Statistical Science

Employability
Data science professionals will be highly sought after as the integration of statistical and computational analytical tools becomes increasingly essential in all kinds of organisations and enterprises. A solid understanding of the fundamentals is to be expected from the best practitioners. For instance, in applications in marketing, the healthcare industry and banking, computational skills should go along with statistical expertise as graduate level. Data scientists should have a broad background so that they will be able to adapt themselves to rapidly evolving challenges. Recent graduates from the related Statistics MSc have been offered positions as research analysts or consultants, and job opportunities in these areas are increasing.

Why study this degree at UCL?

UCL Statistical Science has a broad range of research interests, but has particular strengths in the area of computational statistics and in the interface between statistics and computer science.

UCL's Centre for Computational Statistics and Machine Learning, in which many members of the department are active, has a programme of seminars, masterclasses and other events. UCL's Centre for Data Science and Big Data Institute are newer developments, again with strong involvement of the department, where emphasis is on research into big data problems.

UCL is one of the founding members of the Alan Turing Institute, and both UCL Statistical Science and UCL Computer Science will be playing major roles in this exciting new development which will make London a major focus for big data research.

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The Middlesex PGCE course in Secondary Science is a one year full-time course. It equips you to inspire pupils through the use of engaging interactive workshops, lectures and structured debates. Read more
The Middlesex PGCE course in Secondary Science is a one year full-time course. It equips you to inspire pupils through the use of engaging interactive workshops, lectures and structured debates. You receive personal attention through regular tutor visits to school placements and individual tutorials. Schools are carefully selected to suit individuals and expose them to imaginative and thought provoking teaching and learning strategies.

The course aims to prepare you for the teaching profession. It will:

Enable you to develop knowledge and understanding of pupils and their learning
Develop your expertise in highly specialised professional skills in a context where you'll need to exercise initiative and take personal responsibility for decision making in complex and unpredictable situations
Equip you with the pedagogic knowledge, understanding and skills to teach effectively across the 11-16 age range
Develop your knowledge and understanding of the Secondary Science curriculum
Enable you to understand, critically evaluate and respond to the needs of children in multicultural, multilingual and multifaith settings and schools in an international, urban environment.
We have a full range of specialist Science and teaching facilities on-site and the course includes specialist mentors fromm our partner schools. There is a strong emphasis on the use of ICT in Science and you will be expected to explore up to date developments in this area.

Two thirds (120 days) of the PGCE Secondary Science course will be on placement. We have excellent relationships with schools in north London, Essex and Hertfordshire and many of our graduates go on to work in their first teaching job at the schools where they had a placement.

In 2012, the secondary teacher training programmes at Middlesex were rated Good with Outstanding Features (by Ofsted), an excellent result for a large and diverse provider of teacher training.

The PGCE Secondary Science with Chemistry course involves students from all three science disciplines working together as a group. Teaching science at Key Stage 3 requires competence across the whole range of the National Curriculum Programme of Study for Science. This involves teaching the concepts and processes of how science works through the study of organisms, behaviour and health, chemical and material behaviour, energy, electricity and forces, and the environment, Earth and universe. This also involves integrating the knowledge, skills and understanding of how science works. The science with chemistry course therefore begins with a general mix of biology, chemistry and chemistry to enable you to teach all three sciences at KS3.

However, you will then be able to focus on teaching chemistry since, as well as being able to teach all the science specified in the National Curriculum Programme of Study for Science at Key Stage 3, you will also be required to specialise in the teaching of chemistry topics at KS4, within a broad and balanced science curriculum.

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The Middlesex PGCE course in Secondary Science is a one year full-time course. It equips you to inspire pupils through the use of engaging interactive workshops, lectures and structured debates. Read more
The Middlesex PGCE course in Secondary Science is a one year full-time course. It equips you to inspire pupils through the use of engaging interactive workshops, lectures and structured debates. You receive personal attention through regular tutor visits to school placements and individual tutorials. Schools are carefully selected to suit individuals and expose them to imaginative and thought provoking teaching and learning strategies.

The course aims to prepare you for the teaching profession. It will:

Enable you to develop knowledge and understanding of pupils and their learning
Develop your expertise in highly specialised professional skills in a context where you'll need to exercise initiative and take personal responsibility for decision making in complex and unpredictable situations
Equip you with the pedagogic knowledge, understanding and skills to teach effectively across the 11-16 age range
Develop your knowledge and understanding of the Secondary Science curriculum
Enable you to understand, critically evaluate and respond to the needs of children in multicultural, multilingual and multifaith settings and schools in an international, urban environment.
We have a full range of specialist Science and teaching facilities on-site and the course includes specialist mentors fromm our partner schools. There is a strong emphasis on the use of ICT in Science and you will be expected to explore up to date developments in this area.

Two thirds (120 days) of the PGCE Secondary Science course will be on placement. We have excellent relationships with schools in north London, Essex and Hertfordshire and many of our graduates go on to work in their first teaching job at the schools where they had a placement.

In 2012, the secondary teacher training programmes at Middlesex were rated Good with Outstanding Features (by Ofsted), an excellent result for a large and diverse provider of teacher training.

PGCE Secondary Science with Physics course involves students from all three science disciplines working together as a group. Teaching science at Key Stages 3 requires competence across the whole range of the National Curriculum Programme of Study for Science. This involves teaching the concepts and processes of how science works through the study of organisms, behaviour and health, chemical and material behaviour, energy, electricity and forces, and the environment, Earth and universe. This also involves integrating the knowledge, skills and understanding of how science works. The PGCE Secondary Science with Physics course therefore begins with a general mix of biology, chemistry and physics to enable you to teach all three sciences at KS3.

However you will then be able to focus on teaching physics since, as well as being able to teach all the science specified in the National Curriculum Programme of Study for Science at Key Stage 3, you will also be required to specialise in the teaching of physics topics at KS4, within a broad and balanced science curriculum.

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This course is offered jointly by Cardiff University School of Social Sciences, Cardiff University School of Journalism, Media and Cultural Studies, and Techniquest, a science discovery centre based in Cardiff. Read more
This course is offered jointly by Cardiff University School of Social Sciences, Cardiff University School of Journalism, Media and Cultural Studies, and Techniquest, a science discovery centre based in Cardiff. 

The course aims to offer knowledge and expertise relating to the organisation and funding of scientific research, the reporting of scientific innovation and controversy, and the role of citizens, experts and the media in decision making.

You will receive practical, hands-on training in presenting science via news media or directly to audiences ranging from school children to the general public.

Distinctive features

This is innovative, interdisciplinary degree based on collaboration between internationally respected academics and a leading science discovery centre.

The programme has strong links to a wide range of media and science organisations including National Museum Wales, Wales Gene Park, local and national media, science communication centres, and policy makers in regional, national and European institutions.

It offers excellent opportunities to develop expertise in an area of increasing importance for policy, industry and scientific communities.

The course offers students the opportunity to take a mixture of research-led and vocationally orientated modules in order to engage with current debates about topics such as: the organisation and funding of scientific research; the reporting of scientific innovation and controversy; and the role of citizens, experts and the media in decision-making about science and technology

Structure

This is a one-year full-time programme.

The MSc in Science Media and Communication is organised around a sequence of five 20-credit specialist modules, one 20-credit option and one 60-credit supervised dissertation on a relevant topic of your choice.

A 20-credit module comprises 200 hours of study, including about 30 hours of contact time, and the MSc as a whole, 1800 hours of study.

Core modules:

Media, Science and Health
International News Production 1
Research Design For Masters Students
Introduction to Science, Technology and Society
Public Engagement with Science and Technology
Dissertation

Teaching

Modules employ a diverse range of teaching including lectures, seminars, group and individual tutorials, and independent guided study. All modules within the programme make use of Cardiff University’s Virtual Learning Environment (VLE) Learning Central, on which you will find course materials, links to related materials and information on assessment.

You will be expected to attend lectures, seminars and tutorials as set out in the timetable for MSc students. These sometimes sit outside the regular pattern of university attendance and may include day, evening and weekend study and on occasion may fall outside the standard semester dates. You will also be expected to undertake independent study in preparation for lectures, seminars and assessments. 

The Presenting Science module offered by Techniquest (subject to availability in any given year) has limited places and involves presenting work to live audience including school children and the general public. As a result, there is an audition at the start of each year, at which students will be selected for the module. Those students who are not selected for this module will need to take an alternative module to complete their taught programme.

Assessment

Taught modules are assessed in ways that reflect their particular learning outcomes. So, as appropriate to the module, and across the programme as a whole, the following in-course assessments are used:

Essay assignments
Portfolios
Fieldwork reports
Oral presentations
News reports, documentaries, posters
A dissertation or extended project.

Career Prospects

This course is particularly suitable for those interested in pursuing careers in science communication, and the interface of scientific knowledge and the public domain. These include: policy research; political communication, public relations, government agencies; statutory and voluntary organisations; ‘think tanks’, museums and schools; and the mass media.

Some previous graduates have gone on to study for higher degrees, whilst others are, or have been, employed in museums, schools, advertising agencies, medical research charities, government department, NGOs, television companies and science communication organisations.

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