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

The University of Helsinki will introduce annual tuition fees to foreign-language Master’s programmes starting on August 1, 2017 or later. The fee ranges from 13 000-18 000 euros. Citizens of non-EU/EEA countries, who do not have a permanent residence status in the area, are liable to these fees. You can check this FAQ at the Studyinfo website whether or not you are required to pay tuition fees: https://studyinfo.fi/wp2/en/higher-education/higher-education-institutions-will-introduce-tuition-fees-in-autumn-2017/am-i-required-to-pay-tuition-fees/

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 minor 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.

Minor studies give you a wider perspective of Data Science. Your minor subject 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).

Selection of the Major

You can specialise either in the core areas of data science -- algorithms, infrastructure and statistics -- or in its applications. This means that you can focus on the development of new models and methods in data science, supported by the data science research carried out at the University of Helsinki; or you can become a data science specialist in an application field by incorporating studies in another subject. In addition to mainstream data science topics, the programme offers two largely unique opportunities for specialisation: the data science computing environment and infrastructure, and data science in natural sciences, especially physics.

Programme Structure

You should be able to complete the MSc Programme in Data Science of 120 credits (ECTS) in two years of full-time study. The programme consists of:
-Common core studies of basic data science courses.
-Several modules on specific topics within data science algorithms, data science infrastructures and statistical data science, and on data science tools.
-Seminars and colloquia.
-Courses on academic skills and tools.
-Possibly an internship in a research group or company.
-Studies in an application domain.
-Master’s thesis (30 credits).

Career Prospects

Industry and science are flooded with data and are struggling to make sense of it. There is urgent demand for individuals trained to analyse data, including massive and heterogeneous data. For this reason, the opportunities are expected to grow dramatically. The interdisciplinary Data Science MSc programme will train you to work in data-intensive areas of industry and science, with the skills and knowledge needed to construct solutions to complex data analysis problems.

If you are focusing on the core areas of data science, you will typically find employment as a researcher or consultant, sometimes after taking a PhD in Computer Science or Statistics to deepen your knowledge of the field and research methods. If your focus is on the use of data science for specific applications, you will typically find work in industry or in other fields of science such as physics, digital humanities, biology or medicine.

Internationalization

The Data Science MSc is an international programme, with students from around the world and an international research environment. All of the departments taking part in the programme are internationally recognised for their research and a significant fraction of the teaching and research staff come from abroad.

The departments participate in international student exchange programmes and offer you the chance to include international experience as part of your degree. Data Science itself is an international field, so once you graduate you can apply for jobs in any country.

In the programme, all courses are in English. Although the Helsinki area is quite cosmopolitan and English is widely spoken, you can also take courses to learn Finnish at the University of Helsinki Language Centre. The Language Centre also offers an extensive programme of foreign language courses for those interested in learning other languages.

Research Focus

The MSc programme in Data Science is offered jointly by three departments and two research institutes. Their research covers a wide spectrum of the many aspects of data science. At a very general level, the focal areas are:
-Machine learning and data mining
-Distributed computation and computational infrastructures
-Statistical modelling and analysis
-Studies in the programme are tightly connected to research carried out in the participating departments and institutes.

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

Programme description

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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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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Are you looking for a Masters-level qualification that will open doors to jobs and promotions in the field of information science? This course combines core modules in information science with options that range across the sub-disciplines of data analytics, library management and records management. Read more
Are you looking for a Masters-level qualification that will open doors to jobs and promotions in the field of information science? This course combines core modules in information science with options that range across the sub-disciplines of data analytics, library management and records management.

The core modules cover topics such as human information behaviour, interactive information retrieval, user-centred design and persuasive technologies. You will solve problems from a number of perspectives: as a developer of rigorous technical solutions, as a manager who wants to achieve a profitable and sustainable advantage, and as an ethical and socially aware information professional who understands the role of information within the wider social context.

For your optional modules, you have the flexibility to pick and choose from different sub-disciplines of information science. If you are sure that you want to focus on just one sub-discipline, we offer a suite of more focused courses: MSc Information Science (Data Analytics), MSc Information Science (Library Management), and MSc Information Science (Records Management).

This course can also be completed through distance learning - for more information, please view this web-page: https://www.northumbria.ac.uk/study-at-northumbria/courses/information-science-msc-dl-dtdinz6/

Accreditation

All of Northumbria’s information science postgraduate courses are accredited by the Chartered Institute of Library and Information Professionals, with our Records Management pathway also accredited by the Archives and Records Association. These accreditations make our courses stand out and enhance their credibility and currency among employers, and are also crucial for progressing to Chartership status once qualified.

CILIP assessors particularly commended the way in which the programme had been developed to take account of the changing requirements of employers and feedback from students. The resulting course was particularly strong in the digital elements of information work, and in developing students’ transferable skills.

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.

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.

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.

Module Overview
KC7013 - Database Modelling (Optional, 20 Credits)
KC7020 - Information Organisation and Access (Core, 20 Credits)
KC7021 - Statistics and Business Intelligence (Optional, 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)
KC7025 - The library professional: management, leadership and outreach (Optional, 20 Credits)
KC7026 - Masters Dissertation (Core, 60 Credits)
KC7027 - Information and digital literacy (Optional, 20 Credits)
KC7038 - Recordkeeping Practice: Processes, systems and tools (Optional, 20 Credits)
KC7039 - Recordkeeping Principles: Theory and Concepts (Optional, 20 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.

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 following features of the programme were particularly commended by CILIP assessors:
-The way in which the programme had been developed to take account of the changing requirements of employers and feedback from students. The resulting course was particularly strong in the digital elements of information work, and in developing students’ transferable skills;
-The strong relationships with local employers and the active contribution which the department makes to the regional professional network;
-The areas of good practice reflected in the programme, such as the high level of support provided to distance learners, including dedicated library provision, and the use of innovative approaches to assessment.

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

Information science has an exciting future as massive increases in processing power transform the accessibility and utility of data. With an MSc Information Science, you can play a full and rewarding role in that future.

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 public, private and third sector, who need information scientists or you could consider freelance roles as a consultant. Your Masters qualification can also form the basis for further postgraduate studies at a higher level.

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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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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

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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.

Read less
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.

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 Biology 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 PGCE Secondary Science with Biology course therefore begins with a general mix of biology, chemistry and biology to enable all you to teach all three sciences at KS3.

However, you will then be able to focus on teaching biology 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 biology topics at KS4, within a broad and balanced science curriculum.

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This innovative course in the growing area of behavioural science and behavioural economics combines multidisciplinary expertise from the Departments of Economics, Psychology and Warwick Business School. Read more
This innovative course in the growing area of behavioural science and behavioural economics combines multidisciplinary expertise from the Departments of Economics, Psychology and Warwick Business School. Warwick is one of the strongest places in the world to study behavioural science (flagged for excellence in the 2014 Research Excellence Framework), and one of the few to offer a truly interdisciplinary research and teaching team.

During the course you’ll focus on behavioural, experimental and neuroeconomics, decision-making and the principles of cognition. Methods explored include mathematical modelling of choice, agent-based simulation, econometrics and process-tracing methods (e.g. eye-tracking and brain-imaging).

You’ll also undertake a project, giving you the opportunity to collaborate with a team of researchers on live research projects. Past projects have included analysis of big data sets (e.g. Facebook profiles to large UK/US panel studies), large online experiments with thousands of participants, field experiments on consumer and economic behaviour, and laboratory studies of groups using economic games.

Our graduates continue to PhD research, or to work in the public and private sectors, applying behavioural science to public policy and business.

Science Track

The Science Track is intended for those with an undergraduate degree in science, or another quantitative subject. Students take a module in Behavioural Microeconomics in Term 1, which introduces classic microeconomics and the relationship to the new behavioural approach.

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