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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 demand for skills in this area mean that graduates of this programme will be highly employable.

About this degree

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.

Students undertake modules to the value of 180 credits compromising eight taught modules worth 15 credits each and a substantive piece of student-led research that will carry 60 credits. Students must undertake either four or five core modules. The combination and number of modules studied will depend on your chosen stream and whether your background is in statistics or economics.

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 I
  • 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 select one optional module from any department in UCL. 

Dissertation/report

All students undertake an indepedent 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 programme and access to placements is voluntary and based on open competition.

Careers

Graduates of this MSc may go on to work within the pharmaceutical industry, local or national government departments, international organisations, think tanks, consultancies or in academia among other opportunities. Programme organisers liaise with a range of potential employers to create internship opportunities where students can experience the working environment in their field and develop important professional networks.

Employability

As the global population grows and ages, so too does the challenge of providing equitable access to cost-effective healthcare. This MSc has been developed to fill a gap in training and skills in higher education, to embrace the multidisciplinary nature of health economics and decision science and provide students with a solid theoretical foundation - while allowing them to choose specific pathways within which they can focus on either more advanced modelling or advanced applied economics.

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 on 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.

Research Excellence Framework (REF)

The Research Excellence Framework, or REF, is the system for assessing the quality of research in UK higher education institutions. The 2014 REF was carried out by the UK's higher education funding bodies, and the results used to allocate research funding from 2015/16.

The following REF score was awarded to the department: Institute for Global Health

81% rated 4* (‘world-leading’) or 3* (‘internationally excellent’)

Learn more about the scope of UCL's research, and browse case studies, on our Research Impact website.



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Algorithm Economy, Data-Driven Decision Making, Industry 4.0, Deep Learning, Artificial Intelligence, Optimization, Data Science, Decision Science - these are just some of the phrases that we read in the headlines with increasing frequency. Read more

Algorithm Economy, Data-Driven Decision Making, Industry 4.0, Deep Learning, Artificial Intelligence, Optimization, Data Science, Decision Science - these are just some of the phrases that we read in the headlines with increasing frequency. The world is on the brink of a new industrial revolution, one in which data, algorithms and analytical thinking will be the key ingredients of value creation; ingredients that global leaders now recognize as their most valuable assets. Enterprises tackling the challenges of tomorrow need to develop new data-centric strategies and leadership, and crucially, must ensure that they attract the most qualified personnel at all levels in the organization; personnel who have the skills to put data-driven approaches into practice and create value for the business from data. Innovation springs from the brightest minds - become a leader of tomorrow by joining our new Master in Management and Engineering in Data and Decision Science. The MME-DDS is positioned at the intersection of Data Science and Operations Research. Our courses bring together expertise from a wide range of fields; machine learning, artificial intelligence, mathematical optimization, heuristic algorithm design and simulation. Electives and domain specializations will give you a competitive advantage in your chosen field. Designed for professionals with a STEM (science, technology, engineering, mathematics) background, the MME-DDS begins with the fundamentals and takes you right up to the cutting-edge of machine learning, artificial intelligence and exact and heuristic optimization. Projects in data science and optimization will give you hands-on experience tackling real-world problems. Electives and specialization will allow you to develop comprehensive domain knowledge and subject matter expertise in engineering and a range of application areas and industry sectors.

Why you should choose the MME-DDS

Enrolling in the MME-DDS will help you to prepare for a career in the data-driven economy. Benefit from the key strengths of the program:

Excellent reputation: RWTH Aachen University enjoys an excellent reputation across the world for cutting-edge research in engineering and technology and is synonymous with German engineering.

Interdisciplinary thinking: Our courses are designed to combine deep knowledge in Data and Decision Science with domain-specific knowledge from engineering and a wide range of application areas and industry sectors. This interdisciplinary profile is highly sought after in global enterprises and SMEs alike.

Networking focus: We place a strong focus on communication amongst participants and lecturers, thus building the foundations of a successful career, enhanced by an international network. This is enhanced by industry internships and the opportunity to study abroad, which are offered to our students as part of the program.

A varied approach to teaching: The program uses a wide range of learning styles and teaching methods. Lectures, case studies, applied projects, group work, topical debates and lab sessions provide a varied and lively learning experience.

Excellent career perspectives: Develop into one of tomorrow’s “unicorns” and become a leader with the skills required for the algorithm economy. At RWTH Aachen University you will gain in-depth theoretical knowledge and develop the tools and the skills to put cutting-edge knowledge into practice.



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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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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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The MSc in Data Science & Analytics, jointly offered by the Department of Computer Science and the Department of Statistics, provides an education in the key principles of this rapidly expanding area. Read more
The MSc in Data Science & Analytics, jointly offered by the Department of Computer Science and the Department of Statistics, provides an education in the key principles of this rapidly expanding area. The combination of sophisticated computing and statistics modules will develop skills in database management, programming, summarisation, modelling and interpretation of data. The programme provides graduates with an opportunity, through development of a research project, to investigate the more applied elements of the disciplines.

Visit the website: http://www.ucc.ie/en/ckr49/

Course Details

The MSc in Data Science and Analytics is a significant collaboration between the Departments of Computer Science and Statistics; designed to provide graduates with the skills and knowledge required to help companies and public bodies deal with ever increasing and complex data. The programme emphasises the application of Computer Science and Statistics methodologies helping transform data into useful information that can support decision making.

Format

A typical 5 credit module:
• 2 lecture hours per week
• 1–2 hours of practicals per week
• Outside these regular hours students are required to study independently by reading and by working in the laboratories and on exercises.

Structure

Students must attain 90 credits through a combination of:

- Core Modules (30 credits)
- Elective Modules (30 credits)
- Dissertation (30 credits)

Part 1 (60 credits)

- Core Modules (30 credits) -

CS6405 Data Mining (5 credits) - Dr. Marc Van Dongen
ST6030 Foundations of Statistical Data Analytics (10 credits)
ST6033 Generalised Linear Modelling Techniques (5 credits)

- Database Modules -

Students who have adequate database experience take:

CS6408 Database Technology (5 credits) - Mr. Humphrey Sorensen
CS6409 Information Storage and Retrieval (5 credits) - Mr. Humphrey Sorensen

- Students who have not studied databases take:

CS6503 Introduction to Relational Databases (5 credits)
CS6505 Database Design and Administration (5 credits)

Elective Modules (30 credits)

Students must take at least 10 credits of CS (Computer Science) modules and at least 10 credits of ST (Statistics) modules from those listed below:

CS6322 Optimisation (5 credits) - Dr. Steve Prestwich
CS6323 Analysis of Networks and Complex Systems (5 credits) - Prof. Gregory Provan
CS6509 Internet Computing for Data Science (5 credits)
ST6032 Stochastic Modelling Techniques (5 credits)
ST6034 Multivariate Methods for Data Analysis (10 credits)
ST6035 Operations Research (5 credits)
ST6036 Stochastic Decision Science (5 credits)

- Programming Modules -

Students who have adequate programming experience take:

CS6406 Large-Scale Application Development and Integration l (5 credits) - Professor Gregory Provan
CS4607 Large-Scale Application Development and Integration ll (5 credits) - Professor Gregory Provan

- Students who have not studied programming take:

CS6506 Programming in Python (5 credits)
CS6507 Programme in Python with Data Science and Applications (5 credits) - Dr. Kieran Herley

Part 2 (30 credits)

Students select one of the following modules:

CS6500 Dissertation in Data Analytics (30 credits)
ST6090 Dissertation in Data Analytics (30 credits)

Assessment

Full details and regulations governing Examinations for each programme will be contained in the Marks and Standards 2015 Book and for each module in the Book of Modules 2015/2016 - http://www.ucc.ie/modules/

Postgraduate Diploma in Data Science and Analytics

Students who pass each of the taught modules may opt to exit the programme and be conferred with a Postgraduate Diploma in Data Science and Analytics.

Careers

This programme aims to prepare students to manage, analyse and interpret large heterogeneous data sources. Graduates will design, compare and select appropriate data analytic techniques, using software tools for data storage/management and analysis, machine learning, as well as probabilistic and statistical methods. Such abilities are at the core of companies that constantly face the need to deal with large data sets.

Companies currently seeking graduates with data analytics skills include: firms specialising in analytics, financial services and consulting, or governmental agencies.

Companies actively recruiting Computer Science graduates in 2014-15 include:

Accenture, Aer Lingus, Amazon, Apple, Bank of America Merrill Lynch, Bank of Ireland, BT, Cisco, CiTi-Technology, Cloudreach, Dell, Digital Turbine Asia Pacific, EMC, Enterprise Ireland, Ericsson, First Derivatives, Guidewire, IBM, Intel, Open Text, Paddy Power, Pilz, PWC, SAP Galway Transverse Technologies, Trend Micro, Uniwink, Version 1 (Software).

How to apply: http://www.ucc.ie/en/study/postgrad/how/

Funding and Scholarships

Information regarding funding and available scholarships can be found here: https://www.ucc.ie/en/cblgradschool/current/fundingandfinance/fundingscholarships/

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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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Businesses are increasingly collecting large amounts of information about their customers and activities. This ‘big data’ is big news with the media, businesses and government as they consider how to use this mass of information in a meaningful way. Read more

Businesses are increasingly collecting large amounts of information about their customers and activities. This ‘big data’ is big news with the media, businesses and government as they consider how to use this mass of information in a meaningful way.

Analysts use their expertise to make sense of this information and interpret it, enabling evidence-based business decisions. As a result, they’re in high demand with employers in every sector.

This programme gives you an insight into business analytics and explores how organisations can exploit the big data revolution. You’ll develop decision-oriented, quantitative analytical skills in a management context, and learn to sift intelligence from the growing volume and variety of data collected on many aspects of life.

Combining theoretical concepts with practical application, you’ll develop a unique mix of quantitative and behavioural skills relevant to data analyses, effective decision-making and management.

Academic excellence

You’ll be taught by internationally recognised academics and business practitioners from our Centre for Decision Research, who are actively engaged in the latest research, advising businesses, governments and international bodies. They share this expertise and knowledge with you in the classroom.

With the Leeds Institute for Data Analytics on campus, the University of Leeds has a growing wealth of expertise and resources in data sciences.

Course content

This programme will build your knowledge and understanding of how business analytics can provide evidence to support management decision-making. You’ll learn how to use different evidence-based approaches to make effective decisions, developing your skills in quantitative analysis.

You’ll consider advanced techniques such as forecasting and have the opportunity to apply your decision-making skills to real-life business and management scenarios. With the support of leading researchers in this constantly shifting landscape, you’ll also gain an understanding of research methods.

A range of optional modules allows you to gain specialist knowledge that suits your interests or career plans.

The course culminates in a 12,000 word dissertation or project, enabling you to apply your learning to a topic of your choice. This is an opportunity to explore the very latest insights with the support of an academic who shares your passion and interest.

Course structure

Compulsory modules

You’ll take eight compulsory modules including your dissertation.

  • Effective Decision Making 15 credits
  • Dissertation 45 credits
  • Advanced Management Decision Making 15 credits
  • Business Analytics and Decision Science 15 credits
  • Forecasting and Advanced Business Analytics 15 credits
  • Evidence Based Consultancy 15 credits
  • Research Methods 15 credits
  • Quantitative Analysis 15 credits

Optional modules

You'll also choose another three optional modules.

  • Behavioural Finance 15 credits
  • Risk Perception and Communication 15 credits
  • Managing Global Logistics and Supply Chains 15 credits
  • Operations and Supply Chain Management 15 credits
  • Managing and Designing Value Chain Networks 15 credits
  • Information Tools for Organisations 15 credits
  • Challenges in Information Management 15 credits
  • Designing Information Systems 15 credits

For more information on typical modules, read Business Analytics and Decision Sciences MSc in the course catalogue

Learning and teaching

We use a variety of teaching and learning methods to help you make the most of your studies. These will include lectures, seminars, workshops, online learning, computer classes and tutorials.

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

Graduates of the MSc Business Analytics and Decision Sciences can expect to have the quantitative skills to analyse complex business information, and use the resulting intelligence to inform business decisions.

You will be ideally placed to pursue a career in analytics and decision making, general and specialist management roles in a range of industries, or as business or market analysts.

Employers in both private and public sectors are actively seeking graduates with these skills, and trends show that the career opportunities are fast increasing. The role of the data scientist was described as the 'Sexiest Job of the 21st Century' by the Harvard Business Review.

Demand for experts in business analytics is growing rapidly and the University of Leeds is at the forefront of developments in this area.

Read more about Business Analytics at Leeds.

Links with industry

Students have the opportunity to develop leadership skills as part of our Leaders in Residence initiative which gives management students the opportunity to engage with senior figures from the world of business. This is a rare opportunity where successful and established business people will help you connect the theory of your course to real world practice, and offer their advice for career success.

You will be able to connect with leaders from a range of firms including major manufacturers and retailers, charity chief executives, entrepreneurs and directors of companies large and small, through structured meetings and events. This typically includes workshops, social events, guest lectures and professional skills development.

Careers support

We help you to achieve your career ambitions by providing professional development support as part of the course. You benefit from our professional development tutor, who will work with you to develop the important professional skills that employers value.

Read more about our careers and professional development support.

The Careers Centre also provides a range of help and advice to help you plan your career and make well-informed decisions along the way, even after you graduate.



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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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The master´s programme Global Politics aims towards you who are interested in global political issues. You will learn how an increasing complex world, where the global and the local meet, presents us with new challenges and opportunities. Read more

The master´s programme Global Politics aims towards you who are interested in global political issues. You will learn how an increasing complex world, where the global and the local meet, presents us with new challenges and opportunities. The programme provides you with a solid practical base concerning concepts like justice, peace, security, power, culture and democracy. You will learn how to analyse conflicts, international relations and human rights claims and violations. 

This is a multi-disciplinary programme with a core of political science which address aspects of international relations, human rights and peace and conflict studies. Focus lays on the transformation of society, especially concerning the relationship between the state and other actors such as international organisations and companies. 

Changes in political control, from reduced central control towards a greater degree of network control will also be addressed. You will analyze the growing importance of international norms, such as human rights. The emergence of other conflict patterns than those related to socio-economic resources (such as culture, ideology and religion) is important parts of the courses. 

Political science at Malmö University

This two-year Master's programme draws from the one-year master’s in political science, with additional opportunities for an internship, exchange studies or elective courses. This provides you with the opportunity to deepen knowledge and gain practical experience, as well as the chance to develop relationships and network with people and organisations working with political and global issues.

The programme is thoroughly interdisciplinary and draws on the different strengths from the Department of Global Political Studies, including International Relations, Peace and Conflict Studies, Human Rights, Public Policy, but also ethnography and philosophy. To gain a deeper understanding of the changes in political science, we consider four key development areas:

Global politics: an increasing number of international and intergovernmental organisations impact world politics.

Government and governance: whilst new information technologies and surveillance legislation mean that the administrative powers of the state have never been stronger, the concept of ‘government’ has become increasingly surpassed by ‘governance’ at the transnational level. Few decisions affecting our lives are taken exclusively within the national context.

Existing modes of power are challenged: there has been a significant change in how organisations like NGOs, as well as everyday individuals, challenge existing governance and modes of power. For example, social media has radically changed the transnational political landscape to both enable new forms of protest and contestation, as well as facilitate new political identities.

Global concerns: issues like climate change and terrorism show that increasingly the kind of problems requiring policy solutions far exceed the confines of any nation-state. That is to say, policy problems are increasingly transnational and therefore require transnational solutions.

What career will I be prepared for?

The programme should be of interest to individuals committed to a career in which knowledge of our changing world is an evident benefit, with relevance to employers including international agencies, non-governmental organisations, transnational businesses, and local/national administrative agencies.

Courses

For programme with start Autumn 2018: 

Autumn 2018 - Semester 1

Spring 2019 - Semester 2

Spring 2020 - Semester 4


Learning outcomes

Knowledge and understanding 

  • demonstrate knowledge and understanding in the main field of study, including both broad knowledge of the field and a considerable degree of specialised knowledge in certain areas of the field as well as insight into current research and development work, and
  • demonstrate specialised methodological knowledge in the main field of study.

Competence and skills 

  • demonstrate the ability to critically and systematically integrate knowledge and analyse, assess and deal with complex phenomena, issues and situations even with limited information
  • demonstrate the ability to identify and formulate issues critically, autonomously and creatively as well as to plan and, using appropriate methods, undertake advanced tasks within predetermined time frames and so contribute to the formation of knowledge as well as the ability to evaluate this work
  • demonstrate the ability in speech and writing to clearly report and discuss his or her conclusions and the knowledge and arguments on which they are based in dialogue with different audiences, and
  • demonstrate the skills required for participation in research and development work or autonomous employment in some other qualified capacity.

Judgement and approach 

  • demonstrate the ability to make assessments in the main field of study informed by relevant disciplinary, social and ethical issues and also to demonstrate awareness of ethical aspects of research and development work
  • demonstrate insight into the possibilities and limitations of research, its role in society and the responsibility of the individual for how it is used, and
  • demonstrate the ability to identify the personal need for further knowledge and take responsibility for her or his ongoing learning.


Degree

Master's Degree (120 credits).

Degree of Master of Arts (120 credits) with a major in Political Science



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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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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. 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

Radboud University Master's Open Day 10 March 2018



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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.

About this degree

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 in 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 Machine Learning
  • Statistical Design of Investigations
  • Statistical Computing

Optional modules

At 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 of 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.

Further information on modules and degree structure is available on the department website: Data Science MSc

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:

  • Management Associate, HSBC
  • Statistical Analyst, Nielsen
  • PhD in Statistics, UCL
  • Mortgage Specialist, Citibank
  • Research Assistant Statistician, Cambridge Institute of Public Health

Employability

Data science professionals are likely to be increasingly sought after as the integration of statistical and computational analytical tools becomes essential in all kinds of organisations and enterprises. A thorough 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 should be accompanied by statistical expertise at graduate level. Data scientists need a broad background knowledge so that they will be able to adapt 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.

Research Excellence Framework (REF)

The Research Excellence Framework, or REF, is the system for assessing the quality of research in UK higher education institutions. The 2014 REF was carried out by the UK's higher education funding bodies, and the results used to allocate research funding from 2015/16.

The following REF score was awarded to the department: Statistical Science

82% rated 4* (‘world-leading’) or 3* (‘internationally excellent’)

Learn more about the scope of UCL's research, and browse case studies, on our Research Impact website.



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