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Masters Degrees (Data Scientist)

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There has been a recent upsurge in commercial interest in the new role of "data scientist". A data scientist is a person who excels at manipulating and analysing data, particularly large data sets that don't fit easily into tabular structures (so-called "Big Data"). Read more
There has been a recent upsurge in commercial interest in the new role of "data scientist". A data scientist is a person who excels at manipulating and analysing data, particularly large data sets that don't fit easily into tabular structures (so-called "Big Data").

Why study Data Science at Dundee?

The School of Computing has been working on 'big data' and data analysis for at least five years; not only working with data but also developing new algorithms and techniques for data scientists. The School already runs the most successful Business Intelligence Masters course in the UK.

This course will be led by Professor Mark Whitehorn and Andy Cobley. Mark is an emeritus professor at the University of Dundee and also runs a successful consultancy company that specialises in BI, Data Sciences and analytics. Andy is the course organiser for both the existing BI course and the new Data Science course.

This course will enhance your employability by providing you with knowledge, skills and understanding of data science research and implementation. You will also acquire skills in the professional procedures necessary to ensure that data science research and implementation is both valid and actionable and engage with contemporary debate about the role, ethics and utility of data science in commercial and other settings.

What is the difference between Data Science and Business Intelligence?

There is clearly a huge overlap with Business Intelligence. A BI specialist will need to understand data and data analytics. However there is a bias towards understanding how data is stored in the current operational systems within an enterprise the design and the implementation of an analytical system such as a data warehouse. A data scientist will be less concerned with the construction of a data warehouse and more interested in the message the specific sets of data can deliver.

However, without some understanding of data warehouses the data scientist will find it difficult to interrogate the data for its secrets. For this reason there is overlap between the two courses.

If you already have a strong grounding in Business Intelligence and would like to upgrade your knowledge to include topics from the Data Science MSc, we offer the relevant Data Science modules either on a stand alone basis or as a PGCert.

What's so good about Data Science at Dundee?

Our facilities will give you 24-hour access to our award winning and purpose-built Queen Mother Building. It has an unusual mixture of lab space and breakout areas, with a range of conventional and special equipment for you to use. It's also easy to work on your own laptop as there is wireless access throughout the building. Our close ties to industry allows us access to facilities such as Windows Azure and Teradata, and university and industry standard software such as Tableau for you to evaluate and use.

A booming Postgraduate culture where the School of Computing maintains a friendly, intimate and supportive atmosphere, and we take pride in the fact that we know all of our students - you're far more than just a matriculation number to us. We have a thriving postgraduate department with regular seminars and guest speakers.

Duncan Ross (Director of Data Sciences at Teradata) has said that: "The first and most important trait is curiosity. Insane curiosity. In many walks of life evolution selects against the kind of person who decides to find out what happens 'if I push that button'. Data Science selects for it."

How you will be taught

The programme will be delivered by Prof. Mark Whitehorn with input from Andy Cobley, Yasmeen Ahmad, Chris Hillman and other specialists from within the School of Computing in an innovative blend of live co-presented master-classes, video seminars and recorded materials. A series of guest speakers from industry will provide case studies across both semesters.

The programme will be provided predominantly on-campus, with two intensive study weeks in each of the semesters. Other classes may be taken off-campus using the university’s VLE, remote desktop, Adobe Connect and video conferencing systems along with telephone conferencing.

What you will study

Semester 1
Big Data - 20 Credits
Business Intelligent Systems - 20 Credits
Data Analysis and Visualisation - 20 Credits

Semester 2
Analytical Database Models and Design - 20 Credits
Advanced statistics and data mining - 20 credits
MDX - 20 Credits

Semester 3
Data Science Mini Project - 20 credits (for Certificate)
Data Science Research Project - 60 credits

PGCert:
The PGCert is intended for students who have a strong grounding in Business Intelligence and would like to upgrade their knowledge to include topics from the Data Science MSc. The modules are available stand alone for those who want to take their time studying the material and perhaps build up to a PGCert.

The three modules that make up the PGCert are:
Big Data
Advanced Anlaysis
Mini Project

For more information about the content of the course, please visit the course webpage on the School of Computing website.

How you will be assessed

Assessment will be by examination, practical coursework and research project.

Careers

Various job sites now report an increase in jobs carrying the title of data scientist. Other career opportunities are in intelligence analysis, data management/database maintenance, data processing manager, database development and research, business intelligence consultant and more.

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This intensive programme in data science and software engineering is designed for graduates who are new to computer science and provides an excellent grounding for working as a data scientist or analyst in industry. Read more
This intensive programme in data science and software engineering is designed for graduates who are new to computer science and provides an excellent grounding for working as a data scientist or analyst in industry. You will gain a broad knowledge of computing and acquire programming and data analysis skills, as well as comprehensive, practical problem-solving and analytical skills. You will also critically explore current research and methodologies and have the opportunity to investigate an area of current research in more depth via a project.

If you are new to computer science, this programme provides a solid foundation for a career in IT as a data scientist or analyst. For those already working in IT, the programme is an ideal opportunity to strengthen and update your knowledge and skills in the areas of data science and software engineering, while obtaining a formal Master's qualification.

This programme has been funded by the Higher Education Funding Council for England (HEFCE), as part of an innovative initiative to fund conversion courses in computing and engineering. This course uniquely enables students without any previous computer or data science experience at undergraduate level to study towards a Master's degree in this area of emerging importance. Crucially, the course covers both data science and software engineering, a combination of skills sought after in industry.

Why study this course at Birkbeck?

This programme is ideal if you are new to computer science and want to develop a career in IT as a data scientist or analyst.
Our Department of Computer Science and Information Systems is one of the longest-established in the world - we are celebrating our 60th anniversary in 2017.
We provide a stimulating teaching and research environment, with academic specialists in all fields, including information and knowledge management, web and pervasive technologies, computational intelligence, and information systems development, among others.
Our research dates back to the late 1940s, when one of the first electronic computers was developed at Birkbeck by Dr Andrew Booth. We now house the Computational Intelligence Research Group and the Information Management and Web Technologies Research Group, both of which collaborate with other research groups and with industry, in the UK and abroad, and undertake interdisciplinary research in the life, natural and social sciences, and the humanities.
We are also part of the London Knowledge Lab, a unique collaboration between Birkbeck and the UCL Institute of Education, which brings together computer and social scientists to explore how we learn, the role of technology in this process, and how technology relates to broader social, economic and cultural factors.
In the 2014 Research Excellence Framework (REF), more than 75% of our research outputs in Computer Science were ranked world-leading or internationally excellent.
You will have 24-hour access to several laboratories of networked PCs with a range of language compilers, database and other application software. We are connected, via the SuperJANET network, to the computers of other academic institutions in London, elsewhere in the UK and abroad.

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Drawing on our research excellence in this area, this innovative programme of study in big data and business intelligence is designed to give graduates a competitive advantage in the modern, fast growing business domain. Read more
Drawing on our research excellence in this area, this innovative programme of study in big data and business intelligence is designed to give graduates a competitive advantage in the modern, fast growing business domain. This is one of the first MSc programmes in the UK covering these leading-edge technologies. The programme provides students with the deeper knowledge, advanced skills and understanding that will allow them to contribute to the development and design of big data systems as well as distributed/internet-enabled decision support application software systems, using appropriate technologies, architectures and techniques (e.g. data analytics, business intelligence, NoSQL, data mining, data warehousing, distributed data management and technologies, Hadoop, etc.).

Additionally, the programme enables students to understand and assess the security and legal implications of e-commerce applications and provides students with appropriate knowledge of business and commerce relevant to transacting business on the internet. The courses take a software engineering approach to the construction of applications and focus on modern software engineering methods, tools and techniques that enable an integrated life-cycle software development view.

Through our short course centre opportunity may also be provided to study for the following professional qualifications: Microsoft Technology Associate Exams; Certified Professional Java SE Programmer; Java Certified Associate; Oracle Certified Associate (OCA).

Visit the website http://www2.gre.ac.uk/study/courses/pg/com/cgbdbi

Computing - General

Come and study in the award-winning Department of Computing & Information Systems on the magnificent Greenwich Campus. Welcoming home and international students from all backgrounds, CIS provides an exciting, diverse and friendly environment in which to study.

The latest university league table published in the Sunday Times, has rated the computer science department as seventh in the UK for teaching excellence.

What you'll study

Full time
- Year 1:
Students are required to study the following compulsory courses.

PG Project (CIS) (60 credits)
Data Warehousing (15 credits)
Database Architectures and Administration (15 credits)
Database Tools (15 credits)
Business Intelligence and Data Mining (15 credits)
Enterprise Systems Integration (15 credits)
Big Data (15 credits)
Essential Professional and Academic Skills for Masters Students
English Language Support Course (for Postgraduate Students in the School of Computing and Mathematical Sciences)

Students are required to choose 15 credits from this list of options.

Requirements Analysis & Methods (15 credits)
Software Tools and Techniques (15 credits)
User Centred Web Engineering (15 credits)

Students are required to choose 15 credits from this list of options.

System Modelling (15 credits)
Systems Development Management and Governance (15 credits)
Programming Enterprise Components (15 credits)
Multi-structured Data and NoSQL Technology (15 credits)

Part time
- Year 1:
Students are required to study the following compulsory courses.

Database Architectures and Administration (15 credits)
Business Intelligence and Data Mining (15 credits)
Enterprise Systems Integration (15 credits)
Big Data (15 credits)
Essential Professional and Academic Skills for Masters Students
English Language Support Course (for Postgraduate Students in the School of Computing and Mathematical Sciences)

- Year 2:
Students are required to study the following compulsory courses.

PG Project (CIS) (60 credits)
Data Warehousing (15 credits)
Database Tools (15 credits)

Students are required to choose 15 credits from this list of options.

Requirements Analysis & Methods (15 credits)
Software Tools and Techniques (15 credits)
User Centred Web Engineering (15 credits)

Students are required to choose 15 credits from this list of options.

System Modelling (15 credits)
Systems Development Management and Governance (15 credits)
Programming Enterprise Components (15 credits)
Multi-structured Data and NoSQL Technology (15 credits)

Fees and finance

Your time at university should be enjoyable and rewarding, and it is important that it is not spoilt by unnecessary financial worries. We recommend that you spend time planning your finances, both before coming to university and while you are here. We can offer advice on living costs and budgeting, as well as on awards, allowances and loans.

Assessment

Students are assessed through examinations, coursework and a project.

Professional recognition

This programme is accredited by the British Computer Society (BCS). On successful graduation from this degree, the student will have fulfilled the academic requirement for registration as a Chartered IT Professional (CITP) and partially fulfilled the education requirement for registration as a Chartered Engineer (CEng) or Chartered Scientist (CSci). For a full Chartered status there are additional requirements, including work experience. The programme also has accreditation from the European Quality Assurance Network for Informatics Education (EQANIE).

Career options

Graduates from this programme can pursue careers as data scientists, database designers and administrators, consultants, senior team members, programmers, analysts.

Find out how to apply here - http://www2.gre.ac.uk/study/apply

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This innovative new course developed in collaboration with CDA (Common Data Access Ltd) provides flexible entry to an education in the field of petroleum data management. Read more
This innovative new course developed in collaboration with CDA (Common Data Access Ltd) provides flexible entry to an education in the field of petroleum data management. The course has been designed as an access route for those with relevant work experience in the energy sector who do not currently have the necessary qualifications in this area. The course facilitates access to any of our Masters Degree courses available from the Department of Information Management and enhances professional career development.

You will be able to draw upon your current and previous work experience within the modules. This approach will allow you to analyse both the organisation and its approach to petroleum data management, and to utilise the course content to improve strategic organisational effectiveness. In addition, it encourages you to consider any practical problems that may arise in the execution of any activities, and to reflect critically on the value of your own organisational input.

Visit the website: http://www.rgu.ac.uk/information-communication-and-media/study-options/distance-and-flexible-learning/petroleum-data-management

Course detail

The Petroleum Data Management Graduate Certificate aims to promote the understanding of subsurface exploration and production data and evaluate its importance to upstream oil and gas businesses. The course focuses on managing subsurface exploration and production data throughout its life cycle from capture to realisation until it becomes obsolete.

You will study four modules over the academic year, each assessed through coursework assignments:

• Managing Subsurface Exploration and Production Data
• The Data Management Life Cycle
• Providing Data Management Services
• Data Quality and Governance

Format

The course will be offered online. Our supported distance learning mode of delivery allows you to study online from any location and is designed to fit in around any existing work commitments.

Our virtual learning environment, CampusMoodle offers students flexibility of where and when they can study, offering full and open access to tutors and other class members. Students have the benefit of being part of a group of learners with the invaluable opportunity to participate in active, group-related learning within a supportive online community setting. The online campus provides students with lectures and course materials and it also includes:

• Virtual tutorials
• Live chat
• Discussion forums - student and tutor led
• Up-to-date web technology for delivery methods
• User friendly material
• Access to our online library

As online learners, students are part of a 'virtual cohort' and the communication and interaction amongst members of the cohort is a significant aspect of the learning process.

Careers

There is a growing recognition of the need for more effective data management in the energy sector. In addition to gaining a recognised industry-focussed qualification, this course will also provide access to our CILIP accredited courses allowing you to develop your knowledge and career further, and to undertake a diverse range of roles in the energy sector including:
• Data analyst
• Information scientist
• Records manager

Benefits

The award of Graduate Certificate Petroleum Data Management given on completion of this course has been promoted by CDA as a means of promoting the professionalisation of data managers within the energy sector.

How to apply

To find out how to apply, use the following link: http://www.rgu.ac.uk/applyonline

Funding

For information on funding, including loans, scholarships and Disabled Students Allowance (DSA) please click the following link: http://www.rgu.ac.uk/future-students/finance-and-scholarships/financial-support/uk-students/postgraduate-students/postgraduate-students/

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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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Big data is the description used to encompass the huge amounts of data that is common to many businesses. It has been described as the next frontier for innovation, competition and productivity in business. Read more

Big data is the description used to encompass the huge amounts of data that is common to many businesses. It has been described as the next frontier for innovation, competition and productivity in business. It is essential for companies to embrace so that they can understand their customers better, develop new products and cut operational costs.

This course has been developed to create graduates who can become data scientists capable of working with the massive amounts of data now common to many businesses. It is aimed at people who want to move into this rapidly expanding and exciting area.

The modules on this course help you develop the core skills and expertise needed by the data scientist. The course can be split into three main areas, statistics, computing and management.

In the statistics section you study modules on data mining and data modelling. These modules cover the three main data areas, which are ensuring that data is reliable and of a high quality, searching the data to discover new information and presenting interpretations of that data to the end user.

The computing section covers areas related to data integration, massive datasets stored in the cloud, how data is stored and utilised within the distributed systems of an enterprise and how organisations can utilise data to change and improve business processes.

The management modules are focused on developing your core skills around professionalism and research. All of which are valuable skills during your university studies and in your career.

Our partnerships with business inform the course design, ensuring the content is relevant, up to date and meets the needs of industry. These partnerships also enable the inclusion of some leading edge software such as SAS, SAP Hana, and Hadroop within the course. You may be able to study abroad as part of the Erasmus programme.

Key areas of study

Key areas of study include • data quality and analysis • technologies to store and mine data • professionalism and research

Professional recognition

This course includes the SAP Business Intelligence with SAP BW 7.3 and SAP BI 4.0 e-academy (UB130e). You also have the opportunity to sit the SAP certification exam and the SAS 9 base certification exam.

Sheffield Hallam is a member of the SAS Student Academy, the SAP Student Academy and founding member of the SAP University Alliance.

Course structure

Full time – September start – typically 12 or 18 months

Part time – September start – typically 36 months

Core modules

  • research skills and principles
  • industrial expertise
  • data integration
  • statistical modelling
  • data mining
  • handling data in the cloud
  • big data and distributed systems
  • social and economic aspects of the cloud
  • advanced statistical modelling
  • dissertation

Options

Choose one from :

  • organisational dynamics
  • social and economic aspects of the cloud

Assessment

  • essays
  • assignments
  • computer-based tests
  • practical projects
  • presentations
  • vivas

Employability

Many jobs for data scientists, data analysts and data mining analysts are available with salaries ranging from £35,000 to £80,000.

Jobs typically list the skills to be in areas such as statistical analysis and machine learning techniques, database and programming technologies, and expertise in statistical theory, which are all areas you cover on this course.

You also gain skills and knowledge in HaDoop, MapReduce, Java, SAS, MSQL which are some of the common technologies used in data scientist roles.



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Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Health Data Science at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017). Read more

Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Health Data Science at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017).

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

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

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

Key Features of the Health Data Science Programme

- A one year full-time taught master's programme designed to develop the essential skills and knowledge required of the Health Data Scientist.

- The Health Data Science course is also available for three years part-time study.

- An integrated programme of studies tailored to the essential skill set required for Data Scientists operating within healthcare organisations covering key topics in computation, data modeling, visualisation, machine learning and key methodologies in the analysis of linked health data.

- Hands on experiential learning from the professionals behind the Secure Anonymised Information Linkage (SAIL) Databank, a UK-exemplar project for the large scale mining of healthcare data within a secure environment.

- Strong collaboration links with colleagues from the Centre for Health Services Research of the University of Western Australia, a group of leading experts in the analysis of linked health data.

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

Who should study MSc Health Data Science?

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

Course Structure

Students must complete 6 modules of 20 credits each and produce a 60 credits dissertation on a Health Data Science project. Each module of the programme requires a short period of attendance that is augmented by preparatory and reflective material supplied via the course website before and after attendance.

Attendance Pattern

Health Data Science students are required to attend the University for 1 week (5 consecutive days) for each module in Part One. Attendance during Part Two is negotiated with the supervisor.

Modules

Modules on the Health Data Science programme typically include:

Scientific Computing and Health Care

Health Data Modelling

Introductory Analysis of Linked Health Data

Machine Learning in Healthcare

Health Data Visualisation

Advanced Analysis of Linked Health Data

Professional Development

The College of Medicine offers the modules on the Health Data Science course as standalone opportunities for prospective students to undertake continued professional development (CPD) in the area of Health Data Science.

You can enroll on the individual modules for the Health Data Science programme as either an Associate Student (who will be required to complete the module(s) assessments) or as a Non-Associate Student (who can attend all teaching sessions but will not be required to complete any assessments).

For information and advice on applying for any of the continuing education opportunities, please contact the College directly at .

Employability

Postgraduate study has many benefits, including enhanced employability, career progression, intellectual reward and the opportunity to change direction with a conversion course.

From the moment you arrive in Swansea, specialist staff in Careers and Employability will help you plan and prepare for your future. They will help you identify and develop skills that will enable you to make the most of your postgraduate degree and enhance your career options. The services they offer will ensure that you have the best possible chance of success in the job market.

The student experience at Swansea University offers a wide range of opportunities for personal and professional development through involvement in many aspects of student life.

Co-curricular opportunities to develop employability skills include national and international work experience and study abroad programmes and volunteering, together with students' union and athletic union societies, social and leisure activities.

For the MSc Health Data Science course, we are in the process of identifying opportunities for our students to complete volunteering placements with a number of our collaborative partners.



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Learning how to turn real-world data sets into tools and useful insights, with the help of software and algorithms. Data plays a role in almost every scientific discipline, business industry or social organisation. Read more
Learning how to turn real-world data sets into tools and useful insights, with the help of software and algorithms.

Data plays a role in almost every scientific discipline, business industry or social organisation. Medical scientists sequence human genomes, astronomers generate terabytes of data per hour with huge telescopes and the police employ seismology-like data models that predict where crimes will occur. And of course, businesses like Google and Amazon are shifting user preference data to fulfil desires we don’t even know we have. There is therefore an urgent need for data scientists in whole array of fields. In the Master’s specialisation in Data Science you’ll learn how to turn data into knowledge with the help of computers and how to translate that knowledge into solutions.

Although this Master’s is an excellent stepping-stone for students with ambitions in research, most of our graduates work as data consultants and data analysts for commercial companies and governmental organisations.

Why study Data Science at Radboud University?

- This specialisation builds on the strong international reputation of the Institute for Computing and Information Sciences (iCIS) in areas such as machine learning, probabilistic modelling, and information retrieval.
- We’re leading in research on legal and privacy aspects of data science and on the impact of data science on society and policy.
- Our approach is pragmatic as well as theoretical. As an academic, we don’t just expect you to understand and make use of the appropriate tools, but also to program and develop your own.
- Because of its relevance to all kinds of different disciplines, we offer our students the chance to take related courses at other departments like at language studies (information retrieval and natural language processing), artificial intelligence (machine learning for cognitive neuroscience), chemistry (pattern recognition and chemometrics) and biophysics (machine learning and optimal control).
- The job opportunities are excellent: some of our students get offered jobs before they’ve even graduated and almost all of our graduates have positions within six months after graduating.
- Exceptional students who choose this specialisation have the opportunity to study for a double degree in Computing Science together with the specialisation in Web and Language Interaction (Artificial Intelligence). This will take three instead of two years.

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

Admission requirements for international students

- A proficiency in English
In order to take part in the programme, you need to have fluency in English, both written and spoken. Non-native speakers of English without a Dutch Bachelor's degree or VWO diploma need one of the following:
- TOEFL score of >550 (paper based) or >213 (computer based) or >80 (internet based)
- IELTS score of >6.0
- Cambridge Certificate of Advanced English (CAE) or Certificate of Proficiency in English (CPE), with a mark of C or higher

Career prospects

A professional data scientist has fine problem-solving, analytical, programming, and communication skills. He or she applies those skills to analyse a problem in the light of the available real-world data:
- To come up with a creative and useful solution.
- To find or program the right tool to turn the data into knowledge.
- To communicate the obtained findings to others.

By combining data, computing power and human intellect, data scientists can make a real difference to help and improve our society.

The job perspective for our graduates is excellent. Industry desperately needs data science specialists at an academic level, and thus our graduates have no difficulty in find an interesting and challenging job. A few of our graduates decide to go for a PhD and stay at the university, but most of our students go for a career in industry. They then typically either find a job at a larger company as consultant or data analysis, or start up their own company in data analytics.

Examples of companies where our graduates end up include SMEs like Orikami, Media11 and FlexOne, and multinationals like ING Bank, Philips, ASML, Capgemini, Booking.com and perhaps even Google.

Our approach to this field

Data nowadays plays a role in almost every scientific discipline as well as industry and is rapidly becoming a key driver of scientific discoveries, business innovation, and solutions for societal challenges such as better healthcare. Medical scientists are sequencing and analysing human genomes to uncover clues to infections, cancer, and other diseases. With huge telescopes, astronomers generate terabytes of data per hour to study the formation of galaxies and the evolution of quasars. Businesses like Google and Amazon are sifting social networking and user preference data to fulfill desires we don't even know we have. Police employing seismology-like data models can predict where crimes will occur and prevent them from happening.

It is then with good reason that data science has been called the sexiest job of the 21st century. Many companies complain about the difficulty to find skilled data scientists and predict this to be even harder in the future. A professional data scientist has fine problem-solving, analytical, programming, and communication skills. He or she applies those skills to analyse a problem in the light of the available real-world data, to come up with a creative and useful solution, to find or program the right tool to turn the data into knowledge, and to communicate the obtained findings to others. By combining data, computing power and human intellect, data scientists can make a real difference to help and improve our society.

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

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Today’s society operates on large amounts of data. Industry, governments and academia are asked to provide insight into these data. Read more
Today’s society operates on large amounts of data. Industry, governments and academia are asked to provide insight into these data.
•But how do we deal with such large amounts of data?
•What techniques do we use to mine the data?
•What are the legal and ethical aspects regarding these data sets?
•And what economic value can be found in big data?

The MSc specialization Data Science: Business and Governance trains students to become Data Scientists that can address these questions. The Harvard Business Review calls the job of Data Scientist "the sexiest job of the 21st century"!

Why Data Science: Business and Governance in Tilburg?
•Tilburg University offers a wide range of complementary expertise, including techniques for data mining, pattern recognition, business analytics, visualization and process analytics; as well as knowledge on law, regulation, ethics and entrepreneurship.
•The MSc specialization consists of courses in methods of analysis, together with economic and management as well as legal, ethical and methodological perspectives on data, all of them taught by experts in these fields.
•The Master’s specialization Data Science: Business and Governance offers (constitutes/ consists of) a well-balanced mixture of theoretical and practical (elective) courses.

These elements combine to make this specialization unique in Europe and possibly even in the world: Four schools (Tilburg School of Economics and Management, Tilburg School of Law, Tilburg School of Social and Behavioral Sciences, and the Tilburg School of Humanities) work together in offering the best possible training for the job of the future, that of Data Scientist.

Career Prospects

Data Science: Business and Governance graduates will not only have knowledge and expertise in the area of data analysis and data mining, but also in economic, management and legal perspectives on big data.

Growing need for Data Scientists

There is a growing need in government organizations, in companies and in academia for employees with the analytical skills needed to analyze large datasets, recognize patterns, and visualize data, and combining these skills with interdisciplinary knowledge of perspectives on Data Science.

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The opportunity to exploit Big Data is recognised world-wide and some countries include it in their economic strategies. The UK Government identified Big Data as one of the 8 great technologies which will have a strong impact on growth and the Scottish Government highlights it as an emerging opportunity for Scotland. Read more
The opportunity to exploit Big Data is recognised world-wide and some countries include it in their economic strategies. The UK Government identified Big Data as one of the 8 great technologies which will have a strong impact on growth and the Scottish Government highlights it as an emerging opportunity for Scotland.

Our MSc in Data Science aims to produce specialist data scientists with training in industry relevant data acquisition, storage, warehousing, analytics and visualisation tools and techniques and a good understanding of the needs of industry. The course will prepare graduates in technical disciplines for a career in the design and implementation use of computer-analytics and visualisation solutions for industry.

Visit the website: http://www.rgu.ac.uk/computing/study-options/postgraduate/masters-in-data-science

Course detail

The course will focus on satisfying industry’s demand for data scientists who have the ability to:

• Apply appropriate data science tools and techniques to industry’s data in order to uncover important, previously unknown information only implicit in the data.
• Relate a company’s key performance indicators to a data science problem area in order to focus a data science task.
• Handle large amounts of real-time, non-persistent, data.
• Contribute to business decision-making by effectively communicating (potentially large volumes of) key data visually.
• Understand, clean up, summarise, interpret and manage data.
• Grasp key knowledge about new problem areas in order to communicate with end-users; understand key business needs and processes and identify added value through data analytics.
• Provide user-centred data analytics at an appropriate level.
• Protect and share data as appropriate.

The course will emphasise Big Data, covering not only traditional data management systems but also systems where data and/or its storage is unstructured.

Format

Throughout the course, content is complemented by practical work, allowing you to support your theoretical knowledge with practical experience in data storage, mining, warehousing, visualisation and analysis as well as transferrable skills. You will be taught through a mixture of lectures, tutorials, labs. You will be invited to attend talks presented by highly-experienced researchers, speakers from industry, and members of the BCS (British Computer Society) on a wide range of industry-related topics. You will also be supported through our online virtual learning environment where you can access a wide variety of resources and other support materials.

The individual project provides an opportunity for applying specialist knowledge together with analytic, problem-solving, managerial and communication skills to a particular area of interest within data science. Working with the full support and guidance of an allocated project supervisor, you will be given the opportunity to propose, plan, specify, develop, evaluate, and present a substantial project.

Placements and accreditation

Students who perform particularly well during their first semester of studies will be invited to apply for a 45-week internship.

Careers

The course prepares you for a career in Data Science. Job openings include: Data Scientist, Data Analyst, Data Visualisation Specialist, Data Manager, Database Designer/Manager, Data Mining Expert and Big Data Scientist.

Aberdeen is home to many multinational oil and gas companies and associated suppliers such as mainstream software houses, IT providers to major oil-related companies, specialist software consultancies, and venture capital start-ups.

The university is involved in a number of commercial collaborations on a local, national and international scale with organisations such as BP, British Geological Survey, Wood Group PSN, Accenture, WIPRO and many Aberdeen-based software development companies.

The course also prepares students for research careers by providing the skills necessary of an effective researcher. Suitable MSc graduates may continue to PhD programmes within the school.

How to apply

To find out how to apply, use the following link: http://www.rgu.ac.uk/applyonline

Funding

For information on funding, including loans, scholarships and Disabled Students Allowance (DSA) please click the following link: http://www.rgu.ac.uk/future-students/finance-and-scholarships/financial-support/uk-students/postgraduate-students/postgraduate-students/

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This programme is now closed but you may want to consider other courses such as the . Advanced Computing MSc. The Data Science MSc is an interdisciplinary study programme that will provide you with advanced technical and practical skills in the collection, collation, curation and analysis of data. Read more

This programme is now closed but you may want to consider other courses such as the Advanced Computing MSc.

The Data Science MSc is an interdisciplinary study programme that will provide you with advanced technical and practical skills in the collection, collation, curation and analysis of data. It also examines the professional, legal and ethical responsibilities of data scientists. This is an ideal study pathway for graduates with a background in quantitative subjects, or who possess relevant work experience in the current methods and techniques of data science.

  • Located in central London, giving access to major libraries and leading scientific societies, including the Chartered Institute for IT (BCS), and the Institution of Engineering and Technology (IET).
  • You will gain an in-depth understanding of the general principles of the computational and statistical approaches and methods used in data science, as well as their underlying assumptions and limitations.
  • Frequent access to speakers of international repute through seminars and external lectures, enabling you to keep abreast of emerging knowledge in advanced computing and related fields.
  • Exposure to interdisciplinary aspects of Data Science through opportunities to interact with multiple departments and faculties across King's diverse campuses
  • The Department of Informatics has a reputation for delivering research-led teaching and project supervision from leading experts in their field.

Description

The Data Science MSc degree will provide you with the practical skills needed to effectively assemble, collate, store, manage and analyse data required for data science projects and the critical judgement to decide the appropriate statistical and computational data modelling and analysis techniques to evaluate data science activities and projects. You will study the computational approaches and techniques used to examine mathematical statistics, as well as developing an appreciation for the professional, ethical and legal responsibilities of the data scientist, along with standard conceptual or scientific models in at least one domain of application of data science. You will complete the course in one year, studying September to September and taking a combination of required and optional modules totalling 180 credits, including 60 credits that will come from a research project and dissertation.

Course purpose

The purpose of this degree programme is to train graduates from quantitative disciplines or with relevant quantitative work experience in current methods and techniques of data science, particularly the science of large-scale data collections. These methods and techniques include both computational techniques and methods from mathematical statistics. The MSc will also provide you with an appreciation for the professional, ethical and legal responsibilities of the data scientist, along with standard conceptual or scientific models in at least one domain of application of data science. Your individual project will typically aim to apply these methods to a problem in a specific application domain, and provide valuable preparation for a career in research or industry.

Course format and assessment

Lectures; tutorials; seminars; laboratory sessions; optional career planning workshops. Assessed through: coursework; written examinations; final project report.

Career destinations

Via the Department’s Careers Programme, students are able to network with top employers and obtain advice on how to enhance career prospects.



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Our IT systems and devices are constantly creating data and the amount of data created and stored grows exponentially. Data, and in particular patterns and trends within data, have the ability to inform and provide valuable insights, that help us predict and diagnose specific outcomes. Read more
Our IT systems and devices are constantly creating data and the amount of data created and stored grows exponentially. Data, and in particular patterns and trends within data, have the ability to inform and provide valuable insights, that help us predict and diagnose specific outcomes. Whilst the amount of data grows, the science of gaining insights from this data grows with it. Industry, research institutions and government all seek to extract value from data to improve products and services, serve their customers better and run more operationally efficient organisations. Data Scientists use their mathematical, computational and presentational skills to mine data for value and their skills are highly sort after. There is a significant shortage of skilled Data Scientists and so there are many job opportunities available.

Course content
We have designed this MSc course in consultation with industry partners.

This has enabled us to understand their needs for Data Scientists, what skills will be required and on successful completion of this course individuals will be highly employable within businesses.

Having this close understanding of what industry needs makes this course relatively unique and the very best suited to these looking for a career in the Data Sciences.

The course will be of specific interest to :

A mathematics graduate wishing to use your skills in a vocational business based environment
A computer science graduate wishing to follow a vocational route
Individuals currently working in Business and looking to grow their career through gaining Data Science and Business Analytics skills
Six modules go to make up this MSc:

Data Science Foundation
Managing Data
Data Exploration and Analysis
Mathematics
Machine Learning & Cognitive Computing
Data Visualisation and Presentation
The 1 year full time MSc course will be stimulating and interactive, making use of lectures, self-learning, workshops and hands-on projects.

You will be assigned a Personal Tutor from the start of your course who will work with you throughout your studies to help you achieve your academic best.

The knowledge we provide you with in these areas will give you all of the essential know-how on methods, tools and techniques to deliver in your career as a Data Scientist.

We believe Data Science is very much an intellectual ‘contact sport’ and through this course we provide you with every opportunity to put your theoretical knowledge into practice.

The project work we have imbedded within the course has been chosen and developed based on real-world scenarios across a range of industry and government sectors and is specifically designed to:

Provide an essential link between your theoretical learning and real-world challenges
Create an environment where you decide the methods and tools best suited to the challenge based on what you have learnt
Recreate some of the challenges facing industry and Government today and those very similar to what you will encounter in the workplace as a Data Scientist
Be adaptable to reflect new methods / tools and scenarios in this fast developing discipline
Be able upon completion of the projects to reference your experience in working with such challenges

Fees for 2017

Home fees - 1 year full-time: £8000.00

International fees: £10,920.00

Our facilities
You will undertake your workshops in training rooms that are bang up-to-date with design features, touch screen electronic white boards and high speed wifi; housed across three stunning Georgian mansions.

All of our current students love the learning environment, the culture, camaraderie and the fact that tutors know them by name so they are more than just a ‘face in the crowd’.

You will have access to the very best IT facilities in order to support your studies. These range from computer labs to access to cloud analytics from the leading providers.

We will use software from the academic programs of the major enterprise I.T. vendors such as IBM and Amazon as well as commonly used open source programs and frameworks.

From September 2018, many of the teaching sessions will take place in the purpose-built Engineering and Digital Technology building in the Bognor Regis campus.

What's more, you have lots of other facilities on this dedicated university campus including latest books, journals and online data in a truly modern library, an IT centre, a student zone complete with Costa Coffee, a gym and much more.

Where this can take you
The course has been designed to provide you with a very practical understanding of the issues associated with sourcing, curating, analysing and presenting data in business and other public sector and not-for-profit organisations.

On completion of your MSc studies and successful graduation, you will have very transferable skills and can choose to move directly in to the workplace perhaps in retail, banking, government or transport.

Indicative modules
Data Science Foundation (20 Credits)
Managing Data (20 Credits)
Data Exploration and Analysis (20 Credits)
Mathematics (20 Credits)
Machine Learning & Cognitive Computing (20 Credits)
Data Visualisation and Presentation (20 Credits)
Dissertation/Project (60 Credits)


Teaching and Assessment
Our approach to supporting your learning, and how your learning is assessed, is designed to mirror the workplace environment. With this in mind, key features of our approach to learning and assessment include the following:

We place a lot of emphasis on course work related activity.
Opportunities to work with organisations on current commercial/business problems and projects. These experiences are used to provide the basis for assessments that enable you to apply your learning within authentic commercial situations.

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This degree equips you with advanced knowledge and skills for a range of careers from data analyst to computer scientist or IT consultant. Read more
This degree equips you with advanced knowledge and skills for a range of careers from data analyst to computer scientist or IT consultant.

Cloud Computing and Big Data remain hot topics in the media and there is strong demand for graduates with technical skills in this area. Kent’s Advanced Computer Science (Cloud Computing & Big Data) MSc equips you with the advanced knowledge and skills for a wide range of careers from data analysts to computer scientists and IT consultants.

The programme combines a wide choice of advanced topics in computer science with specialist modules relating to cloud computing and big data. These include Google App Engine, Apache Spark, Software-as-a-Service, Data Centers Galaxy, Mobile Cloud, Hadoop, Bitcoin and MapReduce.

This programme is available with an optional industrial placement which provides an opportunity to work in real-world, technical and business roles, enhancing your study experience and having a dramatic impact on your choices after graduation. We have strong links with industry including Cisco, IBM, Microsoft and Oracle and are among the top ten in the UK for graduate employment prospects.

The Advanced Computer Science (Cloud Computing & Big Data) MSc is aimed at graduates considering a career in research and development. It would also provide an excellent foundation for PhD study.

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The Medicine MRes is a strongly research-based programme, which gives you the training and opportunity to develop as a scientist or scientifically-literate clinician. Read more

The Medicine MRes is a strongly research-based programme, which gives you the training and opportunity to develop as a scientist or scientifically-literate clinician.

It can help you to gain:

  • a comprehensive understanding of the concepts and techniques relevant to medical research
  • the ability to critically and creatively evaluate current issues in medicine and health.

You’ll get experience in formulating new hypotheses and exploring the causes and consequences of diseases by conducting rigorous scientific research in a laboratory or with patients.

A nine-month research project helps you to develop specialised knowledge, as well as design and undertake a substantial piece of publishable research. You’ll be based in one of our internationally-renowned institutes and be supervised by leading experts in their field. You can choose from a range of research opportunities in applied health, cancer and pathology, cardiovascular, genes and development, medical education and musculoskeletal topics.

We invite you to view our list of research projects 2017-18. Please contact the supervisory team before applying to the course and in your application state your three preferred research projects.

More information

The School of Medicine is a major international centre for research and education. Our ambition is to improve health and reduce health inequalities, locally and globally, through excellent research and its translation into healthcare practice, and the education of future scientific and clinical leaders who will advocate and practise an evidence-based approach.

Course content

The taught modules are designed to stimulate a deep and critical knowledge of research. The optional modules allow you to develop a comprehensive knowledge of different approaches to medical research.

The Paper Criticism module enables you to develop subject-specific skills, such as an understanding of the ethical issues of medicine and knowledge of the current requirements for the governance of medical research and its publication. You apply your knowledge of research methods to published papers and enhance your critical skills.

The Analytic Research module provides a critical awareness of research planning and methods and develops your research skills. It includes topics on the structure of analytic research investigations; the analysis of the data obtained in analytic studies, especially the metrics used; the problems resulting from bias and confounding and how they are dealt with; basic statistics of precision and comparison;dealing with unequal duration of follow-up in cohort studies; and critical appraisal of published research.

The Capturing and Handling Data in Research module is an introduction to the collection and handling of health research data. It will include topics on: social inclusion in research; sampling from populations; types of data; collecting data through questionnaires; how scales and tests are used to collect data; and how data are collected and described using various fractions such as rates, ratios, risks and odds; recording quantitative and qualitative data in suitable formats; using computers in the analysis of data; the importance of the statistics that summarise quantitative data; and an introduction to the analysis of quantitative and qualitative data. Critical appraisal of published research will underpin theory.

Course structure

Compulsory modules

  • Analytic Research 15 credits
  • Intervention Research 15 credits
  • Capturing and Handling Data in Research 15 credits
  • Research Project in Medicine 120 credits

For more information on typical modules, read Medicine MRes in the course catalogue

Learning and teaching

There are few formal lectures in the MRes programme. Most of your time is devoted to planning and conducting the research project, usually working with a small team of researchers or healthcare professionals.

Interactive tutorial sessions are shared with students on other Masters programmes in the School of Medicine, intercalating medical students and health professionals.

Assessment

There is one examination in May for the Paper Criticism module. Other modules are assessed by the submission of coursework, workbooks, reports and reviews.

Exit awards of Postgraduate Diploma in Medical Research (120 credits) or Postgraduate Certificate in Medical Research (60 credits) are available for this programme.

Career opportunities

The Master of Research in Medicine is for people who want to pursue a lifelong career in academic medicine research.

For medical students, the addition of the Medicine MRes on your CV is an advantage when applying for Academic Foundation Posts and Specialist Training Posts in the NHS.

Careers support

We encourage you to prepare for your career from day one. That’s one of the reasons Leeds graduates are so sought after by employers.

The Careers Centre and staff in your faculty provide a range of help and advice to help you plan your career and make well-informed decisions along the way, even after you graduate. Find out more at the Careers website.



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Gain in-depth knowledge of analytical and predictive modelling skills as well as management, communication and research skills. Read more
Gain in-depth knowledge of analytical and predictive modelling skills as well as management, communication and research skills.

In the era of Big Data, analytics is becoming a strategic necessity in virtually all areas of business and is an essential tool to drive real-time decisions, foster evidence-based decision-making and sustain competitive advantage. According to a recent ranking by US News and World Report, Market Research Analyst and Operations Research Analyst are in the top four Best Business Jobs of 2015, and Harvard Business Review claims Data Scientist is the 'sexiest job of the 21st century' with practitioners having rare and highly sought-after skills.

To meet the growing demand for graduates with analytics capabilities, the MSc in Business Analytics degree equips you with the latest analytics tools to analyse and interpret data, forecast future trends, automate and streamline decisions, and optimise courses of action. Emphasis is placed on learning fundamental analytics techniques, such as statistical analysis, data mining, forecasting and regression, optimisation, simulation and spreadsheet modelling among others.

You will learn how to apply descriptive, predictive and prescriptive modelling techniques to help organisations improve performance, explore alternatives, and anticipate and shape business outcomes in a rapidly changing environment. Upon graduation, you will be ready to start a fast-track career in a variety of industries and sectors including airlines, manufacturing companies, energy, healthcare delivery, banking, marketing and government.

Students enrolled in the programme have the opportunity to work for real organisations, improve their consultancy skills and enhance their employability through the Student Implant Scheme, which bridges the gap between classroom learning and the real world. Students are also involved in a variety of activities, including case studies, team project work, guest lectures and industry visits.

Software demonstration workshops supported by IBM/ILOG are regularly organised to support the teaching of state-of-the-art analytics packages including IBM Watson Analytics, R, SPSS, Weka, MS Excel and VBA, as well as optimisation packages including Optimization Programming Language, IBM/ILOG, CPLEX and Simul8.

This programme is ideal for graduates with a good background in a quantitative area who are seeking to gain an in-depth knowledge of analytical and predictive modelling skills as well as management, communication and research skills.

Visit the website https://www.kent.ac.uk/courses/postgraduate/292/business-analytics

About Kent Business School

Kent Business School has over 25 years’ experience delivering business education. Our portfolio of postgraduate programmes (http://www.kent.ac.uk/kbs/courses/msc/index.html) demonstrates the breadth and depth of our expertise. Academic research and links with global business inform our teaching, ensuring a curriculum that is relevant and current. We are ranked (http://www.kent.ac.uk/kbs/whychooseus/rank-accred.html) as a top 30 UK business school for the standard of our teaching and student satisfaction. We also hold a number of accreditations (http://www.kent.ac.uk/kbs/whychooseus/rank-accred.html?tab=accreditations-and-professional-bodies) by professional bodies.

Studying at Kent Business School (KBS) gives you the opportunity to increase your employability with real-life case studies, a student council and a business society. We have strong links to local and national organisations providing opportunities for projects, internships and graduate placements. The School attracts many high-profile speakers from industry and last year included visits and lectures from staff of the Bank of England, BAE Systems, Barclays, Lloyds Insurance, Cummins, Delphi and Kent County Council.

Careers

You gain much more than an academic qualification when you graduate from Kent Business School – we enhance your student experience and accelerate your career prospects.

From the moment you start with us, our efforts are focused on helping you gain the knowledge, skills and experience you need to thrive in an increasingly competitive workplace.

In today’s business climate employers are increasingly demanding more from new employees, we are therefore proud that they continually target our graduates for their organisations across the globe. Employers respect our robust teaching and reputation for delivering international business expertise, leading global research and an outstanding international learning experience.

Recent graduates have gone on to work for Barclays Capital, British Embassy, Gray Robinson PA and Holiday Extras.

To find out more about business analytics and future career prospects, see the following links.

- OR Society: British Society of Operational Research: http://www.theorsociety.com/

- What is OR? Video and success stories: http://www.learnaboutor.co.uk/

Professional recognition

Kent Business School is a member of the European Foundation for Management Development (EMFD), CIPD, CIM and the Association of Business Schools (ABS). In addition, KBS is accredited by the Association of MBAs (AMBA).

Find out how to apply here - https://www.kent.ac.uk/courses/postgraduate/apply/

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