Masters Degrees (Data Privacy)

Big Data and Data Engineering

Big data has turned out to have giant potential, but poses major challenges at the same time. On the one hand, big data is driving the next stage of technological innovation and scientific discovery. Accordingly, big data has been called the “gold” of the digital revolution and the information age. On the other hand, the global volume of data is growing at a pace which seems to be hard to control. In this light, it has been noted that we are “drowning in a sea of data”.

Faced with these prospects and risks, the world requires a new generation of data specialists. Data engineering is an emerging profession concerned with big data approaches to data acquisition, data management and data analysis. Providing you with up-to-date knowledge and cutting-edge computational tools, data engineering has everything that it takes to master the era of big data.

Program Features

The Data Engineering program is located at Jacobs University, a private and international English-language academic institution in Bremen, Germany. The two-year program offers a fascinating and profound insight into the foundations, methods and technologies of big data. Students take a tailor-made curriculum comprising lectures, tutorials, laboratory trainings and hands-on projects. Embedded into a vibrant academic context, the program is taught by renowned experts. In a unique setting, students also team up with industry professionals in selected courses. Core components of the program and areas of specialization include:

- The Big Data Challenge
- Data Analytics
- Big Data Bases and Cloud Services
- Principles of Statistical Modeling
- Data Acquisition Technologies
- Big Data Management
- Machine Learning
- Semantic Web and Internet of Things
- Data Visualization and Image Processing
- Document Analysis
- Internet Security and Privacy
- Legal Aspects of Data Engineering and Data Ethics

For more details on the Data Engineering curriculum, please visit the program website at http://www.jacobs-university.de/data-engineering.

Career Options

Demand for data engineers is massive – in industry, commerce and the public sector. From IT to finance, from automotive to oil and gas, from health to retail: companies and institutions in almost every domain need experts for data acquisition, data management and data analysis. With an MSc degree in Data Engineering, you will excel in this most exciting and rewarding field with very attractive salaries. Likewise, an MSc degree in Data Engineering allows you to move on to a PhD and to a career in science an research.

Application and Admission

The Data Engineering program starts in the first week of September every year. Please visit http://www.jacobs-university.de/graduate-admission or use the contact form to request details on how to apply. We are looking forward to receiving your inquiry.

Scholarships and Funding Options

All applicants are automatically considered for merit-based scholarships of up to € 12,000 per year. Depending on availability, additional scholarships sponsored by external partners are offered to highly gifted students. Moreover, each admitted candidate may request an individual financial package offer with attractive funding options. Please visit http://www.jacobs-university.de/study/graduate/fees-finances to learn more.

Campus Life and Accommodation

Jacobs University’s green and tree-shaded campus provides much more than buildings for teaching and research. It is home to an intercultural community which is unprecedented in Europe. A Student Activities Center, various sports facilities, a music studio, a student-run café/bar, concert venues and our Interfaith House ensure that you will always have something interesting to do.

For graduate students who would like to live on campus, Jacobs University offers accommodation in four residential colleges. Each college has its own dining room, recreational lounge, study areas, and common and group meeting rooms. Please visit http://www.jacobs-university.de/study/graduate/campus-life for more information.

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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. 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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Typically information governance/security and law have been taught as distinct subjects in different discipline areas. In recognition of the relationship that exists between information governance/information security and the protection of personal data this programme brings together these subjects in one multi-disciplinary qualification.

The Postgraduate Certificate in Data Protection Law and Information Governance is a distance learning course that has been specifically designed to meet the needs of professionals already working in data protection and/or information governance. You will study three modules. The first of these, the legal research module, will develop your ability to undertake legal research and to present your research findings appropriately. In the second module you will develop your understanding of information governance and security principles that underpin the management of an organisation’s information assets. The third module will focus upon data protection law and practice.

The programme will not only provide you with valuable knowledge of current law and proposed developments to the law and to the principles of information governance, it will also enhance your ability to advise upon both information governance and data protection. The research, writing and presentation skills you will develop will also be of use to you in your working environment. Unlike typical CPD type learning this programme will challenge you to undertake critical evaluation of the law and to consider the application of information governance and security to your own/a chosen organisation.

Learn From The Best

This programme is delivered jointly by academics within Northumbria Law School and the iSchool, in the Faculty of Engineering and Environment. Northumbria Law School is actively involved in research and consultancy in the field of data protection, information sharing, freedom of information and privacy law. The iSchool, which delivers the information governance and security module, is widely recognised for its innovative distance and work-based learning programmes in information and records management and for its related research.

This course is delivered by a team of solicitors and academics with extensive experience in data protection and information governance, who are actively researching the area. In addition our team also boast memberships to key professional bodies, in addition to editing industry publications such as the Records Management Journal.

Teaching And Assessment

This course is primarily delivered online to provide flexibility and the ability for you to study at times convenient to you. We believe, however, that opportunities to engage with your tutors and with fellow students are an important part of your learning experience. On two of the modules you will be offered the opportunity to meet your tutors and attend lectures or workshops at the University at an optional study day. All of the content will be available online should you not be able to attend. On the third module you will be encouraged to engage with your tutor and with fellow students via the module discussion board.

Module Overview
KC7046 - Information Governance and Security (Core, 20 Credits)
LW7002 - Data Protection (Core, 20 Credits)
LW7003 - Legal Research (Core, 20 Credits)

Each taught module is assessed via written assignment. On the legal research module you will work in a group with other postgraduate students to undertake the research, writing and review of that assignment. On the data protection module and the information governance module you will submit an individual written assignment at the end of each module. As part of the assessment process you will be expected to undertake a critical evaluation of the law, and to consider information governance and security in your own or another chosen organisation.

Learning Environment

Your course will be delivered online using the latest innovative software. Learning materials such as module handbooks, assessment information, lecture presentation slides, recorded lectures and electronic reading lists will be available via our highly accessible e-learning platform, Blackboard. You can also access student support and other key University systems through your personal account.

Research-Rich Learning

Research Rich learning (RRL) is embedded across the programme, reflecting the pervasive research culture of the law school. Your student journey commences with the Legal Research module. This module will help you to gain a clear awareness and understanding of appropriate legal research methods and legal sources and how to cite those sources. In your subsequent modules your tutors will expose you to a range of academic literature covering substantive data protection law and relevant information governance and data security frameworks and principles. You will also develop your legal research skills further as your tutors encourage you to discuss, evaluate and critically examine relevant principles and frameworks and as you undertake your own research in order to complete your module assignments.

Give Your Career An Edge

It is envisaged that most students who study this programme will already be employed within the data protection/information governance fields. It recognises that the introduction of a new data protection regulation will result in significant challenges for professionals working in the data protection field, and seeks to help you to develop the skills and knowledge which you will need to do your job professionally notwithstanding the changing legislation framework.

Your Future

This course provides academic recognition of your knowledge of data protection and information governance law and your ability to apply that knowledge to practice. It also provides a strong foundation for further study. Should you decide upon completion of the programme that you wish to further develop your knowledge of information rights law or information governance/security then Northumbria Law School and the Faculty of Engineering and Environment both offer masters programmes in these fields. This programme provides you with a stepping stone towards study a Masters in Law (an LLM). Successful completion of this programme exempts you from study of the first three modules on the Pg Dip/LLM in Information Rights Law and Practice.

What Does Britain Leaving The EU Mean For This Course?

We can confirm that we will not be changing the course in light of the Brexit decision. The focus in this course will be the current legal framework, and any likely reforms including the GDPR. There are several reasons why the course will not be changed at this particular point. Firstly there are no changes to the current legal framework on data protection or environmental information. This is well explained in a statement by the information commissioner's office https://ico.org.uk/about-the-ico/news-and-events/news-and-blogs/2016/06/referendum-result-response/ and was reiterated by Baroness Neville-Rolfe, the Government Minister responsible for Data Protection, on 4 July. These statements also acknowledge that there is a need for reform in data protection and that would have to be seen in the context of European data protection laws. Although it is not clear what the exact relationship of the UK and EU will be in the future there is a recognition that there will be a need for equivalency of data protection law in the UK with other countries. The need for equivalency of the law is likely to be necessary whether the UK is part of the single market, or if it exits the European economic area, in order for EU countries to send data to us as part of the 8th principle (See Schedule 1 of the Data Protection Act 1998). As such the GDPR still has relevance in our understanding of what would be required to achieve equivalent protection and what likely reforms on data protection may be considered in the UK. From an educational perspective the examination of reforms such as the GDPR provide a useful mechanism to critique current data protection laws, allowing for the discussion of strengths and weaknesses, even if all those reforms are not ultimately adopted. We will of course keep the position under review, as we do with all our teaching areas in order to ensure that learning material reflects both the current law and likely changes to that law.

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This Joint Degree between HEC Paris and Ecole Polytechnique will equip students with both the technical skills and the strategic mindset to lead successfully any business career requiring a strong expertise in Big Data.

STUDY IN TWO GLOBALLY-RECOGNIZED INSTITUTIONS

Ecole Polytechnique (https://www.polytechnique.edu/en) and HEC Paris are both world leading academic institutions, renowned for the quality of their degrees, faculties and research (see HEC rankings http://www.hec.edu/Masters-programs/About/Rankings).

Their association within this Joint Degree represents the best Business/Engineering combination Europe could possibly offer, with extraordinary added value for the students who will follow this program in Big Data and Business.

LEAD THE DIGITAL TRANSFORMATION OF THE ECONOMY

Big data marks the beginning of a major transformation of the digital economy, which will significantly impact all industries. There are three main challenges to face:

> Technological: dealing with the explosion of data by managing the spread of vast amounts of information that is often very disorganized (IP addresses, fingerprinting, website logs, static web or warehouse data, social media, etc.)
> Scientific: replacing mass data with knowledge,i.e. developing the expertise that makes it possible to structure information, even out of tons of vague or corrupt data.
> Economic: managing data both to control risks and benefit from the new opportunities they offer. On the one hand, it is absolutely vital to be able to control the flow of information, anticipate data leaks, keep the information secure and ensure privacy. On the other hand, it is also essential to come up with solutions capable of transforming this flow of data into economic results and, at the same time, discover new sources of value from the data.

ACQUIRE THE SKILLS TO MAKE A DIFFERENCE IN TOMORROW’S DIGITAL WORLD

Exploiting this vast amount of data requires the following:

> A mastery of the sophisticated mathematical techniques needed to extract the relevant information.
> An advanced understanding of the fields where this knowledge can be applied in order to be in a position to interpret the analysis results and make strategic decisions.
> A strong business mindset and an even stronger strategic expertise, to be able to fully benefit from the new opportunities involved with Big Data problematics and develop business solutions accordingly.
> The ability to suggest and then decide on the choice of IT structures, the ability to follow major changes in IT systems, etc.

Therefore the program has three objectives:

> To train students in data sciences which combines mathematic modelling, statistics, IT and visualization to convert masses of information into knowledge.
> To give students the tools to understand the newest data distributing structures and large scale calculations to ease decision-making and guide them in their choices.
> To form data ‘managers’ capable of exploiting the results from analysis to make strategic decisions at the heart of our changeable businesses.

MAKE THE MOST OF WORLDWIDE NETWORKING AND ALUMNI POWER

Students will benefit not only from the close ties that HEC Paris has developed with the business world but also those of Ecole Polytechnique, through various networking events, conferences and career fairs.

The HEC Alumni network alone, consists of more than 52,300 members in 127 countries.

Program Details

http://www.hec.edu/Masters-programs/Master-s-Programs/Dual-Degree-Programs-with-Partner-Institutions/MSc-Big-Data-for-Business-Joint-Degree-with-Ecole-Polytechnique/Program-Details

Campuses

http://www.hec.edu/Masters-programs/Master-s-Programs/Dual-Degree-Programs-with-Partner-Institutions/MSc-Big-Data-for-Business-Joint-Degree-with-Ecole-Polytechnique/Campuses

CAREERS

As “Big Data” affects all kinds of companies and all sectors, students will have a very large range of career options upon graduation, from consulting firms to digital start-ups, not to mention very large multi-national companies.
In fact, as can be seen in all areas of cutting-edge innovation, there is a growing demand for high level managers who can combine strong technical skill with business know-how.

This is especially true when it comes to Big Data topics, and students graduating from data science and Big Data programs are therefore highly sought after on the job market.

http://www.hec.edu/Masters-programs/Master-s-Programs/Dual-Degree-Programs-with-Partner-Institutions/MSc-Big-Data-for-Business-Joint-Degree-with-Ecole-Polytechnique/Careers

FAQs

http://www.hec.edu/Masters-programs/Master-s-Programs/Dual-Degree-Programs-with-Partner-Institutions/MSc-Big-Data-for-Business-Joint-Degree-with-Ecole-Polytechnique/FAQ

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The Master’s program in Data Science and Entrepreneurship combines management, entrepreneurship and business models with deep knowledge on data science methods from mathematics, statistics and computer science; understanding their limitations with regard to the law, regulations, and ethical considerations.

Why the Master's program in Data Science and Entrepreneurship?
Are you interested in deploying the potential power of big data to solve real-world problems? Is it a challenge for you to work with complex, structured and unstructured data? Do you like to transform innovative data-centered concepts and ideas into concrete novel and value-adding products and services? And to design business initiatives?

Data science entrepreneurs are able to monetize the flood of data that is generated in this digital age by exploiting the economic value of personal data, developing novel ways to get actionable insights from data streams and exploring novel marketing models. They will typically start up and/or innovate within data based product companies.

Therefore, in this English Master's program you will:
- Combine data science courses with courses that address the entrepreneurship pillar of the program
Examples of courses are: data integration and architecture, data mining, business process management, data entrepreneurship, and creative thinking and open innovation.

- Incorporate theories and concepts from legal and ethical aspects of business venturing, intellectual property, and ethical and privacy aspects of data.

- Apply data entrepreneurship in building a technology startup
The backbone of the program is formed by a series of courses called Data Entrepreneurship in Action (1-3). In these courses, student teams use data-driven methods to test the feasibility of an idea/innovation, build a data-intensive product/solution, propose sales channels and customers, and develop entrepreneurial skills in building a technology startup.

- Solve actual problems with real datasets from industrial partners
Representatives from the industrial partners will share actual problems and datasets in two or three applications domains from which student teams can choose. As 'clients' of the teams, the industrial representatives will actively work with our professors to coach the student teams.

This program is not yet registered in the Netherlands Central Register of Higher Education Study Programs (CROHO). A proposal for initial accreditation will be submitted to the Accreditation Organisation of the Netherlands and Flanders (NVAO). This procedure might take up to six months and there is no guarantee of a positive decision by the NVAO. Only after accreditation by the NVAO and subsequent CROHO registration can this program be started up.
For more information about accreditation, please visit http://www.nvao.com.

Associated Schools:

Law School
School of Social and Behavioral Sciences
School of Humanities

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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.

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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With more and more data being captured, there is growing need for people with the skills to manage large data collections, and make use of them through a range of data analysis techniques. It has been said that “data is the raw material of the 21st century”.

The Master of Business Data Science (MBusDataSc) is an interdisciplinary programme that encompasses understanding how data can be used in a business context, how large data sets can be managed, and how data can be analysed. The programme will also develop students’ skills in data analysis techniques and computing.

Graduates of the MBusDataSc will have advanced knowledge in areas including: understanding of opportunities for applying data analysis in business, awareness of ethical and privacy issues and mitigation approaches, understanding of technologies for managing large data sets and the ability to select and apply appropriate technologies, and an understanding of different techniques for analysing data and the ability to select and apply appropriate techniques.

The programme can be completed in a 12 month period.

Programme Requirements

-BSNS 401 The Environment of Business and Economics (20 points)
-COSC 430 Advanced Database Topics (20 points)
-INFO 408 Management of Large Scale Data (20 points)
-INFO 411 Machine Learning and Data Mining (20 points)
-INFO 420 Statistical Techniques for Data Science (20 points)
-INFO 424 Adaptive Business Intelligence (20 points)
-MART 448 Advanced Business Analytics (20 points)

Plus one of the following project papers:
-BSNS 501 Applied Project or BSNS 580 Research Project (40 points)

Structure of the Programme

-A candidate may be exempted from some of the required papers on the basis of previous study. Alternative papers will be required at an equivalent level of study.
-A candidate shall, before commencing the investigation to be described in the applied or research project, secure the approval of the Head of the Department concerned for the topic, the supervisor(s) and the proposed course of the investigation.
-A candidate may not present a project report which has previously been accepted for another degree.
-A candidate must pass both the papers and the project components.

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About the course

This CILIP-accredited course produces highly employable graduates for a rapidly expanding global job market. It was developed in collaboration with external organisations across a range of sectors to make sure you gain knowledge and learn skills that employers are looking for.

You’ll learn the theory and the skills you need to support data-driven decision-making in organisations. The course covers three core areas: data management, data analysis and business insight. You’ll get hands-on experience with data management and analysis. Industry experts contribute to the course, sharing their experience and talking you through examples of data science in action.

Our graduates are not just technically proficient. They’re also keenly aware of broader issues such as data presentation, privacy and ethics. That extra edge makes them even more attractive to employers.

Your career

Effective use of information improves the world and makes a positive difference to our lives. It is also central to economic development. The rapid pace of technological change and the globalisation of markets means that organisations in all sectors must realise the value of information systems.
The world needs graduates who are information literate.

Our graduates work for all kinds of organisations, in the public and private sectors. Employers include:

Adidas; BBC; British Red Cross; Cambridge University; The Department of Health; Ernst and Young; GCHQ; Goldman Sachs; Hewlett-Packard CDS; House of Commons Library; Imperial College London; IBM; Kings College London; NHS; Pepsico; Pricewaterhouse Coopers; Stanford University

If you’re already an experienced professional, you can develop new skills and advance your career with one of our Professional Enhancement Programmes (page xxx).

Your subject

Our courses are research-led, which means you’ll learn about the latest concepts from academics who work with organisations to drive developments in this field. Alongside the theory and technical skills, you’ll develop some valuable attributes including effective communication, application of research methods and creative problem solving.

How we teach

All our courses (except our distance learning courses) include lectures, seminars, tutorials, practical laboratory classes, group work, online discussion, case studies and lectures by visiting speakers. Our MA Librarianship course also includes visits to library and information service organisations. You’ll be assessed using a wide variety of methods including essays, reports, small projects, in-class tests, presentations, posters, group work and a research-based dissertation.

Learning Environment

Our dedicated departmental teaching suite contains two networked laboratories with 60 computers and a 30-seat lecture room. Our state of the art iLab includes a Usability Lab and Digital Media Lab designed to collect research data into human–computer interaction.

The iSpace is an open plan, social learning area for students. It has display facilities, open-access PCs and bookable partitioned group work areas. There is Wi-Fi coverage throughout the department, and you can connect your own laptop to our network. Mobile devices and tables are available for you to borrow for project work.

We’re right in the middle of the campus and close to the Information Commons and the new Diamond building so you’ll be able to access the University’s many resources.

Core modules

Introduction to Data Science; Data Mining and Visualisation; Data Analysis; Database Design; Research Methods and Dissertation Preparation; Dissertation.

Examples of optional modules

Information Systems in Organisations; Business Intelligence; Information Governance and Ethics; Researching Social Media; Information Retrieval: Search Engines and Digital Libraries; Digital Advocacy; Data and Society.

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Increasingly, big data are used to track and trace social trends and behaviours. In turn, governments, business and industries worldwide are rapidly recruiting graduates who can understand and analyse big data. This course addresses how big data challenge traditional research processes, and impact on security, privacy, ethics, and governance and policy. You will learn practical and theoretical data skills, both in quantitative methods and the wider theoretical implications about how big data are transforming disciplinary boundaries.

You will take three core modules and a dissertation. Three option modules (see below) allow further specialisation. Lab work, report writing, data skills training and guest lectures by industry experts will form an integral part of your learning experience. You will be invited to attend short certified ‘Masterclasses’ to further extend your methodological repertoire. An annual Spring Camp on a key theme (e.g. health; networks; food) is also provided, allowing you to gain expertise in a wide range of cutting-edge quantitative methods.

You don’t need a computer science, mathematics or statistics background to apply. The focus is on conducting and understanding applied quantitative social science, so a willingness to engage with real world social science issues is essential.

Course Overview

Core Modules
-Big Data Research: Hype or Revolution?
-Principles in Quantitative Research
-Advanced Quantitative Research
-Dissertation

Masters Optional Modules
-Visualisation
-Social Informatics
-Big Data Research
-Hype or Revolution?
-Complexity in the Social Sciences
-Media and Social Theory
-Digital Sociology
-Post Digital Books
-User Interface Cultures
-Design, Method and Critique
-Playful Media
-Ludification in the Digital Age

Assessment
A combination of essays, reports, design projects, technical report writing, practice assessments, group work and presentations and an individual research project.

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Centennial College's Marketing Research and Analytics program positions you at the forefront of a cutting edge job market in which organizations have oceans of data available to them but struggle to make sense of it as marketing becomes increasingly data-driven. As a result, there is a large and growing demand for trained researchers who can harness the power of big data using the latest tools and analytical techniques to uncover new insights and drive businesses forward.

This Marketing Research and Analytics program combines advanced courses in marketing research and big data analytics with training on leading commercial technologies and platforms and the opportunity to gain in-demand industry certifications.

This program equips you with knowledge, skills and training in leading business intelligence and marketing research technologies and tools used in the field. Among them are SAS Enterprise Guide and SAS Enterprise Miner, Environics Analytics Envision (used to develop comprehensive profiles of selected target markets), SPSS, Tableau (the leading data visualization software), Excel, XL Miner, Dell Factiva and NVIVO (qualitative research and text analysis software).

Upon graduation, you receive an Ontario Graduate Certificate from Centennial College, plus certificates of recognition from SAS and Environics Canada. In addition, you are put on an accelerated track to earning the Certified Marketing Research Professional (CMRP) designation, the premier credential in Canadian marketing research from the Marketing Research and Intelligence Association (MRIA).

Career Opportunities

Program Highlights
-The Marketing – Research and Analytics program combines marketing research principles and skills with cutting edge "big data" analytics techniques to equip you with the training required to deliver insights and strategies to help organizations make smarter and more impactful business decisions.
-Employed is an extensive use of learner-centered approaches such as case studies, simulations and project-based learning, with a focus on developing project management, teamwork, analytical thinking, and report writing and presentation skills.
-Hands-on learning covers areas such as questionnaire design, data manipulation, quality control, statistical output and program development.
-There is a strong focus on applying marketing research and analytics to strategic marketing decision-making.
-In the second semester, you develop and implement a capstone project that will integrate and apply your learning.
-In addition to market research technologies, you also have access to the full suite of Microsoft products, including Microsoft Excel, XL Miner, Access and PowerPoint.
-Once you graduate, you have the option to take the Comprehensive Marketing Research Exam (CMRE) on campus at Centennial College, which leads to the Certified Marketing Research Professional (CMRP) designation.

Articulation Agreements
Start with a graduate certificate, and continue to a master of business administration through our degree completion partnership. Successful graduates of this Marketing – Research and Analytics program may choose to continue with courses leading to a graduate degree.

Career Outlook
-Marketing research specialist or analyst
-Research analyst
-Marketing research and intelligence coordinator
-Market intelligence specialist or analyst
-Customer insights analyst
-Consumer research manager
-Business intelligence analyst
-Market research analytics manager
-Web marketing analyst
-Customer experience analyst
-CRM analyst
-Direct response analyst
-Digital marketing analyst
-Social media analyst
-Data and analytics specialist
-Business analytics specialist
-Loyalty program analyst
-Sales analyst
-Marketing strategy analyst

Program Outcomes
-Optimize the financial results produced by interactive marketing programs through the application of marketing analytics
-Contribute to the design of a marketing analytics team project (develop charter, business case financials, technical requirements, design, test plan, test results, approval to proceed) and the management of the resulting project
-Create, manage and mine, and apply modelling and decision making functions to a database
-Utilize data auditing techniques and quality control processes that are consistent with current marketing research codes of conduct and Canadian privacy principles to ensure the integrity of the data collection, storage, analysis and presentation processes
-Compare and contrast, evaluate and select appropriate data sources to meet specific marketing objectives
-Conduct industry, competitor and customer analyses using a wide variety of secondary research sources
-Produce reliable and analyzable data through the application of sound questionnaire design principles to marketing research projects
-Design marketing research projects and interactive marketing programs that are founded in sound sampling techniques, hypothesis testing and research design
-Solve business and marketing problems by identifying, selecting and applying effective, current and relevant techniques such as descriptive and inferential analysis
-Prepare provisional output of analyses including cross-tabulations and pivot tables that address the needs of analysts and prepare final output, including research reports, presentation sides and visual representations of data that address the needs of management
-Develop actionable recommendations based on situation analyses and research findings

Areas of Employment
-Retail corporations
-Organizations with in-house analytical and research functions
-Marketing research firms

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INSTITUTE FOR DESIGN INNOVATION

You will have the opportunity to engage with the very latest Cyber Security principles, practices, tools, and techniques through practical application analysing and evaluating problems and responding to challenges in real time.

This programme will provide students with a comprehensive understanding of the challenges in Cyber Security faced by industry and society, and will help you to develop the necessary skills to address those challenges in the most effective way. This programme will enable you to build knowledge and develop expertise in network security in cryptography and through action-based learning to provide you with employment skills essential to the Cyber Security industries and related businesses, e-commerce, and governmental organisations.

See the website http://www.lborolondon.ac.uk/study/institutes-programmes/cybersecurity-and-big-data/

Programme Aims

a) Provide students with a comprehensive understanding of the challenges in cyber security faced by industry and society, and will help them to develop the necessary skills to address those challenges in the most effective way

b) Utilise both cyber security and big data analytics techniques to analyse and evaluate problems and respond to challenges with practical applications in real time

c) Build students’ knowledge and develop expertise in network security and cryptography, including big data analytics to combat malicious activities and to detect anomalies in the network

d) Provide individuals and teams with employment skills essential to the cyber security industries and related businesses, such as IT, e-commerce, and governmental organisations using action-based learning

Programme Structure

To complete the MSc Cyber Security and Big Data students must complete 8 x 15 credit modules. Students must also choose and complete 3 of the 6 optional modules. Students will pick a second subject from the list of nominated second subject modules offered by the other Institutes in the first semester. All students must complete a Dissertation worth 60 credits.

ASSESSMENT

Modules are assessed primarily by exams and also include a combination of group exercises, presentations and time-constrained coursework and assignments with varying levels of weighting depending on the nature of each module.

CAREER PROSPECTS

Graduates from this programme will be in a very strong position to take on digital technology posts in a wide range of industries, including Internet and cloud based businesses, finance firms, governmental organisations, consultancy companies operating in information, communication and network security, as well as those sectors dealing with massive personal data, such as health and well being, where users' privacy and trust needs safeguarding.

Graduates will also have the opportunity to enhance their knowledge and career prospects further by undertaking a PhD programme.

COMPULSORY MODULES

- Collaborative Project
- Dissertation
- Applied Cryptography

OPTIONAL MODULES

Choose three modules only:
- Media Processing and Coding
- Internet and Communication Networks
- Internet of Things and Applications
- Introduction to Programming and MatLab

SECOND SUBJECT MODULES

Choose one module only
- Design Thinking
- Principles of Entrepreneurship and Innovation Management
- Sport Media and Marketing
- The Key Topics in Media and Creative Industries
- Introduction to Diplomacy
- Business Model Development

See here for information on modules: http://www.lborolondon.ac.uk/study/institutes-programmes/cybersecurity-and-big-data/

Scholarships

We are investing over half a million pounds (£0.5m) in our scholarship and bursary scheme to support your studies at Loughborough University London in 2017.

This package of support celebrates and rewards excellence, innovation and community. Our ambition is to inspire students of the highest calibre and from all backgrounds and nationalities to study with us and benefit from the wider Loughborough University experience and network. Our range of scholarships, bursaries and support packages are available to UK, EU and international students.View the sections below to discover which scholarship options are right for you.

What's on offer for 2017?
Inspiring Success Programme
-For unemployed and underemployed* graduates living in the East London Growth Boroughs of Hackney, Newham, Tower Hamlets or Waltham Forest
-Award value: 100% off your tuition fees
-We are joining forces with The London Legacy Development Company to offer a two day programme of specialist support for graduates, including workshops, skills seminars and networking opportunities to increase students' employability and support those looking to enter into postgraduate education.
-Eligibility: At the end of the programme, eight students will be selected for a 100% scholarship to study a masters course of their choice at our London campus in September 2017.

Dean's Award for Enterprise
-For students looking for the skills and support to launch a new business
-Award value: 90% off fees to launch your business idea
-Eligibility: The award will be given at the discretion of the Dean and the Senior Leadership Team, based on a one-page submission of your business idea.

East London Community Scholarship
-For any students who obtained their GCSE’s or A-levels (or equivalent qualifications) from The Growth Boroughs – Barking and Dagenham, Greenwich, Hackney, Newham, Tower Hamlets and Waltham Forest
-Award value: 50% off your tuition fees
-Eligibility: Competitive scholarship based on one-page submission showing your contribution to our community.

Alumni Bursary
-For all Loughborough University alumni
-Award value: 20% off your tuition fees
-Eligibility: International and UK/EU alumni holding a current offer for LoughboroughExcellence Scholarship
-For international and UK/EU high achieving students
-Eligibility: Any student holding a high 2:1 or first class undergraduate degree or equivalent from a recognised high quality institution will be considered

Find information on Scholarships here http://www.lborolondon.ac.uk/study/scholarships-and-bursaries/

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The rapid growth of available data is transforming the way managers, accountants, investors or marketers are working. Including this data into their analyses, business plans and decisions is a must for firms to maintain their competitive advantage.

This programme is a response to these changes in the economic and technological environment. It aims to transform business students into multi-talented professionals, standing in-between their core field of expertise, such as management, finance, and marketing, and information technologies.

The programme mixes advanced modules in finance, marketing or management to provide a deep understanding of the most up-to-date methods for data-processing (machine learning, big data analysis) and data management. Our teaching philosophy is practice-oriented. With this in mind, after an intensive 12-month period of study you will complete your training with a six-month internship within a company.

Distinctive features of the programme are:
• Access to the Big Data Analytics and Technology Centre (BDATC)
• Strong focus on practical data processing and analysis skills
• Internship opportunities
• Industry links to local companies
• Cooperation with Xi’an Jiaotong University

Modules

• Introduction to Business Analytics
• Addressing Privacy and Ethical Risks of Data Sharing
• Econometrics
• Databases and Data Management
• Finance Pathway (I) - Financial Markets
• Marketing Pathway (I) - Social Media Marketing
• Management Pathway (I) - Strategic Business Analysis
• Data Mining and Machine Learning
• Social Network Analysis
• Big Data: Applications in Business
• Finance Pathway (II) - Portfolio Management
• Marketing Pathway (II) - Marketing Management
• Management Pathway (II) - Strategic Operation Management
• Internship Report / Dissertation

What are my career prospects?

Business analytics skills are in high demand in every sector of the economy, particularly within the fast-growing service sectors (finance, retail, marketing, ICT). Typical positions our graduates target include data or information analyst, technical consultant, IT-related project manager, and CRM analyst.

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Distributed and networked computation is now the paradigm that underpins the software-enabled systems that are proliferating in the modern world, with huge impact in the economy and society, from the sensor and actuator networks that are now connecting cities, to cyberphysical systems, to patient-centred healthcare, to disaster-recovery systems.

This new Masters course will educate and train you in the fundamental principles, methods and techniques required for developing such systems. Given the number of elective modules offered, you will be able to acquire further skills in one or more of Cloud Computing, Data Analytics and Information Security.

Facilities include a laboratory where you can experiment with physical devices that can be interconnected in a network, and a cluster facility configured to run the Hadoop MapReduce stack.

A Year in Industry option is also available for this course.

See the website https://www.royalholloway.ac.uk/computerscience/coursefinder/msc-distributed-and-networked-systems.aspx

Why choose this course?

This course will develop a highly analytical approach to problem solving and a strong background in distributed and networked systems, fault-tolerance and data replication techniques, distributed coordination and time-synchronisation techniques (leader-election, consensus, and clock synchronisation), data communication protocols and software stacks for wireless, sensor, and ad hoc networking technologies in virtualisation, and cloud computing technologies.

The course develops an advanced understanding of principles of failure detection and monitoring, principles of scalable storage, and in particular NoSQL technology.

Students will acquire the ability to:
- apply well-founded principles to building reliable and scalable distributed systems
- analyse complex distributed systems in terms of their performance, reliability, and correctness
- design and implement middleware services for reliable communication in unreliable networks
- work with state-of-the-art wireless, sensor, and ad hoc networking technologies
- design and implement reliable data communication and storage solutions for wireless, sensor, and ad hoc networks
- detect sources of vulnerability in networks of connected devices and deploy the appropriate countermeasures to information security threats.
- enforce privacy in “smart” environments
- work with open source and cloud tools for scalable data storage (DynamoDB) and coordination (Zookeeper)
- work with modern network management technologies (Software-Defined Networking) and standards (OpenFlow)
- design custom-built application-driven networking topologies using OpenFlow, and other modern tools
- work with relational databases (SQL), non-relational databases (MongoDb), as well as with Hadoop/Pig scripting and other big data manipulation techniques.

Department research and industry highlights

Royal Holloway is recognised for its research excellence in Machine Learning, Information Security, and Global Ubiquitous Computing.
We work closely with companies such as Centrica (British Gas, Hive), Cognizant, Orange Labs (UK), the UK Cards Association, Transport for London and ITSO.
We host a Smart Card Centre and we are a GCHQ Academic Centre of Excellence in Cyber Security Research (ACE-CSR).

Course content and structure

You will take taught modules during Term One (October to December) and Term Two (January to March). Examinations are held in May. If you are in the Year-in-Industry pathway, you then take an industrial placement, after which you come back for your project/dissertation (12 weeks).

Core course units are:
Interconnected Devices
Advanced Distributed Systems
Wireless, Sensor and Actuator Networks
Individual Project

Elective course units are:

Computation with Data
Databases
Introduction to Information Security
Data Visualisation and Exploratory Analysis
Programming for Data Analysis
Semantic Web
Multi-agent Systems
Advanced Data Communications
Machine Learning
Concurrent and Parallel Programming
Large-Scale Data Storage and Programming
Data Analysis
On-line Machine Learning
Smart Cards, RFIDs and Embedded Systems Security
Network Security
Computer Security
Security Technologies
Security Testing
Software Security
Introduction to Cryptography

Assessment

Assessment is carried out by a variety of methods including coursework, practical projects and a dissertation.

Employability & career opportunities

Our graduates are highly employable and, in recent years, have entered many different [department]-related areas, including This taught masters course equips postgraduate students with the subject knowledge and expertise required to pursue a successful career, or provides a solid foundation for continued PhD studies.

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Programme description

Design Informatics combines Data Science with Design Thinking in a context of critical enquiry and speculation. We build a value-aware, reflective practice at the interface between data and society by combining theory and research with an open-ended process of making and hacking.

Human activity is being constantly shaped by the flow of data and the intelligences that process it, moving towards an algorithmically mediated society. Design Informatics asks how we can create products and services within this world, that learn and evolve, that are contextualised and humane. Beyond that, it asks questions about what things we should create, speculating about the different futures we might be building and the values behind them.

The central premise is that data is a medium for design: by shaping data, we shape the world around us. Data Science provides the groundwork for this, with Design Thinking underpinning reflective research through design. You will use this in working with the internet of things and physical computing, machine learning, speech and language technology, usable privacy and security, data ethics, blockchain technologies. You will connect technology with society, health, architecture, fashion, bio-design, craft, finance, tourism, and a host of other real world contexts, through case studies, individual, and collaborative projects. You will understand user experience in the wider socio-cultural context, through an agile programme of hacking, making and materialising new products and services.

Programme structure

Please be aware that the structure of the programme may change.

Throughout the programme, you will be working both individually and in teams of designers and computer scientists. Everyone will have to write code during the course, and everyone will have to make physical objects. Several courses, including the dissertation, will involve presenting the artefact, product, service, or interactive experience that you have created to the general public in a show.

In the first year, you will study:

• Design Informatics: Histories and Futures
• Data Science for Design (compulsory for MA/MFA, strongly recommended for MSc/ Advanced MSc)
• Case Studies in Design Informatics 1
• Design with Data
• Design Informatics Project
• 20 credits of elective courses

In Design with Data and Design Informatics Project, you are likely to work with an external partner, such as the Royal Bank of Scotland, Amazon, Edinburgh City Council, Royal Botanic Garden Edinburgh or the National Museum of Scotland.

MSc and MA students then undertake a dissertation in the summer before graduation.

MFA and Advanced MSc students take a summer placement with a relevant digital organisation then return for a second year of study, comprising:

• Case Studies in Design Informatics 2
• 60 credits of elective courses
• A dissertation

Elective courses are drawn from the Masters Programmes of the School of Informatics, Edinburgh College of Art, and Philosophy, Psychology, and Language Sciences. Courses are typically 10 or 20 credits.

Career opportunities

This degree will put you at the cutting edge of the intersection between data science, design, and information technology, opening a host of opportunities in working with companies, charities, and the public sector. We encourage entrepreneurship. For those who wish to stay in academia, the course provides a solid foundation for a PhD in related areas.

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A solid, theoretical understanding of computer technology with plenty of attention for the wide range of ICT applications.

The enormous and rapidly growing power of ICT is the main driving force shaping our modern society. This goes beyond the technical and economical aspects. ICT is also essential in research as all sciences benefit from the raw power of software in processing huge quantities of data. But how do we manage and control the complexity of modern software? How can we make the most of the opportunities? And, not to be forgotten, how can we secure the ICT infrastructures we so heavily rely on? The Master’s programme in Computing Science covers all these aspects.

We offer specialisations in each terrain: security, software, data and the mathematics at the base of it all. These are not, however, isolated disciplines. We also look at the interesting interplay between them. For example, by taking privacy into account when dealing with big data. And by doing a thorough analysis of newly designed software to prevent security breaches later. Thanks to a large number of optional courses, you can decide where you want your focus to be.

The job opportunities in computer science are excellent: many of our students get offered jobs before they’ve even graduated and almost all have positions within six months after graduating. Many of our graduates find jobs as systems builders, ICT specialists or ICT managers and a few continue as researchers.

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

Specialisations

- Cyber Security
You’ll learn to assess the security of existing ICT solutions, and how to develop more secure solutions for the future. This specialisation is offered in collaboration with the Eindhoven University of Technology, meaning you get taught by many of the best cyber security experts in the country.

- Data Science
You’ll learn how to turn real-world data sets into tools and useful insights, with the help of software and algorithms. Radboud University and the iCIS research institute are leading in research on legal and privacy aspects of data science and on the societal and administrative impact of data science.

- Mathematical Foundations of Computer Science
You’ll come to understand the fundamental mathematical concepts of computation and information in order to stretch the boundaries of computer technology. We’re the only specialisation in the country – and one of the few in the world – to focus on the theoretical and abstract playing field linking mathematics and computer science.

- Software Science
You’ll learn how to design high-level software that guarantees safety while controlling its complexity. At Radboud University, we are specialised in model based development. In other words, writing and testing code before they are unleashed in the real world or built into an expensive prototype.

- Societal Master's specialisations
You can either follow one of the above-mentioned research Master's specialisations as a whole (2 years), or you can combine the first year of the research specialisation with an additional year of one of the societal Master’s specialisations, namely:
- Science in Society
- Science, Management and Innovation

Why study Computing Science at Radboud University?

- All of our specialisations are closely related to the research carried out within the Institute for Computing and Information Science (iCIS).
- 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.
- There are plenty of high profile companies in the vicinity such as Philips and ASML, where you could do an internship or the research for your Master’s project.
- Exceptional students who choose the Data Science specialisation have the opportunity to do 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.

Career prospects

There is a serious shortage of well-trained information specialists. Often students are offered a job before they have actually finished their study. About 20% of our graduates choose to go on to do a PhD but most find jobs as systems builders, ICT specialists or ICT managers in the private sector or within government.

Our research in this field

The Institute for Computing and Information Science (iCIS) is the research institute that is connected to Radboud University. Within this institute there are three research sections:
- Model Based System Development
- Digital Security
- Intelligent Systems

Within each research section there are different departments/groups that have their own research. On the websites of the research sections you will find more information about their research, publications, the departments/groups and contact information.

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

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