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Masters Degrees (Web Analytics)

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What is special about this course?. In the past twenty years, the web has had a major impact on the way in which we work, live and learn. Read more

What is special about this course?

In the past twenty years, the web has had a major impact on the way in which we work, live and learn. As the sector continues to grow there is a constant need for individuals and organisations to keep abreast of new developments in the field. This programme has been designed to meet the needs of the global IT industry and will give you the advanced skills and expertise to excel in this fast-paced and competitive marketplace.

This fully online programme offers two specialised exit awards; the pathway you choose will depend on your own specific background and interests:

MSc Web Technologies

If your knowledge and experience of computing are already beyond that of an end-user and you wish to gain enhanced web technologies skills, then this pathway is for you. You will explore cutting-edge technologies and gain a solid grounding in programming and software development.

MSc Web Technologies with Management

This pathway, while primarily having a technological focus, will explore key aspects of business and management particularly relevant in an international environment. You will receive a thorough grounding in core management principles, practices and techniques strongly contextualised to web-based applications.

Both pathways will help you develop and build on your specific technical expertise, and gain practical, analytical, and highly transferable skills sought after by employers.

Special features

  • Gain a master's degree at a pace that suits you through online study
  • Fully online study allows you the flexibility to fit your study around work and personal commitments
  • Study individual modules for your own professional development or work towards the PgCert, Pg Diploma and ultimately a Masters award

How will I study my course?

  • You will study through supported online learning using the university's virtual learning environment (VLE)

How long will my course last?

  • Part-time (structured): Pg Cert 1 year, Pg Diploma 2 years, it will nornally take 3 years to complete the MSc. 
  • Part-time (unstructured): Individual modules chosen as CPD will normally take approximately 12 weeks to complete.

Where can I study my course?

  • Perth College UHI - You will be enrolled at Perth College UHI but can study this course from anywhere in the UK

Start date

  • September
  • January (subject to module availability)

Course Content

MSc Web Technologies:

  • Choose three subjects from the list below to achieve the PgCert Web Technologies (60 credits)
  • Successful completion of another three modules and you will have the PgDip Web Technologies (120 credits)
  • For the full Masters you will be required to complete a dissertation (180 credits).

Modules include:

  • Web services
  • Web technologies: cyber security
  • Mobile applications development
  • Web application development
  • Advanced web programming
  • Data modelling on the web
  • Data analytics on the web

MSc Web Technologies with Management:

  • Choose three subjects from module list 1 below and one from module list 2 to achieve the PgCert Web Technologies (60 credits)
  • Successful completion of another two modules from list 1 and one from list 2 and you will have the PgDip Web Technologies (120 credits)
  • For the full Masters you will be required to complete a dissertation (180 credits).

Module list 1:

  • Web services
  • Web technologies: cyber security
  • Mobile applications development
  • Web application development
  • Advanced web programming
  • Data modelling on the web
  • Data analytics on the web

Module list 2:

  • Corporate and competitive strategy
  • Understanding social media
  • Strategic marketing

What can I do on completion of my course?

On successful completion of the programme you will have improved your skills, confidence and knowledge levels, leading to enhanced career opportunities in different sectors of the IT industry. Alternatively, you may be interested in roles in the public sector, in academia, or through business start-up and growth.

Funding

From 2017, eligible Scotland domiciled students studying part-time who meet the residency eligibility can apply for a for a tuition fee loan up to £2,750 per year from the Student Awards Agency Scotland (SAAS).

Full details can be found on the SAAS website. Applications for loans open in April.

Students from the rest of the UK who meet the eligibility requirements may be able to apply for a loan from the Student Loan Company

You may also be able to apply for a government Professional and Career Development Loan



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1. Big Challenges being addressed by this programme – motivation. Globally, there is a reported shortage of data analytics talent, particularly of individuals with the required deep technical and analytical skills. Read more

About the Course

1. Big Challenges being addressed by this programme – motivation

• Globally, there is a reported shortage of data analytics talent, particularly of individuals with the required deep technical and analytical skills.
• Accenture, Gartner and McKinsey have all identified Data Analytics as one of the fastest growing employment areas in computing and one most likely to make an impact in the future.
• The Irish Government’s policy is for Ireland to become a leading country in Europe for big data and analytics, which would result in 21,000 potential new employment opportunities in Ireland alone.
• CNN has listed jobs in this area in their Top 10 best new jobs in America.

2. Programme objectives & purpose

This is an advanced programme that provides Computing graduates with advanced knowledge and skills in the emerging growth area of Data Analytics. It includes advanced topics such as Large-Scale Data Analytics, Information Retrieval, Advanced Topics in Machine Learning and Data Mining, Natural Language Processing, Data Visualisation and Web-Mining. It also includes foundational modules in topics such as Statistics, Regression Analysis and Programming for Data Analytics. Students on the programme further deepen their knowledge of Data Analytics by working on a project either in conjunction with a research group or with an industry partner.

Graduates will be excellently qualified to pursue careers in national and multinational industries in a wide range of areas. Our graduates currently work for companies as diverse as IBM, SAP, Cisco, Avaya, Google, Fujitsu and Merck Pharmaceuticals as well as many specialised companies and startups. Opportunities will be found in:
• Multinational companies, in Ireland and elsewhere, that provide services and solutions for analytics and big data or whose business depend on analytics and big data technologies;
• Innovative small to medium-sized companies and leading-edge start-ups who provide analytics solutions, services and products or use data analytics to develop competitive advantage
• Companies looking to extend their research and development units with highly trained data analytic specialists
• PhD-level research in NUI Galway, elsewhere in Ireland, or abroad

3. What’s special about CoEI/NUIG in this area:

• The MSc in Computer Science (Data Analytics) is being delivered by the Discipline of Information Technology in collaboration with the Insight Centre for Data Analytics (http://insight-centre.org) and with input from the School of Mathematics, Statistics and Applied Mathematics in NUI Galway
• The Discipline of Information Technology at NUI Galway has 25-year track record of education, academic research, and industry collaboration in the field of Computer Science
• The Insight centre at NUI Galway is Europe’s largest research centre for Data Analytics

4. Programme Structure – ECTS weights and split over semester; core/elective, etc.:

• 90ECTS programme
• one full year in duration, beginning September and finishing August
• comprises:
- Foundational taught modules (20 ECTS)
- Advanced taught modules (40 ECTS)
- Research/Industry Project (30 ECTS).

5. Programme Content – module names

Sample Foundational Modules:

• Tools and Techniques for Large Scale Data Analytics
• Programming for Data Analytics
• Machine Learning and Data Mining
• Modern Information Management
• Probability and Statistics
• Discrete Mathematics
• Applied Regression Models
• Digital Signal Processing

Sample Advanced Modules:

• Advanced Topics in Machine Learning and Information Retrieval
• Web Mining and Analytics
• Systems Modelling and Simulation
• Natural Language Processing
• Data Visualisation
• Linked Data Analytics
• Case Studies in Data Analytics
• Embedded Signal Analysis and Processing

6. Testimonials

Ms. Gofran Shukair, MSc, Research Engineer at ZenDesk, Ireland

After graduating with an MSc at NUI Galway, Gofran worked with Fujitsu’s Irish Research Lab as a research engineer before moving to a software engineering position at Zendesk, Ireland.

“The mix of technical and soft skills I gained through my Masters studies at NUI Galway is invaluable. I had the chance to work with great people and to apply my work on real world problems. With the data management and analysis skills I gained, I am currently pursuing my research in an international research project with one of the leading IT companies. I will be always thankful for studying at NUI Galway, a great historic place based in a culturally-rich vibrant city with an international mix of young and ambitious students that made me eager to learn and contribute back the moment I graduated.”

For further details

visit http://www.nuigalway.ie/courses/taught-postgraduate-courses/msc-in-computer-science-data-analytics.html

How to Apply:

Applications are made online via the Postgraduate Applications Centre (PAC) https://www.pac.ie
Please use the following PAC application code for your programme:

M.Sc. Computer Science – Data Analytics - PAC code GYE06

Scholarships :

Please visit our website for more information on scholarships: http://www.nuigalway.ie/engineering-informatics/internationalpostgraduatestudents/feesandscholarships/

Visit the M.Sc. Computer Science – Data Analytics page on the National University of Ireland, Galway web site for more details!

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The MSc covers web-related technologies and big data analytics. It is intended for students with a general science and engineering background and is an ideal preparation for roles with some of the best internet-related industries and areas requiring big data analytical skills. Read more

The MSc covers web-related technologies and big data analytics. It is intended for students with a general science and engineering background and is an ideal preparation for roles with some of the best internet-related industries and areas requiring big data analytical skills.

About this degree

Students will gain a detailed knowledge and understanding of web-related technologies and big data analytics, ranging from information search and retrieval, natural language processing, data mining and knowledge acquisition, large-scale distributed data analytics and cloud computing to e-commerce and their business economic models and the latest concepts of social networks.

MSc students undertake modules to the value of 180 credits.

The programme consists of three core modules (45 credits), five optional modules (75 credits), and the research dissertation (60 credits).

Core modules

  • Complex Networks and Web (15 credits)
  • Information Retrieval and Data Mining (15 credits)
  • Web Economics (15 credits)

Optional modules

Students must choose a minimum of 45 and a maximum of 75 credits of optional modules. Up to two electives (30 credits) may also be chosen instead of two of the optional modules.

  • Affective Computing and Human-Robot Interaction (15 credits)
  • Applied Machine Learning (15 credits)
  • Birkbeck College: Cloud Computing (15 credits)
  • Computer Graphics (15 credits)
  • Entrepreneurship: Theory and Practice (15 credits)
  • Graphical Models (15 credits)
  • Interaction Design (15 credits)
  • Machine Vision (15 credits)
  • Probabilistic and Unsupervised Learning (15 credits)
  • Statistical Natural Language Processing (15 credits)
  • Supervised Learning (15 credits)

Please note: the availability and delivery of optional modules may vary, depending on your selection.

A list of acceptable elective modules is available on the Departmental page.

Dissertation/report

All students undertake an independent research project which culminates in a substantial dissertation.

Teaching and learning

The programme is delivered through a combination of lectures, tutorials and seminars. Lectures are often supported by laboratory work with help from demonstrators. Student performance is assessed by unseen written examinations, coursework and the dissertation.

Careers

Graduates from UCL are keenly sought after by the world's leading organisations, and many progress in their careers to secure senior and influential positions. Graduates of our Web Science and Big Data Analytics programmes are expected to develop careers in scientific research, the internet-based industry and other professional areas that require big data analytics skills.

Recent career destinations for this degree

  • CEO (Chief Executive Officer), Hoxton Analytics
  • Software Engineer, China Mobile
  • Computer Science Lecturer, Singapore Polytechnic
  • Software Developer, Barclays
  • Software Engineer, UCL

Employability

The MSc has a unique industry connection as almost all our lecturers have industry experience. Through long-term collaborations with big players in the field such as Google, Microsoft and BT, research is driven by the fundamental technical challenges faced by the industry. Throughout the degree, our students have the chance to interact with our industry collaborators and previous students, and have placement opportunities to address the specific technical problems faced by the industry.

Why study this degree at UCL?

UCL Computer Science is recognised as a world leader in teaching and research.

UCL received the highest percentage (96%) for quality of research in Computer Science and Informatics in the UK's most recent Research Excellence Framework (REF2014).

Our Master's programmes have some of the highest employment rates and starting salaries, with graduates entering a wide variety of industries, from entertainment to finance.

We take an experimental approach to our subject, enjoy the challenge and opportunity of entrepreneurial partnerships and place a high value on our extensive range of industrial collaborations.



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The MRes covers web-related technologies and big data analytics. It is intended for students with a general science and engineering background and is an ideal preparation for roles with some of the best employers in internet-related industries and areas requiring big data analytical skills. Read more

The MRes covers web-related technologies and big data analytics. It is intended for students with a general science and engineering background and is an ideal preparation for roles with some of the best employers in internet-related industries and areas requiring big data analytical skills.

About this degree

Students will gain a detailed knowledge and understanding of the fundamental principles and technological components of the World Wide Web, learning not only the latest web search and information retrieval technologies and their underlying computational and statistical methods, but also studying essential large-scale data analytics to extract insights and patterns from vast amounts of unstructured data.

Students undertake modules to the value of 180 credits.

The programme consists of two core modules (30 credits), either four optional modules (60 credits) or three optional and one elective module, and the research dissertation (90 credits).

Core modules

  • Investigating Research (15 credits)
  • Researcher Professional Development (15 credits)

Optional modules

Students must choose a minimum of 45 and a maximum of 60 credits of optional modules. Students may also choose up to 15 credits from electives.

  • Affective Computing and Human-Robot Interaction (15 credits)
  • Complex Networks and Web (15 credits)
  • Computer Graphics (15 credits)
  • Graphical Models (15 credits)
  • Information Retrieval and Data Mining (15 credits)
  • Machine Vision (15 credits)
  • Probabilistic and Unsupervised Learning (15 credits)
  • Statistical Natural Language Processing (15 credits)
  • Web Economics (15 credits)

Please note: the availability and delivery of modules may vary, based on your selected options.

A list of acceptable elective modules is available on the Departmental page.

Dissertation/report

All students undertake an independent research project which culminates in a substantial dissertation.

Teaching and learning

The programme is delivered through a combination of lectures, tutorials and seminars. Lectures are often supported by laboratory work with help from demonstrators. For the research project, each student liaises with their academic or industrial supervisor to choose a study area of mutual interest. Student performance is assessed by unseen written examinations, coursework and the research dissertation.

Careers

Graduates from UCL are keenly sought after by the world's leading organisations, and many progress in their careers to secure senior and influential positions. Graduates of our Web Science and Big Data Analytics programmes are expected to develop careers in scientific research, the internet-based industry and other professional areas that require big data analytics skills.

Recent career destinations for this degree

  • Software Developer, British Film Institute (BFI)
  • Software Developer, Geneity

Employability

The MRes has a unique industry connection as almost all our lecturers have industry experience. Through long-term collaborations with big players in the field such as Google, Microsoft and BT, their research is driven by the fundamental technical challenges faced by the industry. Throughout the degree, our students have the chance to interact with our industry collaborators and previous students, and have placement opportunities to address specific technical problems faced by the industry.

Why study this degree at UCL?

UCL Computer Science is recognised as a world leader in teaching and research. UCL received the highest percentage (96%) for quality of research in Computer Science and Informatics in the UK's most recent Research Excellence Framework (REF2014).

Our Master's programmes have some of the highest employment rates and starting salaries, with graduates entering a wide variety of industries, from entertainment to finance.



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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. Read more
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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MSc Business Analytics has been designed to help you gain the skills and qualifications needed to pursue a career in business analytics. Read more
MSc Business Analytics has been designed to help you gain the skills and qualifications needed to pursue a career in business analytics. Big data and business analytics are areas where employers are finding increasing difficulty in recruiting graduates with the right qualifications and skills. There is a growing demand for such roles but also a significant gap between current graduates’ analytical skills and employers’ needs. By completing this programme, you will improve your employability opportunities by gaining the expertise needed to analyse big data, improve decision-making and help companies gain a competitive advantage.

This programme will equip you with the quantitative skills needed to understand and engage with complex data as well as the analytical tools to drive business advantage. You will deepen your knowledge of business analytics, web analytics, data mining and management consultancy with a view to using that knowledge to improve the decision-making process in business.

Subject guide and modules

Core Modules
-Descriptive Analytics
-Decision Models
-Performance Analytics
-Effective Management Consultancy
-Data Mining and Web Analytics
-Applied Research
-Business Analytics in Practice
-Gamification in Business Decisions
-Professional Development Programme.

The programme then concludes with a dissertation project.

Learning, teaching and assessment

You will be assessed through a mixture of examinations and coursework. The taught element of the programme is then complemented by a substantial piece of research leading to the completion of a dissertation. You should ensure that your choice of elective modules is consistent with your intended dissertation topic area.

You will acquire skills in the following areas: giving presentations, team working, report writing, negotiation and IT skills.

Career opportunities

This programme will prepare you for a range of specialist careers as a consultant, data analyst, manager or business analyst. Modern businesses in the UK and worldwide have a great need for professionals with analytical planning and big data analysis skills.

Our international alumni ambassadors share their experiences of studying at Aston Business School with students all over the world who consider applying for a course at Aston. Feel free to contact our ambassadors if you have any questions about 'Aston Life', the Campus, the courses or living in the UK/Birmingham.

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Programme starts in September 2018. Modern businesses and organizations are increasingly involved in collecting and processing vast amounts of customer and operations data. Read more

Programme starts in September 2018

Modern businesses and organizations are increasingly involved in collecting and processing vast amounts of customer and operations data. The resulting (big) data are more and more seen as an important resource for businesses.

In the Data Science and Marketing Analytics programme, students focus on the tools and skills that are needed to analyze such (big) data in modern businesses and turn it into meaningful insights. In particular, Data Science and Marketing Analytics combines theory and practice from computer science, marketing, economics, and statistics, in such a way that the potential of big data can be exploited successfully to create greater value for the consumers and firms.

Careers

Data science has been dubbed the sexiest career of the 21st century, according to Harvard Business Review. Given the growing awareness of the possibilities of exploiting data science for marketing analytics in business, the data science skills acquired during the Data Science and Marketing Analytics programme are expected to provide graduates with excellent job prospects.

According to Trevor Hastie, the John A. Overdeck Professor of Statistics at Stanford University, it is all quite obvious: “Big data is everywhere - it drives web search, web advertising and quantitative finance, to name a few industries. Data Science plays a fundamental role in this new Economy. With its strong history in data modeling, Erasmus School of Economics is well poised to train a new generation of data scientists.

Data Science and Marketing Analytics graduates are therefore expected to have many job opportunities in various sectors of the economy such as (online) retailing, financial services, consulting, and health care. For example, many businesses and organizations are either setting up or expanding business analytics/customer analytics/marketing analytics units. The combination of marketing and economic knowledge with data science skills will be of great value to our graduates and the companies that hire them.  

Download the brochure here.



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With the rapid development of smart sensors, smartphones and social media, "big" data is ubiquitous. Read more

With the rapid development of smart sensors, smartphones and social media, "big" data is ubiquitous. This new MSc teaches the foundations of GIScience, database, spatial analysis, data mining and analytics to equip professionals with the tools and techniques to analyse, represent and model large and complex spatio-temporal datasets.

About this degree

Students will be equipped with computational foundations and skills needed for big data analytics including visualisation, prediction, clustering and simulation with statistical and machine learning approaches, as well as retrieving and mining big (open) data, web services and cloud computing, web and mobile applications, by practising with real case data and open software.

Students undertake modules to the value of 180 credits.

The programme consists of four core modules (60 credits), four optional modules (60 credits) and a dissertation/report (60 credits).

A Postgraduate Diploma, four core modules (60 credits), two optional modules (60 credits), full-time nine months is offered.

Core modules

  • GIS Principles and Technology
  • Principles of Spatial Analysis
  • Spatial Databases and Data Management
  • Spatio-temporal Analysis and Data Mining

Choose four options from the following:

  • Introductory Programming
  • Complex Networks and Web
  • Group Mini project: digital Visualisation (requires basic Java)
  • Mapping Science
  • Supervised Learning (requires Applied Machine Learning)
  • Web Mobile GIS
  • Information Retrieval & Data Mining (requires Introductory Programming)
  • Applied Machine Learning (requires Introductory Programming)

Dissertation/report

All students undertake an independent research project which culminates in a dissertation of 15,000 words.

Teaching and learning

The programme is delivered through a combination of lectures, seminars, and laboratory practicals. Assessment is through examination, coursework, practicals, dissertation, and poster presentation.

Further information on modules and degree structure is available on the department website: Spatio-temporal Analytics and Big Data Mining MSc

Funding

For a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the Scholarships and Funding website.

Careers

Graduates from this programme are expected to find positions in consultancy, local government, public industry, and the information supply industry, as well as in continued research. Possible career paths could include: data scientist in the social media, finance, health, telecoms, retail or construction and planning industries; developer of spatial tools and specialised spatial software; researcher or entrepreneur.

Employability

Graduates will be equipped with essential principles and technical skills in managing, modelling, spatial and spatial-temporal analysis, visualising and simulating "big" spatio-temporal data, with emphasis on real development skills including: Java, JavaScript, Python and R. Business Intelligence (BI) skills will also be taught via practical case studies and close collaborations with leading industrial companies and institutions. All these skills are highly valued in big data analysis.

Why study this degree at UCL?

As one of the world’s top universities, UCL excels across the physical and engineering sciences, social sciences and humanities.

Spanning two UCL faculties, this interdisciplinary programme exploits the complementary research interests and teaching programmes of three departments (Civil, Environmental & Geomatic Engineering, Computer Science, and Geography).

Students on the Spatio-Temporal Analytics and Big Data Mining programme will be part of a vibrant, enthusiastic, and international research environment in which collaboration and free-ranging debate are strongly encouraged. This is supported by weekly research seminars and industrial seminars from top employers in the field.



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IN BRIEF. MSc by project accredited by the British Computer Society. Gain hands-on experience of the design and implementation of databases and web applications. Read more

IN BRIEF:

  • MSc by project accredited by the British Computer Society
  • Gain hands-on experience of the design and implementation of databases and web applications
  • Learn data-mining techniques using popular tools in different application domains
  • Part-time study option
  • International students can apply

COURSE SUMMARY

This course is your opportunity to specialise in the development of web-based software systems that use databases. During your time with us, you will gain a critical awareness of the methodologies, tools and techniques used for the development of web-based computer systems and an advanced understanding of the techniques used for the development, evaluation and testing of databases.

The course also develops an awareness of the latest developments in the field of advanced databases, data mining and data warehousing. You will also gain substantial knowledge and skills in the deployment of SAS business intelligence software leading towards SAS data miner accreditation, and learn what the Semantic Web and Linked Data are, together with what these technologies enable.

COURSE DETAILS

This course covers a very comprehensive range of topics split in to four large modules worth 30 credits each plus the MSc Project. External speakers from blue-chip and local companies will give seminars to complement your learning, that will be real-world case studies related to the subjects you are studying in your modules. These are designed to improve the breadth of your learning and often lead to ideas that you can develop for your MSc Project.

TEACHING

Teaching on this course takes the form of lectures, individual and group class work, topical class discussions and critical case study evaluation.

You will gain hands-on lab experience of using and setting up databases and web-based systems. What’s more, tutorials will give you practice in solving the theoretical and design problems associated with these systems.

ASSESSMENT

  • Coursework 60%
  • Examinations 40%

EMPLOYABILITY

With this qualification, you’ll be equipped as web/database designer and programmer, data analytics and miner among other roles. Your experience will be in high demand across all industrial and commercial sectors.

Previous students have gone on to work with companies including British Airways, Google, Hewlett-Packard, Oracle and other IT firms.

LINKS WITH INDUSTRY

Our links with industry include large companies (BT, Oracle, Microsoft) and local companies.

These companies engage with the University by giving guest seminars and often our students will work with them on their MSc Project.

FURTHER STUDY

Many of our graduates will go on to further study in our Computer Networks and Telecommunications Research Centre (CNTR)

The CNTR undertakes both pure and applied research in the general field of telecommunications and computer networking including computer networking technologies, wireless systems, networked multimedia applications, quality of service, mobile networking, intelligent buildings, context driven information systems and communication protocols. Much of this work is funded through research grants and supported by industry. In addition, members of the group are actively involved in a range of public engagement courses which aim to raise the awareness of these subjects for the general public and in schools.

Research themes in this Centre include:

  • Wireless technologies and sensor networks
  • Context and location based information systems
  • Intelligent buildings and energy monitoring
  • Communication protocols, traffic routing and quality of service
  • Network planning, traffic modelling and optimisation
  • Ubiquitous and ambient technology
  • Information security and computer forensics
  • Public Awareness


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This exciting and challenging programme studies how data can be utilised to solve major business and societal challenges. The programme provides students with the knowledge, technical ability and skills for leadership roles in the fields of business analytics and data science. Read more

This exciting and challenging programme studies how data can be utilised to solve major business and societal challenges. The programme provides students with the knowledge, technical ability and skills for leadership roles in the fields of business analytics and data science.

About this degree

The programme is designed to give students multidisciplinary skills in computing (i.e. programming, big data), analytics (i.e. data mining, machine learning, computational statistics, complexity), and business analysis. Emphasis will be on business problem framing, leveraging data as a strategic asset, and communicating complex analytical results to stakeholders.

Students undertake modules to the value of 180 credits.

The programme consists of three core modules (45 credits), four or five optional modules (60 to 75 credits), up to one elective module (15 credits) and a dissertation (60 credits).

Core modules

  • Business Strategy and Analytics (15 credits)
  • Data Analytics (15 credits)
  • Programming for Business Analytics (15 credits)

Optional modules

Students must choose a minimum of 60 and a maxuimum of 75 credits from Optional modules. A maximum of 15 credits may be taken from Electives.

  • Consulting Psychology (15 credits)
  • Consumer Behaviour (15 credits)
  • Data Science for Spatial Systems (15 credits)
  • Decision and Risk (15 credits)
  • Decision and Risk Analysis (15 credits)
  • Group Mini Project: Digital Visualisation (30 credits)
  • Introduction to Machine Learning (15 credits)
  • Mastering Entrepreneurship (15 credits)
  • Statistical Design of Investigations (15 credits)
  • Statistical Models and Data Analysis (15 credits)
  • Talent Management (15 credits)
  • Urban Simulation (15 credits)
  • Web Economics (15 credits)

Please note: the availability and delivery of optional modules may vary, depending on your selection.

A list of acceptable elective modules is available on the Departmental page.

Dissertation/report

During the summer students will undertake a work placement with a UCL industrial partner. The research and data analysis conducted during this placement will form the basis of a 10,000-word dissertation.

Teaching and learning

The programme is delivered through a combination of lectures by world-class academics and industry leaders, seminars, workshops, tutorials and project work. The programme comprises two terms of taught material, followed by examinations and then a project. Assessment is through unseen written examinations, coursework and the dissertation. 

Further details are available on UCL Computer Science website.

Further information on modules and degree structure is available on the department website: Business Analytics (with specialisation in Computer Science) MSc

Careers

Graduates of UCL Computer Science are particularly valued due to the department's international status and strong reputation for leading research. Recent graduate destinations include such companies as: IBM, Samsung, Microsoft, Price Waterhouse Coopers, Citibank.

Employability

This programme is designed to satisfy the need, both nationally and internationally, for exceptional data scientists and analysts. Graduates will be highly employable in global companies and high-growth businesses, finance and banking organisations, major retail and service companies, and consulting firms. They will be equipped to influence strategy and decision-making, and be able to drive business performance by transforming data into a powerful and predictive strategic asset. We expect our graduates to progress to leading and influential positions in industry.

Why study this degree at UCL?

UCL Computer Science is a global leader in research in experimental computer science. The department scored highest among UK universities for the quality of research in Computer Science and Informatics in the Research Excellence Framework (REF2014), with 96% regarded as 'world-leading' or 'internationally excellent'.

The department consists of a team of world-class academics specialising in big data, computational statistics, machine learning and complexity.

The programme aims to create the next generation of outstanding academics and industry pioneers, who will use data analysis to deliver real social and business impact.

Research Excellence Framework (REF)

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

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

96% rated 4* (‘world-leading’) or 3* (‘internationally excellent’)

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



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Our MSc Big Data Analytics programme is designed to provide students with in-depth knowledge of the new field of big data analytics from a computing perspective. Read more
Our MSc Big Data Analytics programme is designed to provide students with in-depth knowledge of the new field of big data analytics from a computing perspective. Data is being generated on an exponential scale by individuals and organisations. Valuable insights can be drawn from this data to inform strategic decisions, resulting in increased market share, profitability, possible cost savings and procedural efficiency. You will develop a critical understanding of the contemporary tools, techniques and models used for big data analytics.

The programme will enable you to develop practical skills, using tools and techniques from the forefront of business computing, and use these effectively to conduct big data analytics. It also seeks to promote an awareness of the moral, ethical and professional framework, within which you will operate as an IT professional in a business environment.

A key aspect of the programme philosophy is that the learning experience tightly integrates the use of Oracle commercial software (a world leader in this field), with investigation of the wider theoretical context. You will also learn about the skills needed to become a successful entrepreneur in the IT sector.

Why choose us?

-Our course is accredited by the British Computer Society, ensuring our course is fresh and relevant.
-The University is one of Oracle’s university-based academies, as well as being a member of UK Oracle User Group.
-This is the only big data analytics programme developed in partnership with Oracle, which is a major global leading IT vendor in the field.
-Previous graduates have progressed into roles with established companies such as Hewlett Packard, BT, Capgemini, Cisco, IBM and more.

Course breakdown

The MSc programme is normally studied over one year full-time or two years part-time (one year and one term full-time for January start). You may move between full and part-time modes of attendance. The course is divided into taught modules of 20 credits and a Masters project of 60 credits. Students complete 60 credits for Postgraduate Certificate, 120 credits for Postgraduate Diploma and 180 credits for the full MSc. Each credit represents 10 notional hours of student learning and assessment. The structure of the course, the module, levels and credit ratings and the awards that can be gained are shown below.

A range of assessment methods are employed, assessment criteria being published in each assignment brief. Knowledge and skills are assessed, formatively and summatively, by a number of methods: coursework, examinations (seen and unseen, open and closed-book), presentations, practical assignments, vivas, online forums, podcasts and project work.

Modules
-Research Methods and Project Management 20 credits
-Applied Statistics 20 credits
-Databases for Enterprise 20 credits
-Big Data Management 20 credits
-Data Mining 20 credits
-Web/Social Media Analytics and Visualisation 20 credits
-Master’s Project 60 credits

Enhancing your employability

This course is suitable for undergraduates and those who have worked in the industry but do not have the recognised qualifications. Students will be provided with the opportunity to complete industry-recognised Oracle Professional Certification.

The school boasts graduates who have gone on to work for Hewlett Packard, Bell Micro, Birmingham City Council, BT, Cap Gemini, Cisco, Deloitte, Ericsson, Fujitsu, IBM, Intel Corporation, NHS, Motorola, National Express, NEC, Royal Mail, Shell IT, JP Morgan Chase and Co, Carillion plc, Siemens and Nokia and many more.

You will also be provided with the opportunity to complete industry recognised Oracle Professional Certification.

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Are you looking to complement your undergraduate studies with a business-focused master’s degree that will enhance your employability? Do you want to explore… Read more
Are you looking to complement your undergraduate studies with a business-focused master’s degree that will enhance your employability? Do you want to explore the latest techniques for analysing ‘big data’ in order to improve an organisation’s decision making? This course develops broad business skills while also offering a specialist pathway in business analytics that starts after the first semester.

Specialist modules cover topics like business intelligence and marketing metrics. The course culminates in either a master’s dissertation or, if you prefer, a consultancy project where you’ll tackle an issue faced by a real client. Throughout the course there’s a focus on self-development and employability.

There is no requirement to have studied business or business analytics at undergraduate level.

The course is covered by the prestigious AACSB accreditation for Newcastle Business School, which was ‘Business School of the Year’ at The Times Higher Education Awards 2015.

This course can also be studied over 2 years full time (with a year abroad) - for more information, please view this web-page:
https://www.northumbria.ac.uk/study-at-northumbria/courses/business-with-business-analytics-with-study-abroad-msc-dtybba6/

Learn From The Best

Newcastle Business School has a global reputation for delivering some of the best business management education in the UK. We are part of an elite group of less than 1% of business schools worldwide with double accreditation from the Association to Advance Collegiate Schools of Business (AACSB) in business and accounting.

Our staff are actively pushing at the frontiers of knowledge and generating new concepts and insights. Over 40% of our publication outputs and 60% of our impact case studies have been assessed as internationally excellent or world leading. The quality of our research, teaching and engagement with business were among the factors that led to Newcastle Business School being named ‘Business School of the Year’ at the Times Higher Education Awards 2015.

Teaching And Assessment

Your tutors will use a variety of teaching methods including lectures, seminars and workshops. As this is a master’s course there is a major element of independent learning and self-motivated reflection.

Teaching is backed up by a well-designed support system that helps ensure a successful learning journey. We make sure that extensive feedback, from both tutors and peers, is built into the course.

Our assessment strategy is based on our understanding that everyone has different needs, strengths and enthusiasms. Assessment is based on course work and our methods will include essays, reports, group work and presentations. The master’s dissertation or consultancy project will form a major part of the assessment.

Learning Environment

Newcastle Business School provides first-class teaching in a world-class environment. From social spaces and hub areas to lecture theatres and exhibition spaces, our facilities are exceptional. The University’s library was ranked #2 in the UK in the Times Higher Education Student Experience Survey for 2015.

The University has also invested heavily in IT labs and facilities. You’ll use software such as ARIS Express Business Process Modelling, various SAS applications, Microsoft Project, specialist decision-making software, and Google Analytics.

Technology Enhanced Learning (TEL) is embedded throughout the course with tools such as the ‘Blackboard’ eLearning Portal and electronic reading lists that will guide your preparation for seminars and independent research. Our use of lecture capture software will help you revise challenging material.

There will be plenty of opportunities to put your learning into practice. The Student Engagement Centre promotes all types of experiential learning including volunteering, internships and placements. The Business Clinic enables our students to participate in a ‘consultancy firm’ to provide advice for our region’s businesses.

Research-Rich Learning

As a master’s student you’ll develop your research skills to a new, higher level. Your research supervisor will help you submit a proposal for your 15,000-word dissertation or your master’s consultancy project. We’ll support you in the development and completion of the dissertation/project.

If you decide on a master’s consultancy project you’ll be expected to show a deep understanding of the issues that are involved in the client brief. It’ll be essential to undertake primary and desk research combined with reading and reflection.

Throughout your course you’ll be an active participant in the on-going research agenda that’s at the heart of Newcastle Business School. With conferences and research events regularly taking place, and with staff discussing their own research as it relates to the topics you’ll study, there’s a strong emphasis on engaging in up-to-date enquiry-based learning.

Give Your Career An Edge

The course includes two modules that are focused on developing global management competencies. Topics during these modules include emotional intelligence, cultural awareness and the ability to work in diverse groups and teams, as well as project management and decision making.

A further module, ‘Academic and Professional Development’, has a specific focus on self-development. It includes formal sessions with our Careers and Employment Service which offers a range of workshops, one-to-one advice, and networking opportunities.

The master’s consultancy project offers an (optional) opportunity to develop practical experience. You’ll work in a small group, typically no more than five people, and tackle a live project from a host organisation under the mentorship of a member of our academic team. The project will require you to link theory to practice while simultaneously honing your employability skills.

Your Future

Our graduates typically go into professional and graduate management positions and, by the end of the course, you’ll be well-equipped to follow them. Thanks to the specialist modules – Business Intelligence, Marketing Metrics and Analysis, and the dissertation/consultancy project – you’ll have a particular edge in areas related to business analytics, including market research, digital marketing and consulting.

If you decide to start up your own business, it’s good to know that the combined turnover of our graduates’ start-up companies is higher than that of any other UK university.

Whatever you decide to do, you’ll have the transferable skills that employers expect from a master’s graduate from Northumbria University. These include the ability to tackle complex issues through conceptualisation and undertaking research, the ability to contribute to new processes and knowledge, and the ability to formulate balanced judgements when considering incomplete or ambiguous data.

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COURSE OVERVIEW. Practical, hands-on course with live briefs and workplace visits. Ideal for careers in social media management, SEO, and e-commerce. Read more

COURSE OVERVIEW

  • Practical, hands-on course with live briefs and workplace visits
  • Ideal for careers in social media management, SEO, and e-commerce
  • Opportunities for internships, fieldwork and engagement with industry experts

Digital Marketing and Analytics at Winchester advances your knowledge and skills in creating digital content, helping you to ensure your target audience sees and responds. The course also refines your skills in using data analytics, equipping you to develop and use appropriate digital marketing strategies to reach consumers, clients and partners.

You gain an overview of the evolution of marketing and the impact of digital technologies on the theory and practice of marketing, evaluate consumer behaviour models applied to the digital consumer, and monitor changing trends in various industries. You also develop integrated digital marketing communication plans and gain a critical understanding of how to mix traditional and new marketing research tools to obtain relevant and meaningful data. The course also covers the development and management of websites, with incorporated blogs, and how to use social media as a marketing communications tool.

Modules include Digital Consumer Trends, Integrated Digital Marketing Communications Web Design and Analytics and Social Media Marketing and Analytics. For the final dissertation/consultancy project, you are given a live brief from an external organisation facing digital marketing-related issues. You collate, analyse and interpret qualitative and quantitative data to identify issues and provide a report with a set of realistic recommendations and solutions. As you learn the practical skills required for success in current and future business environments, there is extensive interaction with industry experts and there are optional, non-credit bearing, fieldwork and internship opportunities. Throughout the course, you are provided with live briefs from businesses facing issues currently or with recent case studies.

The programme makes extensive use of industry experts and practitioners as visiting speakers in order to enhance the currency and relevance of the topics discussed in each module. Module tutors adopt practical forms of study such as workshops and workplace visits wherever possible.

Graduates enter roles in marketing, customer relationship management, pay-for-click, e-commerce, search engine optimisation, digital account management, web design, copyrighting and social media management.

Careers

Graduates enter roles within marketing, customer relationship management, pay-per-click, e-commerce, search engine optimisation, digital account management, web design, copywriting and social media management.

ABOUT THIS COURSE

Suitable for applicants from:

UK, EU, World

Learning and teaching

The programme makes extensive use of industry experts and practitioners as visiting speakers in order to enhance the currency and relevance of the topics discussed in each module. Module tutors are encouraged to move away from traditional lecture and seminar delivery modes and to adopt practical forms of study such as workshops and workplace visits wherever possible. Students are provided with live briefs from businesses facing issues currently or recent case studies.

Location

Taught elements of the course take place on our King Alfred Campus (Winchester) or at our West Downs Campus (Winchester)

Start date: September

Teaching takes place: Daytime

Assessment

Our validated courses may adopt a range of means of assessing your learning. An indicative, and not necessarily comprehensive, list of assessment types you might encounter includes essays, portfolios, supervised independent work, presentations, written exams, or practical performances.

We ensure all students have an equal opportunity to achieve module learning outcomes. As such, where appropriate and necessary, students with recognised disabilities may have alternative assignments set that continue to test how successfully they have met the module's learning outcomes. Further details on assessment types used on the course you are interested in can be found on the course page, by attending an Open Day or Open Evening, or contacting our teaching staff.

Feedback

We are committed to providing timely and appropriate feedback to you on your academic progress and achievement in order to enable you to reflect on your progress and plan your academic and skills development effectively. You are also encouraged to seek additional feedback from your course tutors.

Further information

For more information about our regulations for this course, please see our Academic Regulations, Policies and Procedures.



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This course addresses the need to propel information-gathering and data organisation, and exploit potential information and knowledge hidden in routinely collected data to improve decision-making. Read more
This course addresses the need to propel information-gathering and data organisation, and exploit potential information and knowledge hidden in routinely collected data to improve decision-making. The course, which builds on the strength of two successful courses on data mining and on decision sciences, is more technology focused, and stretches the data mining and decision sciences theme to the broader agenda of business intelligence.

You will focus on developing solutions to real-world problems associated with the changing nature of IT infrastructure and increasing volumes of data, through the use of applications and case studies, while gaining a deep appreciation of the underlying models and techniques. You will also gain a greater understanding of the impact technological advances have on nature and practices adopted within the business intelligence and analytics practices, and know how to adapt to these changes.

Course content

Embedded into the course are two key themes. The first will help you to develop your skills in the use and application of various technologies, architectures, techniques, tools and methods. These include warehousing and data mining, distributed data management, and the technologies, architectures, and appropriate middleware and infrastructures supporting application layers. The second theme will enhance your knowledge of algorithms and the quantitative techniques suitable for analysing and mining data and developing decision models in a broad range of application areas. The project consolidates the taught subjects covered, while giving you the opportunity to pursue in-depth study in your chosen area.

Teaching approaches include lectures, tutorials, seminars and practical sessions. You will also learn through extensive course work, class presentations, group research work, and the use of a range of industry standard software such as R, Python, Simul8, Palisade Decision Tools, Hadoop and Oracle.

Taught modules may be assessed entirely through course work, or may include a two-hour exam at the end of the year.

Modules

The following modules are indicative of what you will study on this course.

Core modules
-BIG DATA THEORY AND PRACTICE
-BUSINESS ANALYTICS
-DATA MINING AND MACHINE LEARNING
-RESEARCH METHODS AND PROFESSIONAL PRACTICE
-BUSINESS SYSTEMS POSTGRADUATE PROJECT

Option modules
-ADVANCED BIG DATA ANALYTICS
-BUSINESS OPTIMISATION
-DATA VISUALISATION AND DASHBOARDING
-DATA WAREHOUSING AND OLAP
-DATA REPOSITORIES PRINCIPLES AND TOOLS
-SIMULATION MODELLING: RISK, PROCESSES, AND SYSTEMS
-WEB AND SOCIAL MEDIA ANALYTICS

Associated careers

Graduates can expect to find employment as consultants, decision modelling or advanced data analyst, and members of technical and analytics teams supporting management decision making in diverse organisations. Typical employers include local authorities, PLCs (such as GlaxoSmithKline, Prudential, Santander and Unilever), public sector organisations (such as the NHS and primarily care trusts), retail head offices, the BBC, the Civil Service and the host of banks, brokers and regulators that makeup the city, along with all the specialist support consultancies in IT and market research and forecasting, all of the whom us data for the full range of decision making.

Professional recognition

This course is accredited by the British Computer society for partial fulfilment of the academic requirement for Chartered IT professional.

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The Master of Science in Big Data Analytics for Business is a unique program that trains business professionals in the field of (online) marketing, finance, and operations. Read more

The Master of Science in Big Data Analytics for Business is a unique program that trains business professionals in the field of (online) marketing, finance, and operations.

Students are exposed to the leading-edge fundamentals in decision-making by extracting knowledge from Big Data, including social media data, customer web traffic data, Bloomberg’s financial data, and inventory process logs.

Students will learn to solve managerial problems by critically asking questions in the spirit of ‘What do we know?’ (Data driven) rather than ‘What do we think? (Gut feeling).

Program Advantages:

- Introduction of leading tools that convert data to knowledge

- Possibility to obtain business-relevant certificates

- Exposure to both academic and applied industry research

Career Opportunities:

- Digital/Web Analyst

- Customer Analyst

- Data Scientist

- Credit Risk Analyst

This program is under the process of being accredited with the Université Catholique de Lille as diplôme universitaire and with the Conférence des Grandes Ecoles.

Program

The Master of Science in Big Data Analytics for Business offers core modules in business, technology, and methodology as well as specialized modules in marketing, finance, and operations.

These modules will be covered over two semesters and the students will take their newfound knowledge and apply it in a professional environment during a 4 – 6 month internship.

Internship -

Students acquire real-life experience through a 4 – 6 month internship in France, or anywhere in the world.

The objective is to provide an opportunity where MSc in Big Data Analytics for Business students learn how to approach assignments and working relationships in a professional environment. They can apply their newfound knowledge in real world situations while receiving guidance and feedback from managers and colleagues.

New contacts made during their internships help create their professional networks.

French language classes -

French language lessons are mandatory for non-Francophone international students. Francophone students may choose German, Italian, Chinese, or Spanish.

Admission & Fees

The MSc in Big Data and Analytics for Business is for students with a bachelor’s degree with a quantitative component or business administration interested in a new and expanding field.

Admission requirements -

The program is open to candidates with a bachelor’s degree from a recognized university with good academic performance and a good command of English.

Native English speakers or students who have had two years of courses taught in English are exempt. A GMAT score is optional, not mandatory.

No prior knowledge of French is needed; however French language classes are mandatory for non-French speakers as part of the program.

Application process -

The application process is based on students’ online application available at https://application.ieseg.fr/ and review of the required documents.

Rolling admission is offered from October 2017.

Checklist requirements:

- Online application form

- Transcripts and diploma translated into English or French if necessary

- English proficiency test (IELTS 6.5 TOEFL IBT 85, TOEIC 800) if required

- CV / Resume

- Copy of passport

- 80€ application fee

Tuition 2017-2018:

- € 15,000 for domestic and international students

- International merit-based scholarships are available

Funding and scholarship-

IÉSEG has a merit-based International Scholarship Program with a tuition waiver of 15 to 50% per year. Selection is based on the applicant’s previous academic performance and overall application portfolio.

The scholarship application is automatic; students do not need to apply separately.

All international students are encouraged to check with Campus France and their own government to see if there are any scholarships available. For American students please check with Sallie Mae for private loan options.



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