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Masters Degrees (Data Visualization)

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Train to become a data analyst in a growing industry by studying techniques such as data mining, statistical modelling, business intelligence and data visualisation. Read more
Train to become a data analyst in a growing industry by studying techniques such as data mining, statistical modelling, business intelligence and data visualisation. Study on a course which has been developed with direct input from industry experts who will bring real life business case scenarios to you.

More about this course

This specialist advanced course will equip students with the theoretical, technical and practical data analytics competencies required in an area of economic growth. The course curriculum content has been developed with direct input from industry experts and utilises specialist software tools and techniques. Students’ experience of the course will be enriched with exposure to real life business case scenarios brought to them by skilled professionals in industry.

The specialist nature of the course will allow students to explore and experience advanced techniques in data science. Students will acquire practical skills, often first-hand from an external practitioners, preparing them for employment as data analysts. Students will also be trained in the use of software tools and environments currently used by the industry sector. For example, students on this course will have exposure to R and Python programming, IBM SPSS, SAS®, Tableau, Oracle and Hadoop.

A range of assessment methods are used on the course, including written reports, practical and research assignments, demonstrations, presentations, group work and examinations.

Modular structure

The modules listed below are for the academic year 2016/17 and represent the course modules at this time. Modules and module details (including, but not limited to, location and time) are subject to change over time.

Year 1 modules include:
-Data Analysis and Visualization (core, 20 credits)
-Data Mining for Business Intelligence (core, 20 credits)
-Data Modelling and OLAP Techniques for Data Analytics (core, 20 credits)
-MSc Project (core, 60 credits)
-Programming for Data Analytics (core, 20 credits)
-Statistical Modelling and Forecasting (core, 20 credits)
-Financial Mathematics (option, 20 credits)
-Work Related Learning (option, 20 credits)

After the course

On completion of the course graduates will be well equipped to work in some of the fastest growing sectors of the data science and big data industries. The course offers wide-ranging career opportunities in the commercial industry, public and financial services, especially in areas requiring big data analysis such as consumer, healthcare, scientific, financial, security intelligence, business and social sciences.

Job roles include data scientist, data analyst, digital analyst, big data consultant, statistical analyst and data modeller. Graduates will be eligible to work as data analysts or data scientists in a multitude of areas where skills such as R or Python programming, machine learning and statistical modelling, SAS® and SPSS experience, data visualisation and data-driven decision-making are required.

The course also provides an excellent basis for further study for those wishing to pursue a higher-level research degree or embark on an industry-based research career.

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

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

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

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

Career Prospects

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

Growing need for Data Scientists

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

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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. Read more

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-recognised Institutions

Ecole Polytechnique and HEC Paris are both world leading academic institutions, renowned for the quality of their degrees, faculties and research (see HEC 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 Data Science 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 the 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

The key aim of the teaching in this Joint Degree is to provide students with the tools needed to solve real problems, using structured and unstructured data masses, teaching them to ask the ‘right’ questions (both from statistics and ‘business’ perspectives), to use the appropriate mathematical and IT tools to answer these questions.

Students will be equipped to shift constantly from data to knowledge, from knowledge to strategic decision, and from strategic decision to operational business implementations.

All these shifts carry with them numerous challenges that each require an interdisciplinary approach involving mathematics, IT, business strategy, and management skills.



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Studentships. * One-year masters studentships are available for this stream. Each studentship will be worth £5000 and can be taken either as a reduction in fees or as a bursary. Read more

Studentships

* One-year masters studentships are available for this stream. Each studentship will be worth £5000 and can be taken either as a reduction in fees or as a bursary. Studentships will be awarded based on academic merit and are open to all applicants, regardless of fee status (home/EU/overseas). Please indicate 'Data Science' in the first line of your personal statement.

* Two PhD Studentships targeted at successful graduates from this stream. Two 3-year PhD studentships will be on offer, targeted at students obtaining a minimum of a Pass with Merit on the Data Science stream. These studentships will cover the cost of tuition fees for home/EU applicants and a stipend at standard Research Council rates.

Stream overview

This course is a stream within the broader MRes in Biomedical Research.

The Data Science stream provides an interdisciplinary training in analysis of ‘big data’ from modern high throughput biomolecular studies. This is achieved through a core training in multivariate statistics, chemometrics and machine learning methods, along with research experience in the development and application of these methods to real world biomedical studies. There is an emphasis on handling large-scale data from molecular phenotyping techniques such as metabolic profiling and related genomics approaches. Like the other MRes streams, this course exposes students to the latest developments in the field through two mini-research projects of 20 weeks each, supplemented by lectures, workshops and journal clubs. The stream is based in the Division of Computational and Systems Medicine and benefits from close links with large facilities such as the MRC-NIHR National Phenome Centre, the MRC Clinical Phenotyping Centre and the Centre for Systems Oncology. The Data Science stream is developed in collaboration with Imperial’s Data Science Institute.

Who is this course for?

Students with a degree in physical sciences, engineering, mathematics computer science (or related area) who wish to apply their numeric skills to solve biomedical problems with big data.

Stream Objectives

Students will gain experience in analysing and modelling big data from technologically advanced techniques applied to biomedical questions. Individuals who successfully complete the course will have developed the ability to:

• Perform novel computational informatics research and exercise critical scientific thought in the interpretation of results.

• Implement and apply sophisticated statistical and machine learning techniques in the interrogation of large and complex

biomedical data sets.

• Understand the cutting edge technologies used to conduct molecular phenotyping studies on a large scale.

• Interpret and present complex scientific data from multiple sources.

• Mine the scientific literature for relevant information and develop research plans.

• Write a grant application, through the taught grant-writing exercise common to all MRes streams.

• Write and defend research reports through writing, poster presentations and seminars.

• Exercise a range of transferable skills by taking short courses taught through the Graduate School and the core programme of the

MRes Biomedical Research degree.

Projects

A wide range of research projects is made available to students twice a year. The projects available to each student are determined by their stream. Students may have access from other streams, but have priority only on projects offered by their own stream. Example projects for Data Science include (but are not limited to):

• Integration of Multi-Platform Metabolic Profiling Data With Application to Subclinical Atherosclerosis Detection

• What Makes a Biological Pathway Useful? Investigating Pathway Robustness

• Bioinformatics for mass spectrometry imaging in augmented systems histology

• Processing of 3D imaging hyperspectral datasets for explorative analysis of tumour heterogeneity

• Fusion of molecular and clinical phenotypes to predict patient mortality

• 4-dimensional visualization of high throughput molecular data for surgical diagnostics

• Modelling short but highly multivariate time series in metabolomics and genomics

• Searching for the needle in the haystack: statistically enhanced pattern detection in high resolution molecular spectra

Visit the MRes in Biomedical Research (Data Science) page on the Imperial College London web site for more details!



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This postgraduate Masters course is uniquely designed for both computing and non-computing graduates wishing to pursue a career in data science community. Read more
This postgraduate Masters course is uniquely designed for both computing and non-computing graduates wishing to pursue a career in data science community.

Data science is at the intersection of the fields of computer science, statistics, and design. In a rapidly evolving world, new types of big data are emerging from mobile devices, sensors, instruments, transactional systems, web logs, social media, the cloud and other sources. Businesses are accumulating big data at a rate that often exceeds their capacity to extract value from it.

MSc Data Science is ideally placed to provide you with technical knowledge and employer-focused skills required in a data scientist role. The course will develop your specialist knowledge of data acquisition, data cleansing, data analysis, information extraction, prediction, visualization, story-telling and explanation.

You'll gain hands-on experience using industry standard tools for data science, business intelligence and analytics including SAS, Tableau MS SQL Server, Oracle Database, and R Programming.

Modules

Research methods and professional issues
Future internet technologies
Statistical analysis and modelling
Business intelligence
Data management
Machine learning
Data mining and analysis
MSc thesis

All modules are assessed by a mix of coursework and examinations.

Teaching and learning

You'll make use of our e-learning suite and learn in a combination of lectures, seminars, workshops and private study. You'll have access to specialist software including Microsoft SQL Server 2012, Netbeans 7.x with Java 7, Oracle, Python, SAS and Visual Paradigm.

Placements

You are encouraged to actively seek placements, work experience and voluntary work during your studies to improve your CV and to give you the opportunity to put theory into practice. Many opportunities are offered through the University's central Employability team, who can support you in finding a placement.

Accreditation

In order to ensure the course runs in accordance with industry recognised standards we are seeking accreditation for both Chartered Engineer (CEng) status as well as Chartered IT Professional (CITP) accreditation by the British Computer Society, the Chartered Institute for Information Technology.

We are also seeking Chartered Engineer (CEng) status with both the Institute of Engineering and Technology and the Engineering Council.

Employability

Career opportunities range from IT services to business consultancy, and this course will prepare you for a career in the business intelligence community working actively with a range of resources including tools from major commercial vendors such as Microsoft and SAS.

As a graduate of this course you should to be able to work within the areas of business intelligence or business and data analytics, in roles such as a business intelligence specialist, data or business analyst or business intelligence developer.

LSBU Employability Services

LSBU is committed to supporting you develop your employability and succeed in getting a job after you have graduated. Your qualification will certainly help, but in a competitive market you also need to work on your employability, and on your career search. Our Employability Service will support you in developing your skills, finding a job, interview techniques, work experience or an internship, and will help you assess what you need to do to get the job you want at the end of your course. LSBU offers a comprehensive Employability Service, with a range of initiatives to complement your studies, including:

• Direct engagement from employers who come in to interview and talk to students
• Job Shop and on-campus recruitment agencies to help your job search
• Mentoring and work shadowing schemes.

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

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

The MSc in High Performance and Scientific Computing is for you if you are a graduate in a scientific or engineering discipline and want to specialise in applications of High Performance computing in your chosen scientific area. During your studies in High Performance and Scientific Computing you will develop your computational and scientific knowledge and skills in tandem helping emphasise their inter-dependence.

On the course in High Performance and Scientific Computing you will develop a solid knowledge base of high performance computing tools and concepts with a flexibility in terms of techniques and applications. As s student of the MSc High Performance and Scientific Computing you will take core computational modules in addition to specialising in high performance computing applications in a scientific discipline that defines the route you have chosen (Biosciences, Computer Science, Geography or Physics). You will also be encouraged to take at least one module in a related discipline.

Modules of High Performance and Scientific Computing MSc

The modules you study on the High Performance and Scientific Computing MSc depend on the route you choose and routes are as follows:

Biosciences route (High Performance and Scientific Computing MSc):

Graphics Processor Programming

High Performance Computing in C/C++

Operating Systems and Architectures

Software Testing

Programming in C/C++

Conservation of Aquatic Resources or Environmental Impact Assessment

Ecosystems

Research Project in Environmental Biology

+ 10 credits from optional modules

Computer Science route (High Performance and Scientific Computing MSc):

Graphics Processor Programming

High Performance Computing in C/C++

Operating Systems and Architectures

Software Testing

Programming in C/C++

Partial Differential Equations

Numerics of ODEs and PDEs

Software Engineering

Data Visualization

MSc Project

+ 30 credits from optional modules

Geography route (High Performance and Scientific Computing MSc):

Graphics Processor Programming

High Performance Computing in C/C++

Operating Systems and Architectures

Software Testing

Programming in C/C++

Partial Differential Equations

Numerics of ODEs and PDEs

Modelling Earth Systems or Satellite Remote Sensing or Climate Change – Past, Present and Future or Geographical Information Systems

Research Project

+ 10 credits from optional modules

Physics route (High Performance and Scientific Computing MSc):

Graphics Processor Programming

High Performance Computing in C/C++

Operating Systems and Architectures

Software Testing

Programming in C/C++

Partial Differential Equations

Numerics of ODEs and PDEs

Monte Carlo Methods

Quantum Information Processing

Phase Transitions and Critical Phenomena

Physics Project

+ 20 credits from optional modules

Optional Modules (High Performance and Scientific Computing MSc):

Software Engineering

Data Visualization

Monte Carlo Methods

Quantum Information Processing

Phase Transitions and Critical Phenomena

Modelling Earth Systems

Satellite Remote Sensing

Climate Change – Past, Present and Future

Geographical Information Systems

Conservation of Aquatic Resources

Environmental Impact Assessment

Ecosystems

Facilities

Students of the High Performance and Scientific Computing programme will benefit from the Department that is well-resourced to support research. Swansea physics graduates are more fortunate than most, gaining unique insights into exciting cutting-edge areas of physics due to the specialized research interests of all the teaching staff. This combined with a great staff-student ratio enables individual supervision in advanced final year research projects. Projects range from superconductivity and nano-technology to superstring theory and anti-matter. The success of this programme is apparent in the large proportion of our M.Phys. students who seek to continue with postgraduate programmes in research.

Specialist equipment includes:

a low-energy positron beam with a highfield superconducting magnet for the study of positronium

a number of CW and pulsed laser systems

scanning tunnelling electron and nearfield optical microscopes

a Raman microscope

a 72 CPU parallel cluster

access to the IBM-built ‘Blue C’ Supercomputer at Swansea University and is part of the shared use of the teraflop QCDOC facility based in Edinburgh

The Physics laboratories and teaching rooms were refurbished during 2012 and were officially opened by Professor Lyn Evans, Project Leader of the Large Hadron Collider at CERN. This major refurbishment was made possible through the University’s capital programme, the College of Science, and a generous bequest made to the Physics Department by Dr Gething Morgan Lewis FRSE, an eminent physicist who grew up in Ystalyfera in the Swansea Valley and was educated at Brecon College.



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This one year MSc Data Science degree prepares you to become a proficient data scientist, building core areas of expertise, from the ability to operate high-performance computing clusters and cloud-based infrastructures, to devising and applying sophisticated Big Data analytics techniques. Read more

This one year MSc Data Science degree prepares you to become a proficient data scientist, building core areas of expertise, from the ability to operate high-performance computing clusters and cloud-based infrastructures, to devising and applying sophisticated Big Data analytics techniques.

Introducing your degree

This MSc programme will train students to become proficient data scientists.

You will gain advanced knowledge in areas such as data mining, machine learning, and data visualization, including state of the art techniques, programming toolkit, and industrial and societal application scenarios.

Overview

This programme prepares you to become a proficient data scientist, developing your specialist knowledge in subjects that are crucial for mastering the vast and ever-so-complex information landscape that is characteristic to modern, digitally empowered organisations.

This is typically linked to a number of core areas of expertise, from the ability to operate high-performance computing clusters and cloud-based infrastructures, to the know-how that is required to devise and apply sophisticated Big Data analytics techniques, and the creativity involved in designing powerful visualizations.

In the first semester you start with a review of key topics in data science. The course will introduce the core theoretical and technology components required to design and use a data science application, using open-source tools and openly accessible data sets. You will also cover the most important machine learning techniques, which are at the core of any attempt to analyse and reason about data.

You will be exposed to more advanced topics in data mining in the second semester, including feature engineering, methods to manipulate text and multimedia data, topic modelling, social network analysis, and spectral analysis. A new module on data visualization will introduce the most common types of visualization techniques and state-of-the-art technology used to build graphic elements into data science applications to present analytics results.

Finally, during the summer the MSc project enables you will demonstrate your mastery of specialist techniques, relevant methods of enquiry, and your ability to design and deliver advanced application, systems and solutions to a tight deadline, including the production of a substantial dissertation.

Career Opportunities

Data scientists help organisations handle large amounts of data being produced thanks to digital technologies. Harvard Business Review described the role as 'The Sexiest Job of the 21st Century' due to the rare combination of skills that a trained data scientist possesses.

Data science has seen an unparalleled expansion as the data-driven economy grows. Increasingly organisations require skilled professionals who can handle large datasets and managers who can utilise the resulting analysis to make impactful decisions.

There is a range of potential jobs available; demand for big data staff is predicted to rise 92% over 5 years from Jan 2013. The programme provides an excellent opportunity for entry into data sciences or similar fields. Plus, big data positions offer a median salary of £55,000 – 24% higher than for IT staff in general (UK). There are also academic possibilities for doctoral study, as there are for entrepreneurial careers.

ECS runs a dedicated careers hub with is affiliated with more than 100 renowned companies such as IBM, Arm, Microsoft, Samsung, and Google. Visit our Careers Hub for more information.

Graduates from our MSc program can seek employment worldwide in:

  • established companies looking to spot trends in sales, marketing or operational data;
  • start-ups based around new opportunities in the booming data-driven economy;
  • government departments looking to utilise linked open data to gain insights to affect policy at the highest levels;
  • research/consultancy companies analysing data and feeding back to the wider community, with training and specialist services to clients.

Through an extensive blend of networks, mentors, societies and our on-campus startup incubator, we also support aspiring entrepreneurs looking to build their professional enterprise skills. Discover more about enterprise and entrepreneurship opportunities.



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This programme provides students with the knowledge of cutting-edge methodologies, approaches and skills in the emerging field of data science and big data applications, including advanced software development, systems for big data analytics, statistical data analysis data mining, distributed systems, data privacy and security, and data visualization and exploration. Read more
This programme provides students with the knowledge of cutting-edge methodologies, approaches and skills in the emerging field of data science and big data applications, including advanced software development, systems for big data analytics, statistical data analysis data mining, distributed systems, data privacy and security, and data visualization and exploration.

The programme of study culminates in a dissertation, enabling you to bring what you have learnt together in a significant piece of project work.

In summary, the MSc Big Data Science and Technology offers you the opportunity to build your own path of study - from the advanced computing modules, the extended list of optional modules available, as well as the dissertation - so as to match your specific career aspirations in the area of big data and data science.

For more information on the part time version of this course, please view this web-page: http://www.brad.ac.uk/study/courses/info/big-data-science-and-technology-msc-part-time

Why Bradford?

This programme intends to equip graduates with the cutting-edge knowledge and skills to work in the industry as a Data Scientist, Big Data Architect, or Big Data Analyst.

MSc Big Data Science and Technology provides industry with graduates that are ready and able to develop solutions to address challenges for big data analytics and developing big data systems.

Modules

-Software Development
-Big Data Systems and Analytics
-Information Theory and Data Communication
-Security, Privacy and Data Protection
-Mobile Applications
-Statistical Data Analysis
-Data Mining
-Concurrent and Distributed Systems
-Data visualization
-Dissertation

Career support and prospects

The University is committed to helping students develop and enhance employability and this is an integral part of many programmes. Specialist support is available throughout the course from Career and Employability Services including help to find part-time work while studying, placements, vacation work and graduate vacancies. Students are encouraged to access this support at an early stage and to use the extensive resources on the Careers website.

Discussing options with specialist advisers helps to clarify plans through exploring options and refining skills of job-hunting. In most of our programmes there is direct input by Career Development Advisers into the curriculum or through specially arranged workshops.

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Why choose the MSc in Business Analytics?. Do you want to be a professional analyst who understand both the technologies and the business?. Read more

Why choose the MSc in Business Analytics?

  • Do you want to be a professional analyst who understand both the technologies and the business?
  • Do you want to master the skills in making data-driven business decisions?
  • Do you want to learn the practical use of data visualization tools, statistical analysis tools, and big data technologies?

What is business analytics?

Business Analytics is the intersection of management science and machine learning in real world applications.

It offers new potential to improve financial performance, strategic management and operational efficiency.

Business Analytics is an increasingly critical component in preparing organizations to solve 21st-century business challenges and support data driven decision making.

Programme overview

Our MSc Business Analytics programme is a one year, full-time programme consisting of 6 core modules, and 2 elective modules from a choice of 7 elective modules.

The core modules are conducted via lectures, tutorials, and computer laboratory sessions. Students undertake the dissertation project in Business Analytics in collaboration with one of our international industrial partners.

Graduates of the programme will have gained the necessary skills and knowledge in a range of fields, including business operation, database, statistics, informatics, data analytics, machine learning and big data technologies in real-world business contexts.

Applicants for this programme are required to have at least a second class honours in the first division or international equivalent in any discipline, including business and management, and at least 10 credits equivalent value with significant mathematical/statistical content (However, this course is not suitable for students who have previously studied a significant amount of business analytics).

Teaching and Learning

Our learning environment is highly interactive and innovative with student-centred learning activities.

Other than examinations, our students will be assessed via essays writing, practical exercises, group and individual projects, and oral presentations.

The dissertation focuses on developing students’ skills in applying analytic techniques, communicating and solving the data analytics problem.

Career options for this degree

The area of business analytics is growing in financial sectors, customer services, enterprise optimization, and consumer marketing.

When our students graduate, they will be able to:

  • Find a job in the business firms that require the knowledge of big data and advanced analytic techniques.
  • Study the organisations, management, and international external environments.
  • Gain business insights and professional skills in data mining, data visualization, data management, process modeling, predictive and advanced analytics.
  • Develop the ability to optimize the business processes and management practice.
  • Contribute to business and society at large.

What are the potential careers of our graduates?

  • Business intelligence analytics,
  • Marketing analyst
  • Business systems analyst
  • Data scientist
  • Business consultant
  • Solution Architects


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IMF Business School, in collaboration with the Camilo José Cela University, launches the Master in Business Analytics and Big Data. Read more

IMF Business School, in collaboration with the Camilo José Cela University, launches the Master in Business Analytics and Big Data. This program aims to provide students with a global view of Big Data technologies and their use, as well as applied and practical training in Business Analytics. IMF is a member of the Association of Computer Technicians (ATI).

This Master's degree is aimed at both new graduates and experienced professionals who wish to focus on the new professions related to data analysis (Data Analyst, Data Scientists, Chief Data Officer, Data Engineer ...). The recommended access profiles are those related to ICTs, careers with a high qualitative component, and careers in business and economics.

The Master's Degree in Big Data of IMF, of an academic year of duration, is taught in online mode supported by an advanced technological platform that allows the student to access the study, regardless of geographical location or time availability.

With the IMF Student Centered methodology, the student is placed at the center of all training services and guides the institution towards academic and professional success. The student will be able to know his progress at all times, be attended when he needs to, access to all resources with total freedom and have a coaching service, headhunting and job placement.

All students who successfully complete this program will obtain a double Master's degree from the University Camilo José Cela and Master by MFI Business School. They will have at their disposal all the advantages of MFI:

  • Program Scholarships and Study Grants
  • Recruiters with over 12,000 vacancies posted in the last year
  • Unlimited tutoring
  • Live online classes
  • Masterclasses and networking sessions
  • Financing up to 12 months without interest or bank intervention
  • Virtual library with over 30,000 references
  • Virtual library with access to any master classes
  • Access to the VIP Club with discounts on leisure, travel, restaurants ...

TEMARY:

  • MODULE I - Technological Foundations for Data Processing
  • MODULE II - Models and Statistical Learning
  • MODULE III - Applied Automatic Learning
  • MODULE IV - Text Mining and Natural Language Processing (NLP)
  • MODULE V - Business Intelligence and Visualization
  • MODULE VI - Big Data Infrastructure
  • MODULE VII - Storage and Data Integration
  • MODULE VIII - Value and Context of Big Data Analytics
  • MODULE IX - Analytical Applications
  • MODULE X - Final Master's Work
  • COURSE I - English Course


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The growing availability of huge amounts of data in business and industry is generating a high demand for graduates able to handle and exploit big data. Read more
The growing availability of huge amounts of data in business and industry is generating a high demand for graduates able to handle and exploit big data. Using sophisticated analytics techniques, including social network visualization and sentiment analysis, and professional software packages, including R dplyr and ggplot2, you will gain the skills and knowledge to transform data into commercial value and boost your employability.

Key features

-Equipping applicants from almost all undergraduate degrees with broad professional competence in one of the world economy’s most sought-after postgraduate subject areas.
-Offering an equal number of taught credits in the three areas of data modelling, computing and business, with a wide choice of available business modules.
-Providing a flexible individual project in one or more of the three taught areas supervised by world-leading subject experts.
-Establishing high proficiency in the use and application of state-of-the-art programming languages including R.
-Developing modern analytics expertise for obtaining business, scientific and social insights from Big Data sources and social networks such as Facebook and Twitter.
-Consult eBooks to support your learning and receive a free Apple iPad mini to stay-up-to date, wherever you are.
-Enjoy teaching from leading academics: for example, in the UK 2014 Research Excellence Framework 68 per cent of our mathematics and statistics research papers were classified as World Leading or Internationally Excellent.

Course details

Year 1
Throughout the programme you will learn how to master sophisticated analytics techniques and professional software, including R, to handle and exploit big data, and to work as part of a project team. You will also develop practical and professional competence in data science and business analytics, and will be able to make strategic decisions in a broad range of business related practical situations.

In semester two you will select optional modules to suit your interests and career aspirations and have the opportunity to boost your employability with an optional industrial placement.

An optional placement year is available after Semester 2.

Core modules
-ISAD515 Computational Problem Solving and Computer Systems
-BPIE500 Masters Stage 1 Placement Preparation
-MATH500 Big Data and Social Network Visualization
-PROJ516 MSc Project
-SOFT562 Software Development and Databases
-MATH501 Modelling and Analytics for Data Science

Optional modules
-STO702 Global Supply Chain Management
-ACF717 Econometrics and Financial Modelling
-MKT704 Branding and Marketing Communications
-STO703 International Strategic Management
-MKT714 Social Media Practice
-MKT715 Relationship Marketing and CRM
-STO700B International Business Environment
-ACF719 Financial Management

Final year
Optional modules
-BPIE503 Mathematics Masters Industrial Placement

Every postgraduate taught course has a detailed programme specification document describing the programme aims, the programme structure, the teaching and learning methods, the learning outcomes and the rules of assessment.

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This Postgraduate Certificate provides you with a practical understanding of big data analytics and emerging technologies. You will gain the essential skills and confidence required to apply knowledge and understanding of issues surrounding big data analytics in a range of contexts. Read more

This Postgraduate Certificate provides you with a practical understanding of big data analytics and emerging technologies. You will gain the essential skills and confidence required to apply knowledge and understanding of issues surrounding big data analytics in a range of contexts. There is the opportunity to develop a critical understanding of visualisation concepts and emerging technologies, as well as to develop and evaluate new or advanced bespoke solutions for making sense of big and/or complex data. The programme enables you concentrate on a specific practical area within computer science and is suitable whether you are a recent graduate or already working in the IT industry and looking to change career paths.

What will I study?

Gaining knowledge of big data applications and visualization, along with a critical understanding of new technologies, you will develop a systematic and critical understanding of the algorithms and programming techniques required for processing, storing, analysing, visualising and interpreting data.

How will I study?

The course is delivered through a combination of seminars and tutorials in evening classes. Sessions will frequently be highly interactive with a focus on the practical application of concepts and the use of case studies drawn from real life. You will apply your knowledge in a practical environment using the state of the art facilities in the Tech Hub. An emphasis on small group sizes ensures that you will have plenty of opportunities for individual discussions with your tutors. Typically, you will study for approximately nine hours a week.

How will I be assessed?

Your vocational capability, academic critical thinking and intellectual development will be assessed throughout the course. This is achieved through a combination of coursework, portfolios, case studies and problem-solving exercises. You may be assessed individually or as part of a group.

Who will be teaching me?

You will be taught by highly qualified, experienced and enthusiastic academic staff who are research-active and fully engaged with the wider business and academic community. The programme team specialise in a variety of subjects so you will benefit from a wide range of expertise. There will also be occasional input from external IT professionals who will be invited to teach particular sessions.



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The Masters of Science degree program in Business Analytics (MS-BA) is designed to meet the rising national and international demand of businesses for professionals who can collect, analyze, and interpret the avalanche of data created in the context of economic activity. Read more

The Masters of Science degree program in Business Analytics (MS-BA) is designed to meet the rising national and international demand of businesses for professionals who can collect, analyze, and interpret the avalanche of data created in the context of economic activity.

This unique program will:

  • Address rising demand for business analysts of various types (e.g., pricing analyst, market analyst, process analyst, UX analyst) whose job entails the analysis of business-related data (e.g., transaction data for products, sentiments expressed by consumers) for the purpose of business decision making.
  • Position graduates in a world that appears increasingly data-centric (that is, more data generated and exponentially so) and data-decentralized (that is, both data collection and analysis is conducted within business units and sub-units rather than at the enterprise level).
  • Train graduates in the robust use of industry standard tools such as R and Python to solve business problems.
  • Train graduates to participate robustly in the entire value chain of business analytics - from strategy formulation to data collection/visualization to analysis and decision making.


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The Master of Public Health (MPH) programme is designed to prepare students for leadership in scientific and management roles in Public Health. Read more
The Master of Public Health (MPH) programme is designed to prepare students for leadership in scientific and management roles in Public Health. It attracts students from clinical and health related disciplines from all over the world.

Why study Public Health at Dundee?

This course provides high quality training in the application of epidemiological, statistical and behavioural techniques used in public health practice and research.

You will have the opportunity to improve generic and transferable skills and will be ideally placed to pursue a career in research or public health practice. The MPH also provides an ideal springboard for further postgraduate study at PhD level.

What's so good about studying Public Health at Dundee?

"My experience with the MPH course was positive in every respect. From the quality of the teaching to the academic support by members of the department, it was a highly rewarding experience. I would strongly recommend the MPH course at the University of Dundee"
Dr Thaofiq Olatunde Ijaiya (MPH, 2007)

"The MPH provides an invaluable experience of being taught by inspiring academics with excellent research experience in the field"
Tony Barr, Programme Manager - Nursing (MPH, 1996)

"The design and execution of the MPH programme was very good. However, I was most fulfilled during the research dissertation stage. It was a wonderful experience and I am prepared for the future research challenges."
Dr Ekwem Divine (MPH, 2010)

Teaching & Assessment

This course is taught predominantly by staff from the School of Medicine and guest lecturers from further afield.

The full time MPH course lasts for one year. The taught component takes nine months and is followed by research leading to a dissertation. All students initially enrol on a diploma programme (DipPubH) which includes the taught component only. To progress to the Masters programme and undertake the Masters dissertation students must obtain an overall pass of 60% in the taught component. Both programmes may be undertaken on a part-time basis.

This course has one start date - September

How you will be taught

The course is focussed on the academic needs of its students but also provides emotional and pastoral care as required. The inclusion of optional modules creates flexibility, which allows students to tailor the MPH to their specific requirements.

A variety of teaching and assessment methods are used to give students the best possible learning opportunity
Students are given formative assessment on all assignments

Students have a spacious teaching room with networked computers at their disposal

Lecturers operate an open door policy and students are encouraged to seek advice/help at any time

Students are given the opportunity to choose a dissertation topic which reflects their interest, then advised on the most appropriate supervisor

The rich research environment within the Division gives students the opportunity to work on a range of topics

The Division has weekly research seminars during term time, to which students are invited to attend
What you will study

The programme consists of the following modules

Core:
Public Health
Epidemiology
Introduction to Clinical Statistics
Research Methods
Behavioural & Social Science
Applied Epidemiology
Statistics for Clinical Trials
Applied Statistics with Routine Health Datasets
Introduction to Systematic Reviews
Data Visualization
Spatial Epidemiology

Optional:
Students studying for a Master of Public Health then undertake research and write a dissertation.

How you will be assessed

The student's performance is monitored by continuous assessment throughout the programme. Written and oral examinations are held in December, March and May. Examinations are graded passes (A to D) or fail.

Students must obtain grade D or above in all written and oral examinations in order to be awarded the Diploma.

To be eligible to progress from the Diploma onto the Masters, students must pass the examination of each subject and achieve a minimum overall pass at B or above (60%).

Careers

The MPH prepares students for research and management careers in public health and also a variety of medical and health related disciplines.

Previous students graduating with the MPH from Dundee have taken up management positions in public health practice, nursing, professions allied to medicine, education, government, WHO and NGOs; and research positions within academic public health, general practice, acute medicine, nursing, professions allied to medicine, veterinary medicine, dentistry and environmental health.

The MPH also provides an ideal springboard for further postgraduate study at PhD and MD level.

"I had a wonderful time during my stay at Dundee. Scotland as a whole and Dundee in particular have very friendly and hospitable people. This course is a well-balanced general MPH course. It will provide the prospective students with a good foundation and skill set to advance their career in research, management or academics.
Syed Asif Shah, MD. MPH. MBA. FACC. FACP, Assistant professor of Cardiology (MPH 1990)

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This industry-focused course is for Computer Science graduates and experienced professional programmers interested in developing high-quality, complex software systems. Read more
This industry-focused course is for Computer Science graduates and experienced professional programmers interested in developing high-quality, complex software systems.

Who is it for?

This industry-focused course is for Computer Science graduates and experienced professional programmers interested in developing high-quality, complex software systems and aiming at a high-quality career in the industry, e.g. software houses, consultancies, and major software users across different sectors.

Students will have a keen interest in designing complex software systems, coding them in a programming language using the latest technologies (SOA, cloud, etc.), and ensuring that they are of high quality and that they actually meet the needs of their stakeholders.

Objectives

You will develop skills in analysing requirements and designing appropriate software solutions; designing and creating complex software systems to solve real-world problems, evaluating and using advanced software engineering environments, design methods and programming languages, and evaluating and responding to recent trends in interoperability and software development.

The course focuses on advanced engineering concepts and methods, as well as design issues for the systematic development of high-quality complex software systems. These are explored using industrial strength technologies, like the C++ and Java programming languages and the UML modelling language.

The course covers significant trends in systems development, including service-oriented architecture, cloud computing, and big data. The course is delivered by acknowledged experts and draws on City's world-class research in Systems and Software Engineering, which has one of the largest groups of academics working in this area in London, covering almost all aspects - from requirements, to designing reliable systems for the nuclear industry.

Placements

Postgraduate students on a Computing and Information Systems course are offered the opportunity to complete up to six months of professional experience as part of their degree.

Our longstanding internship scheme gives students the chance to apply the knowledge and skills gained from their taught modules within a real business environment. An internship also provides students with professional development opportunities that enhance their technical skills and business knowledge.

Internships delivered by City, University of London offer an exceptional opportunity to help students stand out in the competitive IT industry job market. The structure of the course extends the period for dissertation submission to January, allowing students to work full-time for up to six months. Students will be supported by our outstanding Professional Liaison Unit (PLU) should they wish to consider undertaking this route.

Teaching and learning

Software Engineering MSc is available full-time (12 months) as well as part-time (up to 28 months).

Students successfully completing eight taught modules and the dissertation for their individual project will be awarded 180 credits and a Master's level qualification. Alternatively, students who do not complete the dissertation but have successfully completed eight taught modules will be awarded 120 credits and a postgraduate diploma. Successful completion of four taught modules (60 credits) will lead to the award of a postgraduate certificate.

Assessment

Each module is assessed through a combination of coursework and examination.

Modules

You will develop skills in analysing requirements and designing appropriate software solutions; designing and creating complex software systems to solve real-world problems, evaluating and using advanced software engineering environments, design methods and programming languages and evaluating and responding to recent trends in interoperability and software development.

The focus of the course is on advanced engineering concepts and methods, as well as design issues for the systematic development of high-quality complex software systems. These are explored using industrial strength technologies, such as the C++ and Java object-oriented programming languages and the UML modelling language.

The course covers significant trends in systems development, including service-oriented architecture, mobile and pervasive computing, cloud computing, big data, and XML-enabled interoperable services. The course is delivered by acknowledged experts and draws on City's world-class research in Systems and Software Engineering. City has one of the largest groups of academics working in the area in London, working on almost all aspects of the area - from requirements, to designing reliable systems for the nuclear industry.

Core modules - there are five core modules:
-Advanced Database Technologies (15 credits)
-Research Methods and Professional Issues (15 credits)
-Service Oriented Architectures (15 credits)
-Software Systems Design (15 credits)
-Advanced Programming: Concurrency (15 credits)

Elective modules - you will be required to take three elective modules, choosing from the following:
-Advanced Algorithms and Data Structures (15 credits)
-Big Data (15 credits)
-Programming in C++ (15 credits)
-Business Engineering with ERP Solutions (15 credits)
-Mobile and Pervasive Computing (15 credits)
-Data Visualization (15 credits)
-Cloud Computing (15 credits)

Career prospects

The MSc in Software Engineering aims to meet the significant demand for graduates with a good knowledge of computing. This demand arises from consultancies, software houses, major software users such as banks, large manufacturers, retailers, and the public services, defence, aerospace and telecommunications companies.

Typical entrants to the course have a degree in an engineering or scientific discipline, and wish to either move into the software engineering field or to the development of software for their current field. Entrants must have previous exposure to computing, especially to programming (particularly in Java or C#) and relational databases (from either academic or professional experience).

From this base, the course provides solid technical coverage of advanced software development, including such widely used languages as C++, Java, UML and XML for which demand is particularly high. The course is therefore quite demanding; its success in providing advanced academic education along these lines is evident from the fact that recent graduates of the course are currently employed in a wide spectrum of organisations.

Of course, the employment value of a master's degree is not just short term. Although on-the-job training and experience as well as technology specific skills are valuable, they can be rather narrow and difficult to validate, and to transfer. The structure of this course ensures that there is a strong balance between the development of particular skills and a solid education in the enduring principles and concepts that underlie complex software system development.

SAP Certification - in parallel to your degree you will be able to register for a SAP TERP10 Certification course at a substantial discount, thus obtaining an additional, much sought-after qualification

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