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Masters Degrees (Data Architecture)

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Master in BIG DATA. Read more
Master in BIG DATA : Data Analytics, Data Science, Data Architecture”, accredited by the French Ministry of Higher Education and Research, draws on the recognized excellence of our engineering school in business intelligence and has grown from the specializations in Decision Support, Business Intelligence and Business Analytics. The Master is primarily going to appeal to international students, "free movers" or those from our partner universities or for high-potential foreign engineers who are looking for an international career in the domain of Business Analytics.

This program leads to a Master degree and a Diplôma accredited by the French Ministry of Higher Education and research.

Objectives

Business Intelligence and now Business Analytics have become key elements of all companies.

The objective of this Master is to train specialists in information systems and decision support, holding a large range of mathematic- and computer-based tools which would allow them to deal with real problems, analyzing their complexity and bringing efficient algorithmic and architectural solutions. Big Data is going to be the Next Big Thing over the coming 10 years.

The targeted applications concern optimization in the processing of large amounts of data (known as Big Data), logistics, industrial automation, but above all it’s the development of BI systems architecture. These applications have a role in most business domains: logistics, production, finance, marketing, client relation management.

The need for trained engineering specialists in these domains is growing constantly: recent studies show a large demand of training in these areas.

Distinctive points of this course

• The triple skill-set with architecture (BI), data mining and business resource optimization.
• This master will be run by a multidisciplinary group: statistics, data mining, operational research, architecture.
• The undertaking of interdisciplinary projects.
• The methods and techniques taught in this program come from cutting-edge domains in industry and research, such as: opinion mining, social networks and big data, optimization, resource allocation and BI systems architecture.
• The Master is closely backed up by research: several students are completing their end-of-studies project on themes from the [email protected] laboratory, followed and supported by members from the laboratory (PhD students and researcher teachers).
• The training on the tools used in industry dedicated to data mining, operational research and Business Intelligence gives the students a plus in their employability after completion.
• Industrial partnerships with companies very involved in Big Data have been developed:
• SAS via the academic program and a ‘chaire d’entreprise’ (business chair), allowing our students access to Business Intelligence modules such as Enterprise Miner (data mining) and SAS-OR (in operational research).

Practical information

The Master’s degree counts for 120 ECTS (European Credit Transfer System) in total and lasts two years. The training lasts 1252 hours (611 hours in M1 and 641 hours in M2). The semesters are divided as follows:
• M1 courses take place from September until June and count for a total of 60 ECTS
• M2 courses take place from September until mid-April and count for a total of 42ECTS
• A five-month internship (in France) from mid- April until mid- September for 9 ECTS is required and a Master thesis for 9 ECTS.

Non-French speakers will be asked to participate to a one week intensive French course that precedes the start of the program and allows students to gain the linguistic knowledge necessary for daily interactions.

[[Organization ]]
M1 modules are taught from September to June (60 ECTS, 611 h)
• Data exploration
• Inferential Statistics (3 ECTS, 30h, 1 S*)
• Data Analysis (2 ECTS, 2h, 1 S)
• Mathematics for Computer science
• Partial Differential Equations and Finite Differences (3 ECTS, 30h, 1 S)
• Operational Research: Linear Optimization (2 ECTS, 20h, 1 S)
• Combinatory Optimization (2 ECTS, 18h, 1 S)
• Complexity theory (1 ECTS, 9h, 1 S)
• Simulation and Stochastic Process (3 ECTS, 30h, 2 S**)
• Introduction to Predictive Modelling (2ECTS, 21h, 2 S)
• Deterministic and Stochastic Optimization (3 ECTS, 30h, 2 S)
• Introduction to Data Mining (2 ECTS, 21h, 2 S)
• Software and Architecture
• Object-Oriented Modelling (OOM) with UML (3 ECTS, 30h, 1 S)
• Object-Oriented Design and Programming with Java (2 ECTS, 30h, 1 S)
• Relational Database: Modelling and Design (3ECTS, 30h, 1 S)
• PLSQL (2 ECTS, 21h, 2 S)
• Architecture and Network Programming (3 ECTS, 30h, 2 S)
• Parallel Programming (3 ECTS, 30h, 2 S)
• Engineering Science
• Signal and System (3 ECTS, 21 h, 1 S)
• Signal processing (3 ECTS, 30h, 1 S)

• Research Initiation
• Scientific Paper review (1 ECTS, 9h, 1 S)
• Final research project on BIG DATA (5 ECTS, 50h, 2 S)
• Project Management
• AGIL Methods & Transverse Project (2 ECTS, 21h, 2 S)
• Languages and workshops
• French and Foreign languages (6 ECTS, 61h, 1&2 S)
• Personal and Professional Project (1 ECTS, 15, 1 S)
*1 S= 1st semester, ** 2 S= 2nd semester

M2 Program: from September to September (60 ECTS, 641h)
M2 level is a collection of modules, giving in total 60 ECTS (42 ECTS for the modules taught from September to April, plus 9 ECTS for the internship and 9 ECTS for the Master thesis).

Computer technologies
• Web Services (3 ECTS, 24h, 1 S)
• NOSQL (2 ECTS, 20h, 1 S)
• Java EE (3 ECTS, 24, 1S)
Data exploration
• Semantic web and Ontology (2 ECTS, 20h, 1 S)
• Data mining: application (2 ECTS, 20h, 1S)
• Social Network Analysis (2ECTS, 18h, 1S)
• Collective intelligence: Web Mining and Multimedia indexation (2 ECTS, 20h, 2 S)
• Enterprise Miner SAS (2 ECTS, 20h, 2 S)
• Text Mining and natural language (2 ECTS, 20h, 2 S)
Operations Research
• Thorough operational research: modelling and business application (2 ECTS, 21h, 1 S)
• Game theory (1 ECTS, 10h, 1 S)
• Forecasting models (2 ECTS, 20h, 1 S)
• Constraint programming (2 ECTS, 20h, 2 S)
• Multi-objective and multi-criteria optimisation (2 ECTS, 20h, 2 S)
• SAS OR (2 ECTS, 20h, 2 S)
Research Initiation Initiative
• Scientific Paper review (1 ECTS, 10h, 1 S)
• Final research project on BIG DATA (2 ECTS, 39, 2 S)
BI Architecture
• BI Theory (2 ECTS, 20h, 2 S)
• BI Practice (2 ECTS, 20h, 2 S)
Languages and workshops (4 ECTS, 105h, 1&2 S)
• French as a Foreign language
• CV workshop
• Personal and Professional Project
Internship
• Internship (9 ECTS, 22 weeks minimum)
Thesis
• Master thesis (9 ECTS, 150h)

Teaching

Fourteen external teachers (lecturers from universities, teacher-researchers, professors etc.), supported by a piloting committee, will bring together the training given in Cergy.

All the classes will be taught in English, with the exception of:
• The class of FLE (French as a foreign language), where the objective is to teach the students how to understand and express themselves in French.
• Cultural Openness, where the objective is to enrich the students’ knowledge of French culture.
The EISTI offers an e-learning site to all its students, which complements everything the students will learn through their presence and participation in class:
• class documents, practical work and tutorials online
• questions and discussions between teachers and students, and among students
• a possibility of handing work in online

All Master’s students are equipped with a laptop for the duration of the program that remains the property of the EISTI.

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The world is awash with data and much more is on the way, creating a tidal wave of Big Data. Data Engineers develop the infrastructure to store, manage, analyse this wave of data, to bridge the gap between Data and Computer Science. Read more
The world is awash with data and much more is on the way, creating a tidal wave of Big Data. Data Engineers develop the infrastructure to store, manage, analyse this wave of data, to bridge the gap between Data and Computer Science. This unique course will give you the skills you’ll need to succeed as a Data Engineer.

Why study Data Engineering at Dundee?

The role of “Data Scientist” has been described as the “sexiest job of the 21st Century. However, there is a emerging a new role, that of Data Engineer as more companies are realising they need employees with specific skills to handle the amount of data that is being generated and the coming tidal wave from the Internet of Things.

This MSc has been created with industry input to prepare its students with the skills to handle this wave of data and to be at the forefront of its exploitation. Students on the sister programmes (“Data Science” and “Business Intelligence”) have gone on to work for some of the biggest companies in the industry and we are confident that graduates from this MSc will have the same success.

The School of Computing at the University of Dundee has been successfully offering related MSc programmes such as Business Intelligence and Data Science since 2010. These innovative programmes attract around 40 students per year, drawn from across Europe and Overseas.

What's so good about Data Engineering at Dundee?

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

Special features

The University of Dundee has close ties with the Big Data industry, including Teradata, Datastax and Microsoft. We have worked with SAS, Outplay, Tag, GFI Max, BrightSolid and BIPB, and our students have enjoyed guest lectures from Big Data users such as O2, Sainsbury’s, M&S and IBM.

You will be able to work with a range of leading researchers and tutors, including top vision and imaging researchers and BI experts. Our honorary staff include legal experts, entrepreneurs and renowned industry experts such as John Richards of the newly formed IBM Watson Group.

How you will be taught

The course will be taught by staff of the School of Computing. Depending on the modules you take this will include Andy Cobley, Professor Mark Whitehorn, and Professor Stephen McKenna.

What you will study

The course will be taught in 20 credit modules with a 60 credit dissertation. Students will require to complete 180 credits for the award of the MSc (including 60 credits for the dissertation). Students completing 120 credits (without the dissertation) will be eligible for a Postgraduate Diploma.

Course content

Each module on the course is designed to give the student the skills and understanding they need to succeed in the Data Engineering/ Science field. Content on the course includes (but is not limited to):

CAP theorem
Lamda Architecture
Cassandra, Neo4j and other nosql databases
The Storm distributed real time computation system
Hadoop, HDFS, MapReduce, and other Hadoop/SQL technologies
Spark and Shark frameworks
Data Engineering languages such as Python, erlang, R, Matlab
Vision systems, which are becoming increasingly important in data engineering for extracting features from large quantities of images such as from traffic, medical and industrial
RDBMS systems which will continue to play an important role in data handing and storage. You will be expected to research the history of RDMBS and delve in to the internals of modern systems
OLAP cubes and Business Intelligence systems, which can be the best and quickest way to extract information from data stores
Goals of machine learning and data mining
Clustering: K-means, mixture models, hierarchical
Dimensionality reduction and visualisation
Inference: Bayes, MCMC
Perceptrons, logistic regression, neural networks
Max-margin methods (SVMs)
Mining association rules
Bayesian networks

How you will be assessed

The course is assessed through a combination of examinations, coursework, presentations and interviews. Each module is different: for instance the Big data module has 40% coursework, consisting of Erlang programming and a presentation on nosql databases, along with an examination worth 60%.

Careers

Our experience suggests that graduates of this course will have most impact in the following areas:

Cloud and web based industries that handle large volumes of fast moving data that need to be stored, analysed and maintained. Examples include the publishing industry (paper, TV and internet), messaging services, data aggregators and advertising services

Internet of Things. A large amount of data is being generated by devices (robotic assembly lines, home power management, sensors etc.) all of which needs to be stored and analysed.

Health. The NHS (and others) are starting to store and analyse patient data on an unprecedented scale. The healthcare industry is also combining data sources from a large number of databases to improve patient well-being and health outcomes

Games industry. The games industry records an extraordinary amount of data about its customers' play activities, all of which needs to be stored and analysed. This course will equip students with the knowledge and skill to engage with the industry.

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The Masters in Data Science provides you with a thorough grounding in the analysis and use of large data sets, together with experience of conducting a development project, preparing you for responsible positions in the Big Data and IT industries. Read more
The Masters in Data Science provides you with a thorough grounding in the analysis and use of large data sets, together with experience of conducting a development project, preparing you for responsible positions in the Big Data and IT industries. As well as studying a range of taught courses reflecting the state-of-the-art and the expertise of our internationally respected academic staff, you will undertake a significant programming team project, and develop your own skills in conducting a data science project.

Why this programme

◾The School of Computing Science is consistently highly ranked achieving 2nd in Scotland and 10th in the UK (Complete University Guide 2017)
◾The School is a member of the Scottish Informatics and Computer Science Alliance: SICSA. This collaboration of Scottish universities aims to develop Scotland's place as a world leader in Informatics and Computer Science research and education.
◾We currently have 15 funded places to offer to home and EU students.
◾You will have opportunities to meet employers who come to make recruitment presentations, and often seek to recruit our graduates during the programme.
◾You will benefit from having 24-hour access to a computer laboratory equipped with state-of-the-art hardware and software.

Programme structure

Modes of delivery of the MSc in Data Science include lectures, seminars and tutorials and allow students the opportunity to take part in lab, project and team work.

Core courses

◾Big data
◾Data fundementals
◾Information retrieval
◾Machine learning
◾Research methods and techniques
◾Text as data
◾Web science
◾Masters team project.

Optional courses

◾Advanced networking and communications
◾Advanced operating systems
◾Algorithmics
◾Artificial intelligence
◾Big data: systems, programming and management
◾Computer architecture
◾Computer vision methods and applications
◾Cryptography and secure development
◾Cyber security forensics
◾Cyber security fundamentals
◾Distributed algorithms and systems
◾Enterprise cyber security
◾Functional programming
◾Human computer interaction
◾Human computer interaction: design and evaluation
◾Human-centred security
◾Information retrieval
◾Internet technology
◾IT architecture
◾Machine learning
◾Mobile human computer interaction
◾Modelling reactive systems
◾Safety critical systems.
◾Software project management
◾Theory of Computation

Depending on staff availability, the optional courses listed here may change.

If you wish to engage in part-time study, please be aware that dependent upon your optional taught courses, you may still be expected to be on campus on most week days.

Industry links and employability

◾The advent of Big Data tools in recent years has facilitated the large-scale mining of voluminous data, to allow actionable knowledge and understanding, known as Data Science. For instance, search engines can gain insights into how ambiguous a query is according to the querying and clicking patterns of different users. Data Science combines a thorough background in Big Data processing techniques, combined with techniques from information retrieval and machine learning, to permit coherent and principled solutions allowing real insights and predictions to be obtained from data.
◾The programme includes a thorough grounding in professional software development, together with experience of conducting a development project. The programme will prepare you for a responsible position in the IT industry.
◾The School of Computing Science has extensive contacts with industrial partners who contribute to several of their taught courses, through active teaching, curriculum development, and panel discussion. Recent contributors include representatives from IBM, J.P. Morgan, Amazon, Adobe, Red Hat and Bing.
◾During the programme students have an opportunity to develop and practice relevant professional and transferrable skills, and to meet and learn from employers about working in the IT industry.

The Data Lab

We work closely with The Data Lab, an internationally leading research and innovation centre in data science. Established with an £11.3 million grant from the Scottish Funding Council, The Data Lab will enable industry, public sector and world-class university researchers to innovate and develop new data science capabilities in a collaborative environment. Its core mission is to generate significant economic, social and scientific value from data. Our students will benefit from a wide range of learning and networking events that connect leading organisations seeking business analytics skills with students looking for exciting opportunities in this field.

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

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

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

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

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

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

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

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

Associated Schools:

Law School
School of Social and Behavioral Sciences
School of Humanities

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As a Data Visualisation Designer you can contribute innovative solutions with the potential to transform societal challenges, by designing the human interface to increasingly complex problems. Read more

Why take this course?

As a Data Visualisation Designer you can contribute innovative solutions with the potential to transform societal challenges, by designing the human interface to increasingly complex problems.

On this course, you will learn how to create rich and meaningful stories with data. We will study digital content in any mode, whether it is in alphanumeric form, binary, vector, pixel, video, or others. The designer provides an important interface, that allows us to explore data and generates meaningful communication. This communication is predominantly visual, but with developments in Wearables and the Internet of Things, is also becoming increasingly physical, affective, networked and interactive. Data Visualisation Design spans traditional graphic and information design, interaction design, information architecture, computational design, design thinking and user-centred and user experience design.

What will I experience?

On this course you can:

Learn the theory and practice of data visualisation, data, interface/interaction design and user experience, and apply this to your own design
Critically question the role of data related to the social, political, economic and cultural through contextual research
Explore live data sets from real world scenarios, such as industry or charities like the digital humanitarian network
Develop independent research and project ideas to create innovative, forward thinking design solutions and experiences for a digital and data driven world

What opportunities might it lead to?

The course will prepare you to work in the design disciplines of the creative industries, with a focus on data visualisation, information design, computational design, digital content, interactivity and user experience. Data Visualisation designers are in demand in sectors including business, research, health, education, government/public service, the arts.

The skills gained on this course can also be applied to employment in UI (user interface) design, or focus on interaction as a UX (User experience) designer. The critical and contextual outlook allows you to position yourself as a strategist and operate in a consultative manner. The research aspect of the course would also suit a career in compulsory, further and higher education.

Careers include:

Data Visualisation Design
Information Design
Digital Graphic Design
UI (user interface) / UX (user experience) design
Interaction design

Module Details

The course is offered over one year (full-time) or two years (part-time).

You will study five units, one of which is shared with other MA courses in the School of Art and Design. There will be preparatory units delivering a grounding in practical skills, theoretical context and academic research (competencies and skills). You will also study units that allow more thematic engagement with interactive and data driven design in terms of theory such as critical design, affordances, experience and complexity. It will also provide a unit oriented towards employability, and incorporate live briefs and group work. These units work to catalyse your own ideas and research direction for the Major Project unit.

Core units currently comprise:

A Question of Research
Fundamentals of Data and Interaction Design
Digital Futures – Themes and Issues in Practice
Design Solutions for Enterprise, Society and Culture
Major Project

Programme Details

The teaching combines interactive lectures and group seminar discussions with support through one-to-one tutorials. You also receive feedback on your work through friendly but critical peer review in group sessions with other students, members of faculty and other experts as appropriate. One of the units includes working as a team. Your project work emphasises self-initiated learning which gives you the freedom to explore the specialist area of your interest, while being helpfully guided by your supervisor. The curriculum is very closely related to the research areas in the department, so the staff have cutting edge knowledge of the field and its potential for innovation.

Your learning is mostly assessed through the submission of practical course work, such as digital prototypes, and the documentation of the learning journey in sketchbooks, diaries, blogs or journals.

This will be documenting contextual research as well as stages in practical experimentation and annotation of reflection. There are some written elements to be submitted as well, mostly accompanying proposals/reports to contextualise your practice. The assessment also includes individual and group presentations, this mode is also used to give you formative feedback on your work throughout.

Here's how we assess your work:

Digital artefacts / prototypes
Learning journals
Proposals
Reports
Oral presentation

Student Destinations

This course is an opportunity to focus your creative design practice on the interactive, data driven, user centred and culturally contextualised. It also enhances your design career by upgrading your skills and widening your knowledge and thinking in the digital arena, allowing you to stay one step ahead of the rest. The independent research aspect of the course prepares you for further education in terms of a research degree and employment in R&D and/or education.

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This interdisciplinary MSc is aimed at students who wish to develop skills in the emerging discipline of Data Science. Read more
This interdisciplinary MSc is aimed at students who wish to develop skills in the emerging discipline of Data Science. Building upon data science fundamentals, a variety of pathways through the MSc are available and allow students to choose from a range of elective modules according to their skills, interests and career aspirations. Students then undertake a 12-week summer placement either within industry (in a business setting), or as part of an academic research project to consolidate their learning.

Optional pathways span fundamentals and also application areas including:
• Business Analytics: how to gain business insight from large and complex industrial data
• Data Mining: how data mining can be performed at scale, and in a range of application areas (eg marketing and finance, social computing)
• Health Informatics: how to build models and gain insight to improve public health and aid clinical decision making
• Systems and Technologies: how to build large-scale systems for answering data science questions
• Statistical Inference: how to specify models and build a statistical framework to gain insights from data

Modules
Core modules:
• Data Mining
• Data Science Fundamentals
• Generalised Linear Models
• Likelihood Inference
• Programming for Data Scientists

Optional (elective) Modules:
• Applied Data Mining
• Clinical Trials
• Data Mining for Marketing, Sales and Finance
• Elements of Distributed Systems
• Environmental Epidemiology
• Extreme Value Theory
• Forecasting
• Longitudinal Data Analysis
• Methods for Missing Data
• Multi-level Modelling
• Optimisation and Heuristics
• Principles of Epidemiology
• Statistical Genetics and Genomics
• Survival Analysis
• Systems Architecture and Integration

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The rapidly changing technological environment means that getting ahead of changes and developments is essential – especially for those working in the IT environment. Read more
The rapidly changing technological environment means that getting ahead of changes and developments is essential – especially for those working in the IT environment. Our online MSc in Data Analytics and Enterprise Architecture will provide you with an understanding of how to identify and design appropriate methods of gathering data in the complex modern computing systems of today and how to draw insights from this, and present data to inform decision making.

The programme will equip you with high level skills of managing business change and development to successfully integrate architecture development. You will gain the skills and resources to stay abreast with technological trends and developments and to incorporate strategic business plans into your role.

Modules:

Data Design
Data Handling and Decision Making
Data Visualisation and Interpretation
Architecture Design
Technology and Trend Monitoring
Business Change Management
Research Project

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The MSc in Architecture and Sustainable Environment (MASE) is a taught course aimed at professionals and academics world-wide with an interest in sustainability in the built environment, including architects, engineers, geographers, surveyors, historians and urban designers. Read more
The MSc in Architecture and Sustainable Environment (MASE) is a taught course aimed at professionals and academics world-wide with an interest in sustainability in the built environment, including architects, engineers, geographers, surveyors, historians and urban designers.

The MSc is offered by Centre for Architecture and Sustainable Environment, a new research centre in the Kent School of Architecture that promotes a cross-disciplinary approach to research in the field of sustainability in the built environment, bridging the traditional boundaries between the arts and the sciences, research and practice. The course content ranges from the development of the design skills and the technical and scientific understanding required to develop sustainable solutions for new and existing buildings, the analysis of historic buildings and past environment technologies, to a critical exploration of the historical and cultural context of sustainability and environmental design.

The course, which can be studied full-time or part-time, offers an academically rigorous and intellectually challenging learning environment, which aims to enhance career development within the field for professionals and academics. The over-arching aim of the programme is to provide participants with a systematic understanding of core and advanced areas of sustainable design through a combination of taught courses, research assignments and project work. Students will be asked to conduct rigorous technical and historical research and to explore the practical application of their findings in the context of design and technology.

Visit the website https://www.kent.ac.uk/courses/postgraduate/182/architecture-and-the-sustainable-environment

Course structure

The programme is aimed at professionals and academics with an interest in sustainability in the built environment, including architects, engineers, geographers, surveyors, historians and urban designers. The MSc promotes a cross-disciplinary approach to research in the field of sustainability in the built environment, bridging the traditional boundaries between architecture and the sciences, research and practice.

The course content ranges from the development of the technical and scientific understanding required to develop sustainable design solutions for new and existing buildings, the analysis of past environment technologies, to a critical exploration of the context of sustainability and environmental design.

The programme may lead to a postgraduate diploma, if taken without the dissertation.

Modules

The following modules are indicative of those offered on this programme. This list is based on the current curriculum and may change year to year in response to new curriculum developments and innovation. Most programmes will require you to study a combination of compulsory and optional modules. You may also have the option to take modules from other programmes so that you may customise your programme and explore other subject areas that interest you.

AR827 - Principles of Environmental Design (30 credits)
AR828 - Rediscovery - Understanding Historic Buildings and Past Environmental T (30 credits)
AR829 - Monitoring and Modelling of Environmental Performance (30 credits)
AR830 - Sustainable Design Project (30 credits)
AR899 - Dissertation: Architecture and the Sustainable Environment (60 credits)

Assessment

Assessment is mostly based on coursework, with presentations, case-study analyses, design proposals, essays and the dissertation.

Programme aims

This programme aims to:

- enable students to develop systematic understanding of the effect of the built environment on the environmental performance and energy consumption of buildings, while optimising comfortable conditions for the occupants

- develop your understanding of the sustainability drivers for the built environment

- develop your in-depth knowledge of the theoretical principles of low carbon design

- develop the ability to analyse the environmental behaviour of historic structures and the efficiency of past environmental technologies, using modern scientific methods

- promote creativity in the integration of sustainable solutions in the built environment at different scales

- enable you to develop skills for physical monitoring and digital modelling of the environmental and energy performance of buildings

- provide you with the ability to work in multidisciplinary design teams

- promote and support independent research skills.

- enable you to develop the skills required for both autonomous practice and team-working.

- support you, so that you can fulfil your full potential in the programme.

Research areas

- Research centres

KSA incorporates the Centre for Research in European Architecture (CREAte), which focuses on research in architectural humanities and design, and Centre for Architecture and Sustainable Environment (CASE), which promotes research in the field of sustainable architecture.

- CREAte

The Centre provides a focus for research in architecture in the European context. Its emphasis is on the role and contribution of humanities to architecture and urban design in the context of urban and regional regeneration, nationally and internationally.

CREAte provides a platform for evening lectures by contemporary architects and scholars; hosting debates and events that are in the heart of architectural agenda of today.

The Centre builds upon its staff specialisms, interests and skills in the following areas: regional studies, contemporary architectural and urban theory and design, architectural history and theory (ranging from antiquity to contemporary European cities), sustainability, European topographies (landscape, urban, suburban and metropolitan) etc. Staff participate in the activities of AHRA – Architecture Humanities Research Association and are internationally published authors.

- CASE

The Centre promotes research in the field of sustainable environment regionally, nationally and internationally.

Its research focus encompasses different aspects and scales of the sustainable built environment from the individual building to the urban block, promoting the wider environmental agenda and keeping the School at the forefront of research and development in the field. CASE also pursues research into the historical and cultural dimension of environmental design to foster links between the sciences, arts and humanities. There is a strong interest in understanding the environmental behaviour of historic buildings and the strategies originally deployed to manage the internal environment.

The Centre has already secured funding from various sources. This includes three EPSRC projects on climate change weather data for a sustainable built environment, sustainability of airport terminal buildings and design interventions in the public realm for affecting human behaviour, and two TSB-funded projects on Building Performance Evaluation. CASE is also involved with the recent EPSRC large-scale network on Digital Economy Communities and Culture.

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

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The School of Architecture currently provides research specialism in the areas of . Architecture & Media. , . City Design. Read more

The School of Architecture currently provides research specialism in the areas of Architecture & MediaCity DesignSocial Movements and Future of Work, which are seen as essential to contemporary architectural and urban research. However, the programme welcomes strong applications for other fields of interest as well as traditional academic research.

The Master’s of Research (MRes) RCA is a full-time, one-year programme that offers early-career research students the opportunity to develop and demonstrate mastery in the theory, methods and practice of research within an art and design environment. MRes RCA degrees are offered in four Schools (Communication, Design, Fine Art and Humanities) and are designed to provide early-career researchers with the intellectual, technical and professional tools with which to complete high-quality research projects, whether at doctoral level or within the cultural and creative industries, working across traditional sociocultural, disciplinary and sectoral boundaries.

MRes RCA programmes are delivered through a combination of: structured learning, comprising of lectures and master-classes by practitioners and senior academics; workshop classes based around a set task (a ‘brief’); tutorled seminar classes where students will be asked to reflect on material that they have read or studied in advance; and project assignments that support the structured teaching programme.

The programme provides students with the intellectual, technical and professional tools to pursue their own independent research within academia or industry, drawing on the experience and expertise of world-leading researchers across the College. The ethos of the programme will be collaborative, so students should be prepared to engage fully within their peer group, and with established and emerging research communities throughout the College.

In the development of intellectual engagement, students will be encouraged to demonstrate an advanced understanding of the principles of scholarly research within art, design and the humanities; identify robust research questions that interrogate fundamental questions of knowledge creation and exchange; critically analyse and evaluate complex research data; and situate their own research questions in the wider academic context of their field, understanding how their own research builds on and contributes to existing knowledge.

In the development of technical skills, students will be encouraged to: demonstrate an advanced understanding of the tools, methods, theories and techniques of research in Art and Design; experiment in the development, evaluation and presentation of complex research projects; effectively communicate the aims, methodologies and outcomes of their research to a range of different audiences; and effectively explore and articulate the potential of their research to achieve impact beyond the academic sphere.

For professional development, students will be encouraged to: take responsibility for directing their studies through setting goals and managing time and resources effectively; participate as an active, thoughtful and responsible member of a research community; demonstrate an understanding of and sensitivity to the principles and policies of ethical research; effectively plan and manage a complex research project; define their professional identity through self-reflection informed by theoretical, social and cultural awareness; engage constructively with research partners in order to form collaborations that benefit both their research and the partner organisation



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The dual degree option is a four-year program to pursue the Master of Architecture and the Master of Landscape Architecture at the same time. Read more
The dual degree option is a four-year program to pursue the Master of Architecture and the Master of Landscape Architecture at the same time. The dual degree is certified with both the Canadian Architectural Certification Board and the Canadian Society of Landscape Architects. The dual degree program harmonizes architectural design with ecological consciousness to create an inclusive understanding of built and natural environments.

Innovation

We are the first, and so far the only, school in Canada to offer you the opportunity to pursue both degrees at the same time.

Tradition of excellence

The University of British Columbia is a global centre for research and teaching, ranked among the top 20 public universities in the world. Our school is recognized for its commitment to sustainable research, ranking 20th in the 2015 and 27th in the 2016 QS World University Rankings, the highest of all Canadian architecture schools.

The place

Vancouver is consistently named as one of the top five worldwide cities for liveability and quality of life. With diverse geographic regions and climates, a rich, multi-cultural history and a dynamic arts and culture scene, Vancouver is an amazing place to work and study.

Award-winning faculty

Our faculty are internationally renowned experts in their fields and have chosen to teach here in part because of our school’s reputation for excellence in research. Join us and you will learn from the people who are changing the way we think about design.

Tight-knit community

With low student-faculty ratios, we get to know you by name. We are proud of our small studios, intimate seminars, and personalized learning opportunities. Our support structure ensures that you have a successful experience. From academic guidance to health and wellness, we have an array of services to help you achieve your personal, academic and professional goals.

Mentor program

When entering our program, we pair you with a professional mentor. Our mentor roster includes many of the most prominent pracitioners in Vancouver. Paired with you through to licensure, your mentor will not only contribute to your experience while at SALA, but will help make your transition from school to practice smoother.

International experiences

As a SALA student, you will be able attend summer electives and studios set abroad. These courses range from 3 weeks to a full semester. In recent years, we have taken students to Brazil, Germany, India, Japan, Mexico, and the Netherlands. For a more immersive experience, you can also spend up to a year at one of our partner universities.

Employment opportunities

We have a wide variety of employment opportunities. We currently offer 90 annual teaching assistantships and nearly as many research, administrative, and technical positions. Whether it is leading an undergraduate seminar, analysing data in the lab, or assisting in the workshop, you will find a position that is right for you.

Our students get involved

Our students organize lunchtime lectures, host weekly social events, and curate gallery exhibitions of their work. They create public art on campus, organize design builds and attend conferences around the world. They are passionate about what they do, and we hope you will be too.

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The MSc in Data Science is aimed at providing opportunities for students who wish to establish expertise and employment in data-centric, largely quantitative areas within a broad range of professional disciplines and areas of employment. Read more
The MSc in Data Science is aimed at providing opportunities for students who wish to establish expertise and employment in data-centric, largely quantitative areas within a broad range of professional disciplines and areas of employment. A cross-disciplinary approach is therefore central to the delivery of the programme.

According to Hal Varian, Google Chief Economist, “The ability to take data—to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it—that’s going to be a hugely important skill in the next decades.” It is these skills and the knowledge that underpins them that are the focus of this programme.

The taught elements include:
Data ecology
Quantitative Data Analysis
Spatial Data Analysis
Analysing Qualitative Data
Advanced Decision Making

The dissertation element will focus on pure or applied aspects of the Data Science research agenda and will provide an opportunity for students to apply and enhance their new knowledge and skills under expert guidance.

The taught modules on this programme are available to be taken as credit bearing short courses by suitably qualified individuals.

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The Professional Doctorate in Data Science is aimed at professionals who wish to enhance and/or validate data-centric, evidence-based approaches within their chosen career through a combination of taught modules and doctoral research. Read more
The Professional Doctorate in Data Science is aimed at professionals who wish to enhance and/or validate data-centric, evidence-based approaches within their chosen career through a combination of taught modules and doctoral research. A cross-disciplinary approach is central to the delivery of this programme and is therefore suitable for professionals in a broad range of professional disciplines and areas of employment.

According to Hal Varian, Google Chief Economist, “The ability to take data—to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it—that’s going to be a hugely important skill in the next decades.” It is these skills and the knowledge at depth that underpins them that are the focus of this programme.

The taught elements include:

Data ecology
Research Methods for Technologists
Applied Research Tools and Techniques
Spatial Data Analysis
Analysing Qualitative Data
Advanced Decision Making
Work-based Project Review

The doctoral research element will focus on pure or applied aspects of Data Science within the student’s main discipline or area of employment. The programme is unique, internationally, in offering a Professional Doctorate qualification in Data Science.

The taught modules on this programme are available to be taken as credit bearing short courses by suitably qualified individuals.

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The MA in Professional Studies is a route to registration as an architect in the UK, approved by the Architects Registration Board (ARB) and Royal Institute of British Architects (RIBA) at Part 3 level. Read more
The MA in Professional Studies is a route to registration as an architect in the UK, approved by the Architects Registration Board (ARB) and Royal Institute of British Architects (RIBA) at Part 3 level. On the course, students acquire an in-depth understanding of the legal and economic aspects of architectural practice and construction procurement, and the related skills necessary to practice effectively.

The course has an outstanding reputation. This is reflected in the Commendations it has received from successive RIBA Visiting Boards including from the latest, in July 2016, when the Commendation was for its ‘breadth, depth and rigour’.

On the course students explore the professional aspects of practice as an architect, including the construction industry and role of the profession, development controls, construction law, and project and practice management. We aim to inspire our students with a keen interest in current issues relating to the profession. Students are encouraged to explore their own relevant areas of interest, and to develop critical and independent judgement, and the ability to manage complex processes. Research skills are developed through means of a dissertation.

The MA Professional Studies is a part-time qualification which is a route to registration as an architect that also includes a research element in the form of a dissertation.

Distinctive features

• Accredited by the Royal Institute of British Architects (RIBA) and the Architects Registration Board (ARB) at Part 3 level.

• Based on acclaimed research expertise within the Welsh School of Architecture and run by a leading author and expert in the field.

• Study while you work in practice; this course is taught by distance learning and short courses, where the emphasis is on workshops and group working.

• Benefit from a small cohort size, individual tutoring (normally including a workplace visit), and the wide variety of expert speakers and topics covered.

• Includes a module on international practice, unique for an ARB approved course.

• Supported by an active alumni network.

Structure

The course is taught by distance learning and supplemented by short courses, normally three one-week courses held in October, January and March. We also hold final assessment days in May or June. The activities you carry out on your work placement contribute to your learning experience and are monitored by the School.

Please visit the website to see the modules taught on this course:

http://www.cardiff.ac.uk/study/postgraduate/taught/courses/course/architecture-professional-studies-ma-part-time

Teaching

On this course you will be taught mainly through distance learning using the University’s virtual learning environment, Learning Central. We’ll post course notes, assignments and support materials there and you can also use the forum facility to ask questions and engage with fellow students. Your coursework will be submitted electronically through digital dropboxes.

Due to the nature of this course, you are responsible for reading any emails sent by module tutors or announcements made through Learning Central on a frequent basis.

Assessment

Taught and project-based modules are assessed in a variety of different ways depending on the module content and learning outcomes (found in the module descriptions). We use class tests, course work (both written assignments and oral presentations or critical assessments/crits), and project work, or a combination of these to assess your progress on the module.

In the dissertation stage, your dissertation is the sole object of assessment. The dissertation is a written report on a piece of research which you have carried out in an agreed subject area under supervision. You may choose a topic relating to cutting edge professional practice, or a current issue or problem of concern to the profession. Your dissertation may involve collection and analysis of original data, or placing an original interpretation on existing data.

Career prospects

After completing the MA in Professional Studies, you will be able to register with the Architects Registration Board (ARB) and therefore use the title ‘architect’ in the UK. The profession of architecture is covered by the Mutual Recognition of Professional Qualifications Directive 2005/36/EC. Therefore, registration also gives you the right to register in other EU member states on successful completion of the course. A UK architectural qualification is generally valued worldwide.

Past graduates have gone on to found their own architectural practice and lead teams within large global architecture firms. MA students have also gone into research posts or academia. Tutors on this course have established links with architectural practice which can help students to network and make connections in the field. There is also a strong alumni network with international links that you may benefit from.

Placements

You will be based in a suitable work placement as part of this distance learning course. You are required to find your own placement location before the course begins, such as an architects practice, or an approved construction industry firm.

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This MSc programme is centred on furthering the understanding of architecture and urban design in the development of building cities and the social groups that inhabit them. Read more
This MSc programme is centred on furthering the understanding of architecture and urban design in the development of building cities and the social groups that inhabit them. It offers an increase of specialism to those interested in the research and design of the built environment intending to take either an academic pathway or a specific direction within their current professional practice.

Degree information

The programme addresses the study of architecture and cities using the theoretical and analytical framework of space syntax as well as wider theoretical and analytical approaches. Students learn to specialise in one of several streams related to contemporary world challenges: architecture and computing, sustainable urbanism, social inclusion and exclusion, informal settlements, spatial cognition, the physical and immaterial dimensions of social networks and design innovation.

Students undertake modules to the value of 180 credits.

The programme consists of seven core modules (90 credits), one optional module (30 credits) and a dissertation (60 credits).

Core modules
-Design as a Knowledge-Based Process
-Buildings, Organisations and Networks
-Space Syntax Methodology and Analytical Design
-Spatial Cultures
-Architectural Phenomena
-Spatial Justice

Optional modules
-Analytical Design Research Project
-E-Merging Design and Analysis

Dissertation/report
All MSc students submit a 10,000-word dissertation related to the main themes of the programme, typically involving a directed research project on a building or urban site.

Teaching and learning
The programme is delivered through seminars, lectures, design studios, hands-on computer workshops, a variety of field trips in and around London and an international trip (optional). Assessment is through essays, written and take-home examinations, oral presentations, project reviews, debates, group and individual projects, classroom exercises and the dissertation.

Fieldwork
The E-merging analysis and design studio (optional module) is usually accompanied by an international trip not exceeding £ 750 per person, based on standard costs as specified by the School.

Careers

Graduates of the programme go on to many different career routes: some have progressed to PhD degrees and have obtained academic positions in top universities worldwide, others have found teaching positions on architectural programmes; some go into policy-making activities; and many have ploughed their knowledge back into furthering their architectural/design careers. In the past few years an increasing number of graduates have obtained jobs at Space Syntax Limited.

First destinations of recent graduates include: CABE, Foster and Partners, Aecom, Arup, Qatar Foundation, Cube Design, Portland Design Associates, Levitt Bernstein, Paul Drew Design, Manu Chugh Architects, Buro Happold and Space Lab, as well as various academic or research positions at prestigious international universities or research centres.

Employability
This programme enhances students' intellectual and design abilities in the field of urban/architectural theory, architectural/urban morphology and the social aspects of the urban environment. Graduates of this programme can be involved in both professional and academic activities. Graduates who choose to go into practice will have a leading edge in evidence-informed and research-based design. Those who choose an academic path will have the advanced knowledge and skills required for high-level academic positions.

Why study this degree at UCL?

The course provides a unique approach to the study of architecture and cities world-wide equipping students with exceptional theoretical and analytical skills. It is located in UCL Bartlett one of the UK's largest multidisciplinary built environment faculty, bringing together scientific and professional specialisms required to research, understand, design, construct and operate the buildings and urban environments of the future.

The programme is unique in the world in integrating architecture and urbanism, and adopting a user-centred approach. Students receive advanced and exceptional training in theories, data analysis and their creative integration with design thinking.

The degree draws on the rich design industries in London including Space Syntax Ltd and provides networking opportunities to help advance students in their academic and professionals both during and after the programme.

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Programme description. Design Informatics combines Data Science with Design Thinking in a context of critical enquiry and speculation. Read more

Programme description

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

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

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

Programme structure

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

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

In the first year, you will study:

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

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

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

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

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

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

Career opportunities

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



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