• Jacobs University Bremen gGmbH Featured Masters Courses
  • University of Derby Online Learning Featured Masters Courses
  • University of Surrey Featured Masters Courses
  • Northumbria University Featured Masters Courses
  • Swansea University Featured Masters Courses
  • University of Bristol Featured Masters Courses
  • University of Edinburgh Featured Masters Courses
  • Aberystwyth University Featured Masters Courses
London Metropolitan University Featured Masters Courses
University College London Featured Masters Courses
Birmingham City University Featured Masters Courses
Imperial College London Featured Masters Courses
University of Sheffield Featured Masters Courses
"machine" AND "design"×
0 miles

Masters Degrees (Machine Design)

We have 234 Masters Degrees (Machine Design)

  • "machine" AND "design" ×
  • clear all
Showing 1 to 15 of 234
Order by 
MA Communication Design at Falmouth is a transformative, intensive studio based course, enabling you to develop your individual critical voice in communication design. Read more
MA Communication Design at Falmouth is a transformative, intensive studio based course, enabling you to develop your individual critical voice in communication design. The course prepares you for the demands of a rapidly changing, complex media world, where the ability to create meaningful and effective ideas is paramount.

Benefits:
- Learn from leading global design provocateurs and teachers in project challenges and study set
- Gain commercial experience through internships
- Work in a multi-million pound studio environment that mirrors leading contemporary design studios
- Specialist skills training, relevant for your project interests
- Final semester London show
- Digital final exhibition for global recognition and launch

Visit the website https://www.falmouth.ac.uk/communication-design-ma

How the course is taught

The course is structured over 45 weeks, across three semesters: deconstruction, reconstruction and reinvention.

You'll be in the studio most weekdays working on outcomes rooted in design process and the development of meaningful and innovative ideas. The experience is designed to be supportive yet provocative, so you can take your ideas and practice into new and exciting realms, that challenge you and the wider communications world.

Your learning is delivered across a mixture of set lectures, tutorials, workshops, and peer and tutor review.

Contact hours vary across the course, being most intensive during the first two semesters, with more self directed study as you develop your final project in the third semester. We expect some students to be away at points during the final semester, either working on research and project feedback, or attending internships.

Course outline

The course prioritises fresh and fearless thinking, developing students who see no boundaries to their work, curious to engage and discover while pursuing the highest level of innovation in communication design.

You'll gain an understanding of the global framework of communication design, and an approach to design process that delivers great ideas across diverse media platforms.

Mirroring the success of longstanding programmes at our School of Communication Design, you'll benefit from frequent industry contact, enabling you to stretch and question your practice, gaining inspiration from within and beyond your immediate boundaries.

Attracting a range of applicants, the course prepares you for independent or studio practice, in the applied creative industries, broader arts, or further academic research.

Our priority is to encourage your development by distilling and building your creative voice and ambition. We do so via three semesters, deconstruction, reconstruction and reinvention, with project outcomes mirroring a design process structure.

What you'll do

Semester 1: Deconstruction
- MACD 101: Process
(20 credits)
This module introduces the components of design process in relation to your own personal practice. Through provocation and critical debate you'll reflect on and challenge what you do, seeing how global, experiential and experimental insights can generate the most appropriate process models for a contemporary communications problem.

- MACD 102: Intersections
(20 credits)
This module examines the fundamental components to the production of design: human interaction and collaboration. Whether this interaction is between client and designer, object and user, or experience and emotion, it allows you to experience provocative challenges that hone your own standpoint. You'll learn how social engagement, polar tension or friction can inspire new thinking.

- MACD 103: Boundaries
(20 credits)
This module allows you to take more radical entry points into your understanding of practice; taking project interest into new forms or creating critical design response from more theorised or experimental catalysts.
Provocateurs will continue to challenge and stretch the limits of your enquiry, exploring new theoretical models and examining the debate of 'designer as author'; how works are translated or used; and how they or their work become the provocateur.

Semester 2: Reconstruction
- MACD 104: Curate and build
(40 credits)
You'll deep dive into your emergent interests, exploring how technology and an increasingly complex consumer and cultural landscape may effect your enquiry. Thinking by doing, you'll elect and develop skill sets and a depth of study in both practice and theory. With the module running across the whole semester, it allows you to fully prepare and test ideas and craft, sectors and media as you begin to prepare your main MA project.

- MACD 105: Compete
(20 credits)
Ahead of the final semester, you'll begin to look at avenues and insights for your own practice and from a business or funding perspective. You'll build professional skills relevant to individual need and examine components of design development including publishing, presentations, production and IP.

The module will also examine other methodologies of delivering work around the world, whether through commission or employment, working in known fields of the creative industries or with museums, arts organisations or universities and research bodies.
Student will also engage in competitive projects set by external bodies.

Semester 3: Reinvention
- MACD 106, MA project
(60 credits)
This module allows you to realise your final major project, in a largely self directed semester, bringing together practice, theory and an evaluation phase that provides reflection and potential industry or funding opportunities to be negotiated ahead of graduating.

The first phase leads to exhibiting at a key industry or cultural event, with an interim show. The second sees you gather insights, industry or critical feedback, or undertake an internship, or preparing for the launch of your project. This final phase sees the production of an essay or strategic report, depending on future plans.

Facilities

- Dedicated MA studio space
- Lecture theatres, design lab, break out spaces and meeting rooms
- Digital printing facilities, Risograph machine, woodblock printing and presses, workshop and negotiated access to screen-printing studios
- Apple suite, with Adobe CS and full collection of Monotype typefaces
- Extensive library facilities and digital collections
- Negotiated use of other facilities such as film, photographic, textiles and product design studios

Staff

You'll be taught by staff with backgrounds spanning design, academic, writing and research careers. They offer decades of experience teaching and working for leading studios, working with international clients, arts and cultural organisations, exhibiting and publishing work and research. They are enaged with many of the world's top creative universities and organisations as keynote speakers, external examiners and consultants. Overall they are all inspired by design, teaching, nurturing and encouraging great and motivated students.

Assessment

- Individual project briefs
- Design research journal
- Essay
- Oral presentations, individually and in groups
- Critical review or business plan

Careers

Communication design is a broad field of study, with career choices depending largely on your own personal project focus.

Options include:

- Graphic design
- Advertising
- Packaging and brand design
- Service design
- Photography and film
- Type design or illustration
- Editorial design
- Motion graphics, interactive or digital design
- Information or UX design
- Design criticism and writing
- Teaching, research or PhD study
- Allied fields: television, the heritage sector or exhibition design

Interview and selection process

Please apply via submission of an application form, an outline of your key interest or masters proposal and a portfolio. Details about our portfolio requirements can be found on the application form.

Interviews are held in person at the School, online via Skype or by phone.

Find out how to apply here - https://myfalmouth.falmouth.ac.uk/urd/sits.urd/run/siw_ipp_lgn.login?process=siw_ipp_app&code1=MACODEFC_SEP&code2=0001

Read less
This course is for designers who want to pursue their passion for particular areas of design, at an advanced level and with professional support. Read more
This course is for designers who want to pursue their passion for particular areas of design, at an advanced level and with professional support.

Course overview

This Masters is built around your personal design interests and aspirations. It allows you to push the boundaries of creativity, within a framework of academic rigour and contextual research.

You can choose to study any of the following areas:
-Advertising
-Animation
-Calligraphy and lettering
-Creative computational design
-Design thinking, innovation and ideation
-Design leadership
-Fashion, product and promotion
-Graphic communication
-Graphic design
-Illustration
-Interactive media
-Motion graphics
-Typographic design

Other specialised design disciplines will also be considered. Our specialist tutors will work with you as you create a portfolio of creative designs that will excite and impress potential employers.

The course includes a theoretical element which contextualises your chosen areas of study within the broader field of design.
By the end of the course, you will have completed a major project that has evolved from your practice and research. The project will be supported by a critical evaluation report.

At Masters level, the specialisms of tutors are an important factor. Our Department offers a wide range of research expertise within design. For example, we host the International Research Centre for Calligraphy (IRCC) which promotes and supports the development of calligraphy both nationally and internationally. We have excellent engagement with industry, locally, nationally and internationally and have several academic partners overseas including Hong Kong, Malaysia and the USA.

Graduates from Sunderland have gone on to work throughout the design industry around the world. A Masters qualification not only opens doors in the workplace but also helps you progress more rapidly once your career is underway.

This course can also be taken part time - for more information, please view this web-page: http://www.sunderland.ac.uk/courses/artsdesignandmedia/postgraduate/design-part-time/

Course content

The content of the course is shaped by your personal interests with guidance and inspiration from Sunderland's supportive tutors and industry speakers and visits.

Modules on this course include:
-Design Studies 1 (60 Credits)
-Design Studies 2 (60 Credits)
-Design Studies 3 (60 Credits)

Teaching and assessment

Compared to an undergraduate course, you will find that this MA Design programme requires a higher level of independent working. The course aims to stretch your creativity and maximise your sense of personal fulfilment.

We use a wide variety of teaching and learning methods, which include lectures, seminars, critiques, workshops and practical demonstrations. These are supported by a range of guest speakers from diverse academic and industry backgrounds. You will also have high levels of contact with tutors who give regular feedback and support.

Facilities & location

Our Design Centre allows you to develop your creativity while taking advantage of state-of-the-art facilities and, importantly, your own workspace. We provide well-equipped facilities and industry-standard design software so it's easy to make a seamless transition from your studies to the workplace. The Design Centre also attracts international exhibitions and conferences, and it provides a highly stimulating environment.

Facilities at the University include:
-Five computer suites incorporating the latest Mac Pros
-Digital design suites using industry standard software like Adobe Creative Suite, Maya and Toon Boom
-Digital SLR and HD video cameras
-Fully equipped Photography studio
-Fully equipped printmaking studio
-Laser cutting machine
-Large format colour printers
-Access to 3D printers and scanners
-Large format digital fabric printer and full garment design and making facilities

Arts and Design Library
Our Arts and Design Library has a specialist collection of over 120,000 books, videos, slides and one of the largest electronic information networks in the sector.

Journals and research
We subscribe to a comprehensive range of print and electronic journals so you can access the most reliable and up-to-date articles. Some of the most important sources for your course include:
-Art Full Text + Art Abstracts, which is a major resource for media and arts information
-Design and Applied Arts Index, which covers journals featuring both new designers and the development of design and the applied arts since the mid-19th century
-British Universities Film and Video Council (BUFVC), which provides resources for the production, study and use of film and related media
-JSTOR (short for ‘Journal Storage’), which provides access to important journals across the humanities, social sciences and sciences
-Lexis, which provides access to legal information as well as full-text newspaper articles
-Screen Online (BFI), which is an online encyclopaedia of British film and television, featuring clips from the vast collections of the BFI National Archive

Employment & careers

Postgraduates are highly employable and, on average, earn more than individuals whose highest qualification is an undergraduate degree. On completing this course, you will be equipped for roles throughout the creative industries.

Potential roles include animator, graphic designer, illustrator, calligrapher, lettering designer, typographic designer, interactive designer, lecturer or broad-based designer.

A Masters degree will also enhance career opportunities within Higher Education and prepare you for further postgraduate studies, such as MPhil or PhDs.

Read less
The Laurea Magistrale (equivalent to a Master of Science) trains professionals with solid engineering foundations, a good scientific approach and a broad range of technical and applied contents. Read more

Mission and goals

The Laurea Magistrale (equivalent to a Master of Science) trains professionals with solid engineering foundations, a good scientific approach and a broad range of technical and applied contents. The level of cultural education is raised during the first year by broadening the knowledge of advanced analysis methods, which in the second year are applied in specialisation subjects and a thesis. The first year is offered in the Milano Bovisa and Lecco campuses with the same study plan (the first year is not available in the Piacenza campus, which offers only the second year). Students can choose different previously approved study plans (PSPA) in the second year. Some are offered in the Milano Bovisa campus (“Impianti e Produzione” [Production Plants and Production], “Meccatronica e Robotica” [Mechatronics and Robotics], “Metodi e Tecniche di Prototipazione Virtuale” [Methods and Techniques for Virtual Prototyping], “Motori e Turbomacchine” [Engines and Turbomachinery], “Progettazione” [Design], “Materiali e Tecnologie Innovative” [Materials and Innovative Technologies] and “Veicoli Terrestri” [Ground Vehicles]). Others are offered in the Lecco campus (“Mechanical Systems Design” and “Industrial Production”) and one in the Piacenza campus (“Macchine Utensili e Sistemi di Produzione” [Machine Tools and Production Systems]).

See the website http://www.polinternational.polimi.it/educational-offer/laurea-magistrale-equivalent-to-master-of-science-programmes/mechanical-engineering/

Career opportunities

Graduates with a Laurea Magistrale (equivalent to a Master of Science) in Mechanical Engineering are technicians who can independently develop the functional, construction and energy-related aspects of innovative products, processes and systems in industry and in the advanced tertiary sector. On passing the State Professional Examination, Mechanical Engineering Graduates with a Laurea Magistrale (equivalent to a Master of Science) can ask to be included in the Register of Engineers (section A).

Presentation

See http://www.polinternational.polimi.it/uploads/media/Mechanical_Engineering_04.pdf
The MSc Programme in Mechanical Engineering – Ingegneria Meccanica provides an academically challenging exposure to modern issues in advanced Mechanical Engineering.
The educational goal of the MSc Programme is to train highly qualified engineers, capable of playing different roles in the job market, by providing them with sound scientific, economic and technical competences, together with broad practical and professional skills needed for a successful career in a technologically advanced and rapidly evolving society.
The specialist in Mechanical Engineering, being involved in the design, production process and operation of products and systems, needs to develop a strong interdisciplinary background in machine design, with respect to functional requirements, dynamic and structural analysis, propulsion and engine systems, fluid mechanics, material properties and selection, manufacturing processes and production systems, operation and management of industrial plants, experimental techniques, mechatronics and industrial automation. The programme is taught in English. http://www.ccsmecc.polimi.it/en

Subjects

The 1st year is organised in the following compulsory modules: Control and Actuating Devices for Mechanical Systems, Applied Metallurgy, Energy Systems, Nonconventional Machining Processes, Machine Design, Mechanical System Dynamics, Mechanical Measurements, Configuration and Management of Production Systems.

In the 2nd year students will have the possibility to specialize the training, by choosing among the following tracks:
Milano Bovisa Campus: Production Systems, Mechatronics and robotics, Virtual prototyping, Internal Combustion Engines and Turbomachinery, Advanced Mechanical Design, Advanced Materials and Technology, Ground Vehicles.
Lecco Campus: Mechanical Systems Design, Industrial Production.
Piacenza Campus: Machine Tools and Manufacturing Systems.

See the website http://www.polinternational.polimi.it/educational-offer/laurea-magistrale-equivalent-to-master-of-science-programmes/mechanical-engineering/

For contact information see here http://www.polinternational.polimi.it/educational-offer/laurea-magistrale-equivalent-to-master-of-science-programmes/mechanical-engineering/

Find out how to apply here http://www.polinternational.polimi.it/how-to-apply/

Read less
The MSt in the History of Design is a taught Master's Degree offered part-time over two years. A tea cup, be it hand-painted porcelain, studio pottery or mass produced ceramic, offers a glimpse of the rituals of everyday life and historical experience. Read more
The MSt in the History of Design is a taught Master's Degree offered part-time over two years.

A tea cup, be it hand-painted porcelain, studio pottery or mass produced ceramic, offers a glimpse of the rituals of everyday life and historical experience. A designed object or space reflects the individual, the society for which it was created, as well as its creator. It expresses aesthetic preoccupations and articulates historical and political conditions. Decoration challenges the hierarchies and contested inter-relationships between the disciplines and careers of artists, designers, crafts workers, gardeners, and architects. Such concerns reside at the heart of the study of the history of design.

This history of design course is taught on nine monthly Saturdays and one residential weekend per annum. The syllabus focuses particularly on the period from 1851 to 1951 in Europe (including Britain) and America. Combining close visual and material analysis with historical methodologies, the course explores decorative and applied art, the design of interiors and public spaces, and for performance and industry.

There will be two Open Mornings, on one Saturday in November 2016 11am - 12.30pm and on one Saturday in February 2017 11am - 12.30pm, where you can meet the Course Director, Dr Claire O'Mahony, and learn more about the course. Please contact usl if you would like to attend including which day you prefer: .

Visit the website https://www.conted.ox.ac.uk/about/mst-in-the-history-of-design

Description

Core themes of the History of Design course will include the rivalries between historicism and modernity; internationalist and nationalist tendencies; handicraft and industrial processes, as well as the analysis of critical debates about the makers and audiences of decoration in advice literature and aesthetic writing.

The programme aims to provide students with a framework of interpretative skills useful to understanding design. It provides grounding in the analysis of the techniques and materials deployed in creating objects or sites. It enables students to develop a grasp of historical context, encompassing the impact of the hierarchies within, and audiences for, the critical reception of 'decoration'. It encourages the analysis of the historiography of political and aesthetic debates articulated by designers, critics and historians about design, its forms and purposes.

Teaching and learning takes a variety of forms in this programme. In keeping with the Oxford ethos, individual tutorials and supervisions will be an important of the course, particularly whilst researching the dissertation, whilst earlier stages of the programme principally take the form of seminar group discussion, lectures and independent study. First-hand visual analysis is an essential component of the discipline of the history of design. As such each course element of the programme includes site visits, both to Oxford University's unique museum and library collections, and to those nearby in London and the regions. Formal assessment is by means of analytical essay and dissertation writing, complemented by informal assessment methods including a portfolio of research skills tasks and an oral presentation about each candidate's dissertation topic.

The monthly format of the programme should enable applicants who are employed or have caring duties to undertake postgraduate study, given they have a determined commitment to study and to undertake independent research.

The University of Oxford offers a uniquely rich programme of lectures and research seminars relevant to the study of Design History. Research specialisms particularly well represented in the Department for Continuing Education are:

- Art Nouveau and Modern French Decoration
- Modernist Design and Architecture
- The Arts and Crafts Movement
- Garden History
- The Art of the Book
- Ecclesiastical Architecture and Design

As a discipline Design History is well represented in conferences organised and academic journals and books published by The Design History Society; the Association of Art Historians; AHRC Centre for the Historic Interior at the Victoria and Albert Museum; the Modern Interior Centre at Kingston University; The Twentieth Century Society; The Garden History Society; The Textile History Society; The Wallpaper Society, The Societe des Dix-Neuviemistes.

Graduate destinations

Future research and career paths might be a DPhil programme; creative industries; museum curatorship; the art market; teaching; arts publishing.

Programme details

- Course structure
The MSt is a part-time course over two years with one residential weekend per annum. Each year comprises nine Saturdays (monthly; three in each of the three terms in the academic year) students will also have fortnightly individual tutorials and undertake research in reference libraries in Oxford between these monthly meetings. The course is designed for the needs of students wishing to study part-time, including those who are in full-time employment but will require 15 to 20 hours of study per week.

- Course content and timetable
The course is based at Rewley House, 1 Wellington Square, Oxford OX1 2JA. Some classes may take place at other venues in Oxford. Class details, reading lists and information about any field trips will be supplied when you have taken up your place.

Core Courses

- Materials and Techniques of Design
- Historical Methods
- Research Project in the History of Modern Design
- Dissertation

Options Courses

- Decoration in Modern France
- The Arts and Crafts Tradition in Modern Britain
- Design in the Machine Age
- Design, Body, Environment
- Visual Cultures of the World Wars
- Academic Writing and Contemporary Practice

Course aims

The MSt was devised with the aim of providing effective postgraduate-level education in history of design on a part-time basis in which case it should be possible to participate fully in the programme while remaining in full-time employment.

The programme aims to provide students with skills:

- To develop further their critical understanding of the principles and practice of the history of design

- To enhance their subject knowledge, analytical and communication skills needed for professional involvement in the history of design

- To demonstrate a grasp of primary evidence to build on their critical understanding of the types of evidence used in the historical study of designed objects and sites and how they are selected and interpreted

- To build on the appropriate skills and concepts for analysing material objects and textural sources

- To enable the student to undertake their own research to be presented in essays, oral presentations and as a dissertation

- To demonstrate an understanding of primary evidence and secondary sources through the application of appropriate analytical skills and concepts within a research context resulting in a dissertation.

Find out how to apply here - http://www.ox.ac.uk/admissions/graduate/applying-to-oxford

Read less
This MSc programme offers you an advanced level of study in specific aspects of mechanical engineering which are in demand from industry. Read more

This MSc programme offers you an advanced level of study in specific aspects of mechanical engineering which are in demand from industry. It is an ideal bridging programme for those graduates seeking to register as a Chartered Engineer with the Institution of Mechanical Engineers.

Course details

You study the core modules in CAD/CAM and Product Development, Finite Element Methods and Machine Design and you select three additional modules from Automotive Engineering and Vehicle Design, Manufacturing Systems, Project Management and Enterprise, Supply Chain Management and Applied Continuum Mechanics.

Professional accreditation

Our MSc Mechanical Engineering is accredited to CEng level by the Institution of Mechanical Engineers under licence from the UK regulator, the Engineering Council. Accreditation is a mark of assurance that the degree meets the standards set by the Engineering Council in the UK Standard for Professional Engineering Competence (UK-SPEC). 

The accredited Masters-level award will provide you with the underpinning knowledge, understanding and skills in preparation for your registration as a Chartered Engineer (CEng). Some employers recruit preferentially from accredited degrees, and an accredited degree is likely to be recognised by other countries that are signatories to international accords.

What you study

For the Postgraduate Diploma (PgDip) award you must successfully complete 120 credits of taught modules. For an MSc award you must successfully complete 120 credits of taught modules and a 60-credit master's research project.

Course structure

Core modules

  • CAD/CAM and Product Developments
  • Finite Element Methods
  • Machine Design
  • Practical Health and Safety Skills
  • Project Management and Enterprise
  • Research and Study Skills

and three optional modules

  • Applied Continuum Mechanics
  • Automotive Engineering and Vehicle Design
  • Manufacturing Systems
  • Supply Chain Management

MSc candidates

  • Project

Modules offered may vary.

Teaching

How you learn

You learn through lectures, tutorials and practical sessions. Lectures provide the theoretical underpinning while practical sessions give you the opportunity to put theory into practice, applying your knowledge to specific problems.

Tutorials and seminars provide a context for interactive learning and allow you to explore relevant topics in depth. In addition to the taught sessions, you undertake a substantive MSc research project.

How you are assessed

Assessment varies from module to module. The assessment methodology could include in-course assignments, design exercises, technical reports, presentations or formal examinations. For your MSc project you prepare a dissertation.

Employability

Mechanical engineers typically secure employment in structural engineering, research and development, automotive engineering and design, the aerospace industry, manufacturing, processing and chemical industries as well as management positions.



Read less
This MSc programme offers you an advanced level of study in specific aspects of mechanical engineering which are in demand from industry. Read more

This MSc programme offers you an advanced level of study in specific aspects of mechanical engineering which are in demand from industry. You study develop knowledge and key skills in CAD/CAM and Product Development, Finite Element Methods and Machine Design and options available include Automotive Engineering and Vehicle Design, Manufacturing Systems, Project Management and Enterprise, Supply Chain Management and Applied Continuum Mechanics.

Course details

There are three routes you can select from to gain a postgraduate Master’s award:

  • MSc Mechanical Engineering – one year full time
  • MSc Mechanical Engineering – two years part time
  • MSc Mechanical Engineering (with Advanced Practice) – two years full time

The one-year programme is a great option if you want to gain a traditional MSc qualification – you can find out more here. This two-year master’s degree with advanced practice enhances your qualification by adding to the one-year master’s programme an internship, research or study abroad experience.

Professional accreditation

Our one-year MSc Mechanical Engineering is accredited to CEng level by the Institution of Mechanical Engineers under licence from the UK regulator, the Engineering Council. Accreditation is a mark of assurance that the degree meets the standards set by the Engineering Council in the UK Standard for Professional Engineering Competence (UK-SPEC). [include Engineering Council logo, Institution of Mechanical Engineers logo]

The accredited Masters-level award will provide you with the underpinning knowledge, understanding and skills in preparation for your registration as a Chartered Engineer (CEng). Some employers recruit preferentially from accredited degrees, and an accredited degree is likely to be recognised by other countries that are signatories to international accords.

The two-year MSc Mechanical Engineering with Advanced Practice incorporates all the elements of the one-year MSc and adds to these the advanced practice module. The new title is being prepared for formal recognition as accredited title. 

What you study

For the MSc with advanced practice, you complete 120 credits of taught modules, a 60-credit master’s research project and 60 credits of advanced practice.

Course structure

Core modules

  • CAD/CAM and Product Developments
  • Finite Element Methods
  • Machine Design
  • Practical Health and Safety Skills
  • Project Management and Enterprise
  • Research and Study Skills
  • Research Project (Advanced Practice)

and two optional modules

  • Applied Continuum Mechanics
  • Automotive Engineering and Vehicle Design
  • Manufacturing Systems
  • Supply Chain Management

Advanced Practice options

  • Research Internship
  • Study Abroad
  • Vocational Internship

Modules offered may vary.

Teaching

How you learn

You learn through lectures, tutorials and practical sessions. Lectures provide the theoretical underpinning while practical sessions give you the opportunity to put theory into practice, applying your knowledge to specific problems. 

Tutorials and seminars provide a context for interactive learning and allow you to explore relevant topics in depth. In addition to the taught sessions, you undertake a substantive MSc research project.

In addition to the taught sessions, you undertake a substantive MSc research project and the Advanced Practice module. This module enables you to experience and develop employability or research attributes and experiential learning opportunities in either an external workplace, internal research environment or by studying abroad. You also critically engage with either external stakeholders or internal academic staff, and reflect on your own personal development through your Advanced Practice experience.

How you are assessed

Assessment varies from module to module. It may include in-course assignments, design exercises, technical reports, presentations or formal examinations. For your MSc project you prepare a dissertation.

Your Advanced Practice module is assessed by an individual written reflective report (3,000 words) together with a study or workplace log, where appropriate, and through a poster presentation.

Employability

Mechanical engineers typically work in structural engineering, research and development, automotive engineering and design, the aerospace industry, manufacturing, processing and chemical industries as well as management positions.



Read less
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 programme 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.



Read less
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. Read more

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.

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.

The Advanced MSc programme offers students a unique opportunity to deepen their learning through an additional 6-10 week internship, followed by an additional two semesters at Design Informatics where students can develop further as reflective practitioners, makers, and innovators.

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.

Year 1:

Compulsory Courses:

  • Design Informatics: Histories and Futures
  • Data Science for Design (not compulsory yet, but strongly recommended for MSc/ Advanced MSc)
  • Case Studies in Design Informatics 1
  • Design with Data
  • Design Informatics Project

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

Elective Courses:

In addition to the compulsory courses, you can choose 1-4 elective courses from the Masters Programmes of the School of Informatics, Edinburgh College of Art, and Philosophy, Psychology, and Language Sciences.

Students in the Advanced MSc programme will complete a 6-10 week internship with a company, charity, government, or third sector organisation over the summer.

Year 2:

Compulsory Courses:

  • Case Studies in Design Informatics 1
  • Dissertation

Elective Courses:

In addition to the compulsory courses, you can choose 2-4 elective courses from the Masters Programmes of the School of Informatics, Edinburgh College of Art, and Philosophy, Psychology, and Language Sciences.

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 deepen their research practice, the course provides a solid foundation for a PhD in related areas.



Read less
This MSc teaches advanced analytical and computational skills for success in a data rich world. Read more

This MSc teaches advanced analytical and computational skills for success in a data rich world. Designed to be both mathematically rigorous and relevant, the programme covers fundamental aspects of machine learning and statistics, with potential options in information retrieval, bioinformatics, quantitative finance, artificial intelligence and machine vision.

About this degree

The programme aims to provide graduates with the foundational principles and the practical experience needed by employers in the area of machine learning and statistics. Graduates of this programme will have had the opportunity to develop their skills by tackling problems related to industrial needs or to leading-edge research.

Students undertake modules to the value of 180 credits.

The programme consists of two core modules (30 credits), four to six optional modules (60 to 90 credits), up to two elective modules (up to 30 credits) and a research project (60 credits). Please note that not all combinations of optional modules will be available due to timetabling restrictions.

Core modules

  • Supervised Learning (15 credits)
  • Statistical Modelling and Data Analysis (15 credits)

Optional modules

Students must choose 15 credits from Group One Options. Of the remaining credits, students must choose a minimum of 30 and a maximum of 60 from Group Two, 15 credits from Group Three and a maximum of 30 credits from Electives.

Group One Options (15 credits)

  • Graphical Models (15 credits)
  • Probabilistic and Unsupervised Learning (15 credits)

Group Two Options (30 to 60 credits)

  • Advanced Deep Learning and Reinforcement Learning (15 credits)
  • Advanced Topics in Machine Learning (15 credits)
  • Applied Machine Learning (15 credits)
  • Approximate Inference and Learning in Probabilistic Models (15 credits)
  • Information Retrieval and Data Mining (15 credits)
  • Introduction to Deep Learning (15 credits)
  • Machine Vision (15 credits)
  • Statistical Natural Language Processing (15 credits)

Group Three Options (15 credits)

  • Applied Bayesian Methods (15 credits)
  • Statistical Design of Investigations (15 credits)
  • Statistical Inference (15 credits)

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

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

Dissertation/report

All MSc students undertake an independent research project, which culminates in a dissertation of 10,000-12,000 words.

Teaching and learning

The programme is delivered through a combination of lectures, discussions, practical sessions and project work. Student performance is assessed through unseen written examinations, coursework, practical application and the project assessment process.

Further information on modules and degree structure is available on the department website: Computational Statistics and Machine Learning MSc

Careers

There is a strong national and international demand for graduates with skills at the interface of traditional statistics and machine learning. Substantial sectors of UK industry, including leading, large companies already make extensive use of computational statistics and machine learning techniques in the course of their business activities. Globally there are a large number of very successful users of this technology, many located in the UK. Areas in which expertise in statistics and machine learning is in particular demand include: finance, banking, insurance, retail, e-commerce, pharmaceuticals, and computer security. Graduates have gone on to further study at, for example, the Universities of Cambridge, Helsinki, Chicago, as well as at UCL. The MSc is also ideal preparation for a PhD, in statistics, machine learning or a related area.

Recent career destinations for this degree

  • Data Scientist, Interpretive
  • Software Engineer, Google
  • Data Scientist, YouGov
  • Research Engineer, DeepMind
  • PhD in Computer Science, UCL

Employability

Scientific experiments and companies now routinely generate vast databases and machine learning and statistical methodologies are core to their analysis. There is a considerable shortfall in the number of qualified graduates in this area internationally. CSML graduates have been in high demand for PhD positions across the sciences. In London there are many companies looking to understand their customers better who have hired our CSML graduates. Similarly graduates now work in companies in, amongst others, Germany, Iceland, France and the US in large-scale data analysis. The finance sector has also hired several graduates recently.

Careers data is taken from the ‘Destinations of Leavers from Higher Education’ survey undertaken by HESA looking at the destinations of UK and EU students in the 2013–2015 graduating cohorts six months after graduation.

Why study this degree at UCL?

The Centre for Computational Statistics and Machine Learning (CSML) is a major European Centre for machine learning having coordinated the PASCAL European Network of Excellence.

Coupled with the internationally renowned Gatsby Computational Neuroscience and the Machine Learning Unit, and UCL Statistical Science, this MSc programme draws on world-class research and teaching talents. The centre has excellent links with world-leading companies in internet technology, finance and related information areas.

The programme is designed to train students in both the practical and theoretical sides of machine learning. A significant grounding in computational statistics is also provided.

Research Excellence Framework (REF)

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

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

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

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



Read less
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. Read more

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.

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.

Compulsory Courses:

  • Design Informatics: Histories and Futures
  • Data Science for Design (not compulsory yet, but strongly recommended for MSc/ Advanced MSc)
  • Case Studies in Design Informatics 1
  • Design with Data
  • Design Informatics Project
  • Dissertation In Design with Data and Design Informatics Project, you are likely to work with an external partner, such as the Royal Bank of Scotland, Edinburgh City Council, or the National Museum of Scotland.

Elective Courses:

In addition to the compulsory courses, you can choose 1-4 elective courses from the Masters Programmes of the School of Informatics, Edinburgh College of Art, and Philosophy, Psychology, and Language Sciences.

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 deepen their research practice, the course provides a solid foundation for a PhD in related areas.



Read less
This course is an innovative collaboration between Manchester School of Art and the Faculty of Science and Engineering at Manchester Metropolitan University. Read more

This course is an innovative collaboration between Manchester School of Art and the Faculty of Science and Engineering at Manchester Metropolitan University. It brings together students from creative and manufacturing backgrounds to foster original approaches to product and furniture design for manufacture whilst exploring personal philosophies and cultural contexts.

Supported by extensive hand, machine and digital workshops across a range of materials, you will investigate and challenge the application and use of materials and processes within making and manufacturing to embrace opportunities for innovation across a breadth of product and furniture design practices.

As part of the wider MA/MFA Design Network, a series of options units are delivered to enable you to further expand your creative agendas and design methodologies.  Within these options, you can choose to develop design ambitions within a business context, through a unit delivered by the Manchester Metropolitan Business School, which cultivates project planning and management skills, raises understanding of markets and marketing opportunities, and highlights the financial factors and concerns that impact on production design decisions within a commercial manufacturing environment.

Features

Graduates will develop theoretical and practical skills suitable for roles in; design consultancy; design for engineering and manufacturing; design management; and design research for industry or academic research and teaching. The programme will also prepare graduates who wish to go on to self-employment, establishing and running their own design/manufacturing businesses.



Read less
The Machine Learning MSc at UCL is a truly unique programme and provides an excellent environment to study the subject. It introduces the computational, mathematical and business views of machine learning to those who want to upgrade their expertise and portfolio of skills in this domain. Read more

The Machine Learning MSc at UCL is a truly unique programme and provides an excellent environment to study the subject. It introduces the computational, mathematical and business views of machine learning to those who want to upgrade their expertise and portfolio of skills in this domain.

About this degree

Students develop an understanding of the principles underlying the development and application of new techniques in this area, alongside an awareness of, and ability to analyse the range and scope of algorithms and approaches available, and design, develop and evaluate appropriate algorithms and methods for new problems and applications.

Students undertake modules to the value of 180 credits.

The programme consists of one core module (15 credits), five to seven optional modules (75 to 105 credits), up to two modules (30 credits) from electives, and a research project (60 credits).

Core modules

  • Supervised Learning (15 credits)

Optional modules

Students must choose 15 credits from Option Group One and a minimum of 60 credits from Option Group Two. Students must choose a further 30 credits from either Option Group Two or approved electives.

Option Group One (choose 15 credits)

  • Graphical Models (15 credits)
  • Probabilistic and Unsupervised Learning (15 credits)

Option Group Two (choose 60 to 90 credits)

  • Advanced Deep Learning and Reinforcement Learning (15 credits)
  • Advanced Topics in Machine Learning (15 credits)
  • Affective Computing and Human-Robot Interaction (15 credits)
  • Applied Machine Learning (15 credits)
  • Approximate Inference and Learning in Probabilistic Models (15 credits)
  • Bioinformatics (15 credits)
  • Information Retrieval and Data Mining (15 credits)
  • Introduction to Deep Learning (15 credits)
  • Machine Vision (15 credits)
  • Programming and Mathematical Methods for Machine Learning (15 credits)
  • Statistical Natural Language Programming (15 credits)

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

Students may select up to 30 credits from elective modules

A list of acceptable elective modules is available on the departmental website.

Dissertation/report

All MSc students undertake an independent research project which culminates in a dissertation of 10,000-12,000 words in the form of a project report.

Teaching and learning

The programme is delivered through a combination of lectures, seminars, class discussions and project supervision. Student performance is assessed though a combination of unseen written examination, coursework (much of which involves programming and/or data analysis), practical application, and the research project.

Further information on modules and degree structure is available on the department website: Machine Learning MSc

Careers

Graduates from this programme have an excellent employment record. Substantial sectors of UK industry, including leading, large companies already make extensive use of intelligent systems techniques in the course of their business activities, and the UK has a number of very successful developers and suppliers of the technology. Students also benefit from strong corporate and academic connections within the UCL Computer Science alumni network.

Graduates have taken machine learning research degrees in domains as diverse as robotics, music, psychology, and bioinformatics at the Universities of Basel, Cambridge, Edinburgh, Nairobi, Oxford and at UCL. Graduates have also found positions with multinational companies such as BAE Systems and BAE Detica.

Recent career destinations for this degree

  • Computer Vision Engineer, ZVR
  • Data Analyst / Data Scientist, Deloitte Data Analytics Group
  • Programmatic Yield Manager and Data Analyst, eBay
  • Data Scientist, dunnhumby
  • PhD in Computer Science, UCL

Employability

Scientific experiments and companies now routinely generate vast databases and machine learning and statistical methodologies are core to their analysis. There is a considerable shortfall in the number of qualified graduates in this area internationally. Machine Learning graduates have been in high demand for PhD positions across the sciences. In London there are many companies looking to understand their customers better who have hired our graduates. Similarly graduates now work in companies in Germany, Iceland, France and the US, amongst other places, in large-scale data analysis. The finance sector has also hired several graduates recently.

Careers data is taken from the ‘Destinations of Leavers from Higher Education’ survey undertaken by HESA looking at the destinations of UK and EU students in the 2013–2015 graduating cohorts six months after graduation.

Why study this degree at UCL?

UCL Computer Science is recognised as a world leader in teaching and research, and our Master's programmes have some of the highest employment rates and starting salaries.

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

This MSc is one of the few leading Master's programmes entirely dedicated to machine learning. It combines a rigorous theoretical academic framework along with specific knowledge of a variety of application fields to fast-track your commercial career or to prepare for PhD research.

Research Excellence Framework (REF)

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

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

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

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



Read less
Learn how to research, design and develop machine learning and autonomous systems technologies. You’ll be prepared for a wide range of careers in industry. Read more

Learn how to research, design and develop machine learning and autonomous systems technologies. You’ll be prepared for a wide range of careers in industry.

Intelligent and autonomous systems are increasingly important in all areas of human life and activity from medicine and space exploration to agriculture and entertainment.

Understanding and developing autonomous systems involves a range of skills and knowledge including designing interactive systems with both human and machine elements, and modelling and building systems that can sense and learn.

Machine learning is at the heart of autonomous and intelligent systems, including computer vision and robotics. It also underpins the recent developments in data analytics across many fields.

You will learn to use new knowledge to solve complex machine learning and autonomous systems problems. You’ll develop a range of skills including the theory of machine learning, artificial intelligence, autonomous systems design and engineering, and the implications for humans of interacting more and more with intelligent and autonomous systems.

You will be taught by academics from the Department of Computer Science with expertise in machine learning, autonomous systems, artificial intelligence and human-computer interaction. This course has been designed in collaboration with the Department of Electronic and Electrical Engineering who offer expertise in robotics.

You will study in a research-led department with a supportive postgraduate community. You’ll learn in our bespoke computer laboratory and be exposed to the latest ideas and technology. The department has strong links to industry both nationally and internationally.

With machine learning and autonomous systems forming an essential part of a number of key industries, our MSc graduates will be highly sought after by employers.

You’ll gain the knowledge and transferable skills for a career in a wide range of industries, or for further study at PhD level. Graduates from the department have gone on to work in a wide variety of sectors, including IT consultancy, software development, banking and education.

Visit the website.



Read less
This course delivers a broad coverage of all major disciplines in Electrical Power, including power electronics, electric drives, electrical machine design and power systems. Read more
This course delivers a broad coverage of all major disciplines in Electrical Power, including power electronics, electric drives, electrical machine design and power systems. It also covers important electrical power themes such as renewable energy systems and electric vehicles.

The Electrical Power MSc covers the following key subject areas:
-Electrical Machines
-Power Electronics
-Electric Drives
-Power System Operation
-Control of Electrical Power

A feature of the course is design of electrical systems for transportation and renewable energy applications. This is a particular specialisation of researchers in the School of Electrical and Electronic Engineering.

You will develop a knowledge of industry standard computer aided design and analysis techniques appropriate to electrical power such as the use of software packages such as MagNet, MATLAB, Simulink, PSpice and ERACS.

Throughout the course you use industry standard test and measurement equipment, experimental hardware, and software packages relevant to the field of electrical and power engineering.

The course comprises a mixture of lectures, tutorials, coursework and practical laboratory classes. You will research a specialist topic of your choice through an in-depth project. Innovative educational techniques are designed to equip you with practical design skills and research methodologies.

As a graduate of this course you are equipped with the knowledge and practical experience to embark on a career as an engineer in the field of Electrical Power. You will also have skills in research and knowledge acquisition and a solid foundation for further postgraduate studies in the field of electrical engineering and power engineering.

Delivery

You take modules to a total value of 180 credits over three semesters. Taught modules, worth 120 credits, take place during the first and second semesters with exams held in January and May/June. An individual project, worth 60 credits, is undertaken over semesters two and three.

Background reading and design work take place during the second semester. The majority of experimental work and preparation of your dissertation takes place during the semester three.

Teaching takes place in lecture theatres equipped with audio visual equipment. Blackboard, a web based Virtual Learning Environment (VLE) supports your taught modules. Practical sessions are in small groups with experts in the field of Power Electronics, Electric Drives, Machines, and Power Systems and in modern laboratory and computing facilities.

Employability

We collect information from our graduates six months after they leave University. This is part of the Destination of Leavers from Higher Education (DLHE) survey that every UK higher education institution takes part in.

Accreditation

The course is accredited by the Institution of Engineering and Technology (IET) and Engineering Council, and therefore provides a good foundation for professional registration.

Read less
Data Science brings together computational and statistical skills and machine learning for data-driven problem solving. Read more

Data Science brings together computational and statistical skills and machine learning for data-driven problem solving. This rapidly expanding area includes deep learning, large-scale data analysis and has applications in e-commerce, search/information retrieval, natural language modelling, finance, bioinformatics and related areas in artificial intelligence.

About this degree

The programme comprises core machine learning methodology and an introduction to statistical science, combined with a set of more specialised and advanced options covering computing and statistical modelling. Projects are offered both within UCL Computer Science and from a range of industry partners.

Students undertake modules to the value of 180 credits.

The programme consists of three compulsory modules (45 credits), four optional modules (75 credits) and a dissertation/report (60 credits).

Core modules

  • Applied Machine Learning (15 credits)
  • Introduction to Machine Learning (15 credits)
  • Introduction to Statistical Data Science (15 credits)

Optional modules

Students must choose 30 credits from Group One options. For the remaining 45 credits, students may choose up to 30 credits from Group Two options or up to 45 credits from Electives.

Group One Options (30 credits)

  • Advanced Deep Learning and Reinforcement Learning (15 credits)
  • Birkbeck College: Cloud Computing (15 credits)
  • Information Retrieval and Data Mining (15 credits)
  • Introduction to Deep Learning (15 credits)
  • Machine Vision (15 credits)
  • Statistical Natural Language Processing (15 credits)
  • Web Economics (15 credits)

Group Two Options (up to 30 credits)

  • Applied Bayesian Methods (15 credits)
  • Decision and Risk (15 credits)
  • Forecasting (15 credits)
  • Statistical Design of Investigations (15 credits)

Electives (up to 45 credits)

  • Affective Computing and Human-Robot Interaction (15 credits)
  • Bioinformatics (15 credits)
  • Computational Modelling for Biomedical Imaging (15 credits)
  • Graphical Models (15 credits)
  • Stochastic Systems (15 credits)
  • Supervised Learning (15 credits)

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

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

Dissertation/report

All students undertake an independent research project which culminates in a dissertation of 10,000-12,000 words.

Teaching and learning

The programme is delivered though a combination of lectures, seminars, class discussions and project supervision. Student performance is assessed through a combination of unseen written examination, coursework (much of which involves programming and/or data analysis), practical application, and the research project.

Further information on modules and degree structure is available on the department website: Data Science and Machine Learning MSc

Careers

Data science professionals are increasingly sought after as the integration of statistical and computational analytical tools becomes more essential to organisations. This is a very new degree and information on graduate destinations is not currently available. However, MSc graduates from across the department frequently find roles with major tech and finance companies including:

  • Google Deepmind
  • Microsoft Research
  • Dunnhumby
  • Index Ventures
  • Cisco
  • Deutsche Bank
  • IBM
  • Morgan Stanley

Employability

Students gain a thorough understanding of the fundamentals required from the best practitioners, and the programme's broad base enables data scientists to adapt to rapidly evolving goals.

Why study this degree at UCL?

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

UCL Computer Science staff have research interests ranging from foundational machine learning and large-scale data analysis to commercial aspect of business intelligence. Our extensive links to companies provide students with opportunities to carry out the research project with an industry partner.

The department also enjoys strong collaborative relationships across UCL; exposure to interdisciplinary research spanning UCL Computer Science and UCL Statistical Science will provide students with a broad perspective of the field. UCL is home to regular machine learning masterclasses and big data seminars.

Research Excellence Framework (REF)

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

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

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

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



Read less

Show 10 15 30 per page



Cookie Policy    X