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University of Cambridge, Full Time Masters Degrees in Computer Science

We have 3 University of Cambridge, Full Time Masters Degrees in Computer Science

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The aim of the course is to provide preparation appropriate for undertaking a PhD programme in computer science. Read more
The aim of the course is to provide preparation appropriate for undertaking a PhD programme in computer science. Students select five taught modules from a wide range of advanced topics in computer science from biomedical information processing to denotational semantics, and from natural language processing to current applications and research in computer security. Students may also choose from a selection of topics borrowed from the Department of Engineering. Additionally, students take a mandatory, ungraded course in Research Skills which includes core and optional topics.

Students also undertake a research project over two terms and submit a project report in mid-June. Research topic selection and planning occurs in the first term and the work is undertaken in subsequent terms. The taught modules are delivered in a range of styles. For example, there are traditional lecture courses, lecture courses with associated practical classes, reading clubs, and seminar style modules.

Visit the website: http://www.graduate.study.cam.ac.uk/courses/directory/cscsmpacs

Course detail

The course aims:

- to give students, with relevant experience at first-degree level, the opportunity to carry out directed research in the discipline;
- to give students the opportunity to acquire or develop skills and expertise relevant to their research interests;
- to provide preparation appropriate for undertaking a PhD programme in computer science;
- to provide the Faculty with an extended period in which to train students and then to judge the suitability of students for PhD study;
- to offer a qualification that is valuable and highly marketable in its own right that equips its graduates with the skills and expertise to play leading roles in industry and the public sector.

By the end of the programme, the students will have:

- a comprehensive understanding of techniques, and a thorough knowledge of the literature, applicable to their chosen area;
- demonstrated some originality in the application of knowledge, together with an understanding of how research and enquiry are used to create and interpret knowledge in their chosen area;
- shown abilities in the critical evaluation of current research and research techniques and methodologies;
- demonstrated some self-direction and originality in tackling and solving problems, and acted autonomously in the planning and implementation of research.

Format

The M.Phil in Advanced Computer Science covers advanced material in both theoretical and practical areas as well as instilling the elements of research practice. It combines lectures, seminars and project work in various combinations tailored to the individual student. Students choose a from an extensive list of topics.

Assessment

- Thesis -

All students submit a research project on a topic approved by the Degree Committee, of no more than 15,000 words (excluding bibliography, photographs and diagrams but including tables, footnotes, and appendices), to the Secretary of the Degree Committee no later than 12:00 noon on the second Friday in June.

- Individual modules may include a final assessment piece by an essay or a mini-project report of up to 5,000 words.
- Individual modules may include weekly assignments of up to 1,500 words.
- Individual modules may be assessed by written in-class test or by take-home test.
- Students taking modules borrowed from the Engineering Tripos, Part IIB, may be required to take written examinations in Easter Term.
- Modules offered by the Computer Laboratory may be assessed by written in-class test or by take-home test.
- Modules may also include a proportion of practical assessment.
- Modules may include a proportion of assessment of student presentations and participation in reading group discussion.
- Modules may also include a proportion, not more than 20% of the overall assessment, of ungraded exercises which are assessed on a Pass/Fail basis.
- The examination may include, at the discretion of the Examiners, an oral examination on the work submitted by the candidate, and on the general field of knowledge within which such work falls.

Continuing

The minimum requirement for continuation to the PhD programme in Computer Science is that MPhil students achieve an overall Pass in the taught modules and, separately, the project. Continuation is dependent on the approval of the Department and Degree Committee.

How to apply: http://www.graduate.study.cam.ac.uk/applying

Funding Opportunities

The Department has limited funds to support partial and full scholarships for UK and eligible EU students. Applicants will automatically be considered for these awards. Since only limited funds are available, applicants should not rely on receiving financial support from the Department and should explore all available funding opportunities.

General Funding Opportunities http://www.graduate.study.cam.ac.uk/finance/funding

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The MPhil programme in Scientific Computing is a full-time 12-month course which aims to provide education of the highest quality at Master’s level. Read more
The MPhil programme in Scientific Computing is a full-time 12-month course which aims to provide education of the highest quality at Master’s level. Covering topics of high-performance scientific computing and advanced numerical methods and techniques, it produces graduates with rigorous research and analytical skills, who are well-equipped to proceed to doctoral research or directly into employment in industry, the professions, and the public service. It also provides training for the academic researchers and teachers of the future, encouraging the pursuit of research in computational methods for science and technology disciplines, thus being an important gateway for entering PhD programmes containing a substantial component of computational modelling.

See the website http://www.graduate.study.cam.ac.uk/courses/directory/pcphmpscm

Course detail

The MPhil in Scientific Computing has a research and a taught element. The research element is a project on a science or technology topic which is studied by means of scientific computation. The taught element comprises of core lecture courses on topics of scientific computing and elective lecture courses relevant to the science or technology topic of the project. Most of the projects are expected to make use of the University’s High Performance Computing Service.

The students will attend lecture courses during Michaelmas Term (some courses may be during Lent Term) and then they will undertake a substantial Research Project over the next 6 months (from March to the end of August) in a participating Department. The research element aims to provide essential skills for continuation to a PhD programme or employment, as well as to assess and enhance the research capacity of the students. It is based on a science or technology topic which is studied by means of scientific computation. Research project topics will be provided by academic supervisors or by the industrial partners who are working with the participating Departments and may be sponsoring the research project.

There is equal examination credit weighting between the taught and the research elements of the course, which is gained by submitting a dissertation on the project and by written assignments and examinations on the core and elective courses, respectively.

Weighting of the assessed course components is as follows: Dissertation (research) 50%; written assignments on the core courses 25%; written examinations on the elective courses 25%.

Learning Outcomes

By the end of the course, students will have:

- a comprehensive understanding of numerical methods, and a thorough knowledge of the literature, applicable to their own research;
- demonstrated originality in the application of knowledge, together with a practical understanding of how research and enquiry are used to create and interpret knowledge in their field;
- shown abilities in the critical evaluation of current research and research techniques and methodologies;
- demonstrated self-direction and originality in tackling and solving problems, and acted autonomously in the planning and implementation of research.

Format

The taught element comprises core lecture courses on topics of all aspects of scientific computing, and elective lecture courses relevant to the topic of the research project.

The taught element comprises core lecture courses on topics of all aspects of scientific computing, and elective lecture courses relevant to the topic of the research project. There is equal examination credit weighting between the taught and the research elements of the course, which is gained by submitting a dissertation on the project and by written assignments and examinations on the core and elective courses, respectively. Weighting of the assessed course components is as follows: Dissertation (research) 50%; written assignments 25%; written examinations 25%.

The core lectures are on topics of high performance scientific computing numerical analysis and advanced numerical methods and techniques. They are organized by the Centre for Scientific Computing and are taught and examined during the first five months (October-February). Their purpose is to provide the students with essential background knowledge for completing their dissertation and for their general education in scientific computing.

In particular, their objective is to introduce students to the simulation science pipeline of problem identification, modelling, simulation and evaluation - all from the perspective of employing high-performance computing. Numerical discretisation of mathematical models will be a priority, with a specific emphasis on understanding the trade-offs (in terms of modelling time, pre-processing time, computational time, and post-processing time) that must be made when solving realistic science and engineering problems. Understanding and working with computational methods and parallel computing will be a high priority. To help the students understand the material, the lecturers will furnish the courses with practical coursework assignments.

The lectures on topics of numerical analysis and HPC are complemented with hands-on practicals using Linux-based laptops provided by the course (students may bring their own), as well as on the University’s High Performance Computing Service.

Appropriate elective lecture courses are selected from Master’s-level courses offered by the Departments of the School of Physical Sciences, Technology or Biological Sciences. The choice of courses will be such as to provide the students with essential background knowledge for completing their theses and for their general education in the materials science application of the project. They are decided in consultation with the project supervisor. While every effort is made within the Departments to arrange the timetable in a coherent fashion, it is inevitable that some combinations of courses will be ruled out by their schedule, particularly if the choices span more than one department.

Continuing

For continuation to a PhD programme in Scientific Computing, students are required to gain a Distinction (overall grade equal or greater than 75%).

How to apply: http://www.graduate.study.cam.ac.uk/applying

Funding Opportunities

There are no specific funding opportunities advertised for this course. For information on more general funding opportunities, please follow the link below.

General Funding Opportunities http://www.graduate.study.cam.ac.uk/finance/funding

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This is a twelve-month MPhil programme, taught from within our Information Engineering Division, with a unique, joint emphasis on both machine learning and on speech and language technology. Read more
This is a twelve-month MPhil programme, taught from within our Information Engineering Division, with a unique, joint emphasis on both machine learning and on speech and language technology. The course aims: to teach the state of the art in machine learning, speech and language processing; to give students the skills and expertise necessary to take leading roles in industry; to equip students with the research skills necessary for doctoral study.

See the website http://www.graduate.study.cam.ac.uk/courses/directory/egegmpmsl

Course detail

By the end of the programme, students will have acquired:

- a knowledge of the fundamental techniques in machine learning and how to apply these techniques to a range of practical problems;
- a deep understanding of the fundamental problems in speech and language processing and the technologies that form the current state-of-the art;
- a comprehensive understanding of techniques, and a thorough knowledge of the literature, applicable to the area of their chosen research topic;
- presentation skills through presenting their research in progress;
- the methodological and other technical skills necessary for research in their chosen area;
- the ability to critically assess the technical literature in machine learning and speech and language processing and related topics;
- directly marketable skills in computing, speech and language processing, machine learning, and the data sciences;
- collaborative skills through working with other students on the practical exercises and with PhD students and Research Assistants while carrying out their research project;
- experience in large-scale computing for machine learning and speech and language processing;
- an understanding of how to define and conduct a research project.

Format

Students will spend the Michaelmas and Lent terms undertaking taught course modules. There will be an equivalent of ten 'full' core modules (ie, equivalent to a 16 lecture course), in addition to an elective option which can be chosen from a broad variety of modules. From mid-Lent term through the end of the course, students will conduct a substantial research project leading to a dissertation.

The taught modules will be in a range of styles: traditional lecture courses, lecture courses with associated practical classes, reading clubs, and seminar style modules. The course will emphasize coursework in several of the taught modules. Software projects aimed at implementing algorithms and modelling methods will be central to the practical modules and the research project.

Students can expect to receive reports at least termly on the Cambridge Graduate Supervision Reporting System. They will receive comments on items of coursework, and will have access to a University supervisor for their dissertation. All students will also have personal access to the Course Director and the other staff delivering the course.

Assessment

Students will write a dissertation of no more than 15,000 words. An oral presentation will be compulsory, and will contribute to the assessment of the dissertation.

Several of the core courses are examined wholly or mainly through coursework. Some elective options will also be examined through coursework.

Several of the core courses are examined wholly or mainly through written examination. Some of the elective options will also be examined through written examination.

At the discretion of the Examiners, candidates may be required to take an additional oral examination on the work submitted during the course, and on the general field of knowledge within which it falls.

Continuing

Students wishing to apply for continuation to the PhD would normally be expected to attain an overall mark of 70%.

How to apply: http://www.graduate.study.cam.ac.uk/applying

Funding Opportunities

There are no specific funding opportunities advertised for this course. For information on more general funding opportunities, please follow the link below.

General Funding Opportunities http://www.graduate.study.cam.ac.uk/finance/funding

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