collageThe MSc is designed to combine theory and practice. It teaches the advanced techniques and ideas that are being developed in application domains (such as machine learning, verification and computer security) and the rich and diverse theories that underpin them. These include models of computation and data, and mathematical analysis of programs and algorithms.
The course aims:
- to provide a foundation for research into the theory and practice of programming and the design of computer-based systems;
- to present knowledge, experience, reasoning methods and design and implementation techniques that are robust and forward-looking;
- to provide the foundation for a professional career in the computing-based industries, including telecommunications, process control, business-, mission-, and safety-critical fields; and
- to enhance the skills of a professional who is already working in one of these industries.
The Department of Computer Science is committed to the development and application of effective theory based on realistic practice, and some of the modules were developed through consultation and collaboration with industry. The department believes that only by the interplay of theory and practice can you be trained properly in such a rapidly advancing subject. Practice alerts us to real contemporary problems – theory is a shield against professional obsolescence.
Entrants to the course will come from either a computer science or mathematical background. You may be a recent graduate in computer science and will supplement your knowledge with the kind of sound mathematical basis which is not always found in undergraduate courses. If you are a graduate in mathematics you will apply your training in the context of a rigorous application of the fundamental techniques of computer science.
You will develop knowledge and understanding of a formal disciplined approach to computer science, a range of relevant concepts, tools and techniques, the principles underpinning these techniques and the ability to apply them in novel situations. On subsequent employment, you will be able to select techniques most appropriate to your working environment, adapt and improve them as necessary, establish appropriate design standards for both hardware and software, train colleagues and subordinates in the observance of sound practices, and keep abreast of research and development.
Course outline
The academic year is split into three terms of eight weeks but work on the MSc course continues throughout the year and is not restricted just to term time. During the three terms of the course, you will choose from modules on various aspects of computer science. Most modules will last for one term and will be between 16 to 24 lectures. In addition, all modules will have problem classes and some may also have practical sessions associated with them. In the third term (Trinity term) you will undertake a dissertation.
A typical week for a student taking three courses in each of the first two terms may be as follows:
- Lectures – eight hours
- Tutorial classes – three hours
- Practicals – four hours
- Self-directed study, including preparatory reading, problem sheets, revision of material – 20 hours
Total – 36 hours
The split of work may differ depending on whether a course has practicals associated. This should be taken as a guide only.
Examples of modules offered:
- Advanced Security
- Advanced Topics in Machine Learning
- Quantum Computer Science
- Categories, Proofs and Processes
- Computational Complexity
- Database Systems Implementation
- Computational Learning Theory
- Probabilistic Model Checking
Masters of Science in Computer Science in Cambridge United Kingdom
A Master of Science, or a Master’s degree in Science is an academic degree delivered by Universities in many countries. A Master of Science is a popular choice after completing a Bachelor’s degree.
Although the foundations for computer science have existed for years, it wasn’t until the past century that the most leading technology has been developed. In the 1940s, more exact computing machines were created.
The United Kingdom of Great Britain and Northern Ireland, commonly known as the United Kingdom and Britain, is a sovereign state located off the north-western coast of continental Europe.The two most famous (and oldest) universities are Oxford and Cambridge (often referred to as Oxbridge by many Britons) England also has several other world-class institutions, including several in London (notably Imperial College, the London School of Economics, University College London and King’s College London, all are part of London University)
Cambridge, university town with around 130 thousand students, is proud to be home to University of Cambridge, founded in early 13th century and constantly ranked as one of top 5 universities in the world. There is also Anglia Ruskin University.
University of Cambridge Masters Degrees in Computer Science
MPhil in Advanced Computer Science
About the course
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 networking and systems measurements to category theory, and topics in natural language processing. 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 early 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.
The course aims to:
- give students, with relevant experience at a first-degree level, the opportunity to carry out directed research in the discipline;
- give students the opportunity to acquire or develop skills and expertise relevant to their research interests;
- provide preparation appropriate for undertaking a PhD programme in computer science;
- provide the Faculty with an extended period in which to train students and then to judge the suitability of students for PhD study; and
- 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 industrial and public-sector research.
Learning Outcomes
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; and
- demonstrated some self-direction and originality in tackling and solving problems, and acted autonomously in the planning and implementation of research.
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. The pass mark is 60 per cent; however, higher minimum requirements may be set at the discretion of the Department and Degree Committee. Continuation to the PhD degree is dependent on the approval of the Department and Degree Committee.
Open Days
The Open Day usually takes place at the beginning of November. The event is suitable for those considering applying for postgraduate study at the University. It provides opportunities to meet with academics, explore the Colleges, and find out more about the application process and funding opportunities. Visit the Postgraduate Open Day page for more details.
Teaching
The MPhil 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 five modules from an extensive list of topics.
Placements
Research placement opportunities may be available between finishing the MPhil and commencing the PhD.
Feedback
Students receive feedback on all graded coursework. This may include oral and electronic feedback as well as more detailed written feedback. Results from in-class and take-home written tests are provided in termly letters.
Students receive regular project supervisions throughout the second and third terms and assistance from the supervisor in the selection of a research project in the first term.
Course advisers and project supervisors provide progress feedback via formal termly reports.
Assessment
Thesis / Dissertation
All students submit a research project on a topic approved by the Degree Committee, of no more than 15,000 words (excluding bibliography, photographs, diagrams and data listings, but including tables, footnotes, and appendices).
Essays
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.
The Degree Committee will publish a list of available modules in each year, with accompanying information about the form of assessment for each module.
Written examination
Students taking a borrowed module from Engineering Tripos, Part IIB, may be required to take written examinations in Easter term. This option is available only in special circumstances.
Modules offered by the Department of Computer Science and Technology may be assessed by written in-class test or by take-home test.
Practical assessment
Modules may include a proportion of practical assessment.
Other
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 per cent 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.
Visit the MPhil in Advanced Computer Science page on the University of Cambridge website for more details!
Entry Requirements
Applicants for this course should have achieved a UK First class Honours Degree.
If your degree is not from the UK, please check International Qualifications to find the equivalent in your country.
The first-class honours degree, or equivalent, should be in computer science. Alternatively, applications will be considered from those holding a degree of equal status in engineering, science, mathematics, or another numerate degree, and where the applicant can demonstrate significant relevant preparation for the Cambridge MPhil course.
Mathematics to A-level standard or equivalent and programming experience will be presumed.
MSt in Artificial Intelligence Ethics and Society
About the course
Artificial intelligence (AI) technology is rapidly developing and is increasingly being applied across sectors, posing significant ethical and societal challenges. There is therefore a national and global need to adequately equip future leaders and decision-makers to address these challenges. The Masters of Studies in AI Ethics and Society addresses this need. The MSt is an academically rigorous part-time programme aimed at professionals from business, public, and social sectors working with AI. The programme will provide students with the critical skills, knowledge and analytical abilities needed to identify and address ethical challenges as they arise in practice from the application of AI. The MSt will engage with the ethical and societal challenges of AI and is thoroughly informed by the knowledge, theories and methods of established academic disciplines from philosophy to computer science.
The MSt AI Ethics and Society is developed and taught by the University’s Leverhulme Centre for the Future of Intelligence (LCFI), a global research centre at the forefront of AI Ethics and impact research, in partnership with the Institute of Continuing Education. Because the programme is run by a specialist research centre, rather than by a department, the curriculum is uniquely multidisciplinary, informed by up-to-the-minute research developments, and incorporates experts from diverse areas, including philosophy, machine learning, computer science, policy, law, and more. Visit http://lcfi.ac.uk/master-ai-ethics/ for more information on the Leverhulme Centre for the Future of Intelligence.
Education Aims
The programme aims to equip students with the skills and knowledge necessary to address the ethical and societal challenges arising from the use of Artificial Intelligence. It provides a professionally relevant teaching and learning environment informed by the forefront of academic research on AI and its ethical and societal impacts.
The programme will:
- Ensure that engagement with the ethical and societal challenges of AI is thoroughly informed by the knowledge, theories and methods of relevant established academic disciplines
- Provide a critical overview of the state of current interdisciplinary research on the challenges of AI
- Develop the critical research skills and analytical abilities needed to identify and address ethical challenges as they arise in practice from applications of AI
- Instil thorough knowledge of the role that different governance approaches can play in navigating the challenges of AI, and the ability to critically analyse those approaches
- Develop experts in the ethical and societal implications of AI with the ability and initiative to identify and address the challenges of AI across sectors and society
- Create a network for such experts to collaborate and continue learning as leaders in the field of AI ethics and governance
Learning outcomes
Knowledge and Understanding
By the end of this programme, students will be able to:
- Discuss the ethical and societal challenges of AI with a full understanding of its history and its relationship to other disciplines and technologies
- Identify the capabilities of current AI systems, their key applications and the potential ethical and societal challenges of those applications
- Evaluate key ethical and societal challenges arising from the use of AI and the existing critical literature
- Apply theories and methodologies from a range of established disciplines and demonstrate their use in addressing ethical and societal challenges raised by AI
- Analyse the strengths and weaknesses of current governance approaches for addressing the challenges posed by AI
- Apply the systematic understanding of AI ethics and governance to develop new insights
Skills and other attributes
By the end of this programme, students will be able to:
- Synthesise and analyse research and advanced scholarship across disciplines
- Put theoretical and academic knowledge into practice
- Structure extended pieces of written work and present arguments clearly and effectively
- Plan and implement an independent research project
- Deal with complex issues both systematically and creatively, and show originality in tackling and solving problems
Residentials in Cambridge
Students are expected to attend all week-long residentials in Cambridge, as follows:
- 27 September – 1 October 2021
- 10 – 14 January 2022
- 20 – 24 June 2022
- 12 – 16 September 2022 (tbc)
See website for module information.
Assessment
Assignments on the MSt are divided into two components: the essays, taken as a group, and the dissertation.
The modules are assessed as follows:
● Module 1: 2,000 word essay (8% of final grade)
● Modules 2, 3 and 4: 4,500 word essay each (14% each of final grade)
All summative assessment is compulsory. Students will receive continual formative feedback throughout the course using a variety of strategies and techniques, including evidence of regular reflection.
In the second year (module 5), students will write a 15,000 word dissertation which accounts for 50% of the final grade.
Visit the MSt in Artificial Intelligence Ethics and Society page on the University of Cambridge website for more details!
Entry Requirements
Applicants are normally expected to a hold a 2i degree or higher from a UK university or an equivalent from an overseas university in a relevant subject.
If your degree is not from the UK, please check International Qualifications to find the equivalent in your country.
Applicants to the programme are expected to demonstrate proficiency in the English language; students whose first language is not English must be able to satisfy the current English Language Competence requirements of the University’s Board of Graduate Studies in the year in which they apply for admission to the course.
MPhil in Scientific Computing
About the course
The MPhil programme in Scientific Computing is based in the Department of Physics and 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 postgraduates with rigorous research and analytical skills, who are well equipped to proceed to doctoral research or directly into employment in industry, the professions, and 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.
The course 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 undertake a substantial research project over the following six months (from March to 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 maybe 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.
The weighting of the assessed course components is as follows: dissertation (research) 50 per cent; written assignments on the core courses 25 per cent; and written examinations 25 per cent.
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; and
- demonstrated self-direction and originality in tackling and solving problems, and acted autonomously in the planning and implementation of research.
Continuing
Students wishing to progress to PhD study after passing the Masters degree should reapply for admission to a PhD through the University admissions website, taking the funding and application deadlines into consideration.
Open Days
The Department of Physics participates in the University of Cambridge’s Postgraduate Open Day.
The Open Day usually takes place at the beginning of November. The event is suitable for those considering applying for postgraduate study at the University. It provides opportunities to meet with academics, explore the Colleges, and find out more about the application process and funding opportunities. Visit the Postgraduate Open Day page for more details.
Teaching
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 per cent; written assignments 25 per cent; and written examinations 25 per cent.
The core lectures are on topics of high-performance scientific computing, numerical analysis and advanced numerical methods and techniques. They are organised by the Centre for Scientific Computing and are taught and examined during the first five months (October–February). Their purpose is to provide students with essential background knowledge for completing their dissertation and for their general education in scientific computing.
Feedback
Feedback on the student’s performance on their examination and on the written assignment results is provided by the course director; feedback on their research project progress is provided by their research project supervisor. Students receive written termly progress reports.
Postgraduate students are represented on the Department’s Postgraduate Student Consultative Committee, which normally meets five times a year, and consists of one or more student representatives from each of the research groups. The committee exists to enable discussion of any issue affecting postgraduate studies and students may approach any member of the committee to suggest items for discussion.
Assessment
Thesis / Dissertation
The topic of the project (and hence the choice of supervisor) should fall within the research interests of the groups within the departments of the schools of Physical Sciences, Technology and Biological Sciences. The project is supervised by a member of the research groups of the departments of the school. To gain examination credit for the research element (50 per cent credit towards the degree), students have to submit in August a 15,000-word (maximum) dissertation on a substantial project of original research.
The viva voce examination of the dissertation will take place during September, conducted by two examiners and carried out according to the relevant University regulations. The assessment of the projects is based on the candidate’s understanding of the background literature, the commitment of the candidate to the project, the degree of originality shown in the research and the degree of rigour applied in justifying any conclusions.
Visit the MPhil in Scientific Computing page on the University of Cambridge website for more details!
Entry Requirements
Applicants for this course should have achieved a UK High II.i Honours Degree.
If your degree is not from the UK, please check International Qualifications to find the equivalent in your country.
Applicants’ first degree should be in science or a technology discipline, and applicants are expected to be able to demonstrate an adequate level of computer literacy (should be able to write code performing a science or maths application using a high-level computing language).
Postgraduate Certificate in Healthcare Data and Informatics
About the course
Cambridge is a world-leading centre for innovation in electronic patient and clinical trial data. This is underpinned by an extensive and vibrant community of clinicians, researchers, entrepreneurs, and commercial and public sector organisations. There is a recognised shortage of the appropriate technical and practical skills in the workforce to effectively utilise the opportunities presented by healthcare data.
This Postgraduate Certificate has been designed to provide an introduction to the research skills, governance and innovation needed to work successfully with healthcare data. In addition students will be equipped with the skills necessary to understand how healthcare data relates to populations, health conditions and clinical outcomes and learn how to work with healthcare data in an effective manner.
Aims of the course
The programme will develop individuals with the necessary knowledge and skills to be able to understand and critically evaluate electronic healthcare data and its application for healthcare research.
The course will:
- Provide professionally relevant teaching and learning of the knowledge and skills at the forefront of the successful understanding and utilisation of electronic healthcare data.
- Develop healthcare data experts with the necessary expertise, and originality of application, to pursue and expand their roles in the rapidly evolving environment of healthcare data.
- Promote a comprehensive understanding of the practical and ethical considerations relevant to healthcare data and informatics.
- Ensure a systems-based approach to the critical analysis and development of improvements in healthcare systems.
- Provide work-relevant learning around the current problems, best-practice, challenges and potential solutions in the use of healthcare data.
- Create a professional network of like-minded individuals as leaders in the field of healthcare data.
- Provide students with the skills and knowledge to make value-based judgments around how to extract, refine, and structure data to permit effective healthcare research.
Teaching
This is a part-time course designed to fit with the demands of full-time employment. The course is delivered through a combination of face-to-face sessions requiring attendance in Cambridge, self-directed learning and supported through a virtual online environment [VLE].
It is structured across the following two units of work:
Unit 1: Research skills, governance and innovation, 20 credits;
Unit 2: Data structures, storage, and queries, 40 credits;
Each 20 credits of study is roughly equivalent to 200 hours of study which will consist of face to face teaching, blended, and self-directed learning. This is an indicative amount and it is recognised that individuals may engage in greater or lesser amounts of study for each unit.
Feedback
This is a part-time course with a combination of face-to-face delivery and self-directed learning designed to be compatible with full-time work.
Students will receive formative and peer-based feedback throughout the course, along with tutor provided feedback on the submitted summative assignments
Assessment
Essays, projects & written papers
Units will use summative assessment approaches designed to ensure experiential learning and work-based real-life relevance.
Approaches may include, but are not limited to: critical analysis of case-studies, assessment of evidence-based portfolios, assessment of work and sector relevant group presentations and projects, short answer questions, essays, and the ability to handle, analyse and visualise unseen datasets.
Visit the Postgraduate Certificate in Healthcare Data and Informatics page on the University of Cambridge website for more details!
Entry Requirements
Applicants for this course are expected to have achieved a UK 2.i honours degree or equivalent.
It is preferred that an applicants first degree be in a subject relevant, or related to, life sciences, medical sciences, computational or data science.
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