(MSc) Master of Science
Cloud Computing
Withdrawn
University of Essex
University of Essex
Computer Science and Electronic Engineering (School of)
Colchester Campus
Masters
Full-time or part-time
None
None
None
MSC G42524
10/05/2023
Details
Professional accreditation
Accredited by BCS, the Chartered Institute for IT for the purposes of partially meeting the academic requirement for registration as a Chartered IT Professional.
Accredited by BCS, the Chartered Institute for IT on behalf of the Engineering Council for the purposes of partially meeting the academic requirement for registration as a Chartered Engineer.
Accredited by the Institution of Engineering and Technology (IET) on behalf of the Engineering Council as meeting the requirements for Further Learning for registration as a Chartered Engineer. Candidates must hold a CEng accredited BEng/BSc (Hons) undergraduate first degree to comply with full CEng registration requirements.
Admission criteria
Applicants with a 2:2 degree in one of the following subjects (with no module requirements):
- Computer Science
- Computer Engineering
- Computer Networks
- Computer Games
- Computing
- Software Engineering
We will consider applicants with any other 2:2 degree or above which include one or more modules from this list:
One computing module such as:
- Database
- Web Development
- Software Engineering
- Operating System
- Computer Architecture
- Computer Systems
AND One or more maths modules, such as:
- Mathematics
- Calculus
- Algebra
- Differential Equations
- Probability and Statistics
AND One or more signal and systems modules such as:
- Signal and systems
- Control theory
- Computer systems
- Embedded systems
- Microprocessors
- Automation and control engineering
- Control technology
- System hardware fundamentals
- Control engineering
- Another relevant signal and systems module
AND Two or more programming modules from the following list:
- C
- C#
- C++
- Java
- Python
- MATLAB
- Object oriented programming / OOP
- Advanced programming
- Introduction to programming
- Programming languages
- Software Engineering
- System Programming
- Algorithms
- Data Structures
- Programming Elements
IELTS (International English Language Testing System) code
IELTS 6.0 overall with a minimum component score of 5.5
If you do not meet our IELTS requirements then you may be able to complete a pre-sessional English pathway that enables you to start your course without retaking IELTS.
Additional Notes
The University uses academic selection criteria to determine an applicant’s ability to successfully complete a course at the University of Essex. Where appropriate, we may ask for specific information relating to previous modules studied or work experience.
Course qualifiers
A course qualifier is a bracketed addition to your course title to denote a specialisation or pathway that you have achieved via the completion of specific modules during your course. The
specific module requirements for each qualifier title are noted below. Eligibility for any selected qualifier will be determined by the department and confirmed by the final year Board of
Examiners. If the required modules are not successfully completed, your course title will remain as described above without any bracketed addition. Selection of a course qualifier is
optional and student can register preferences or opt-out via Online Module Enrolment (eNROL).
None
Rules of assessment
Rules of assessment are the rules, principles and frameworks which the University uses to calculate your course progression and final results.
Additional notes
Please refer to the full time version of this course for information on Core and Compulsory modules.
External examiners
External Examiners provide an independent overview of our courses, offering their expertise and help towards our continual improvement of course content, teaching, learning, and assessment.
External Examiners are normally academics from other higher education institutions, but may be from the industry, business or the profession as appropriate for the course.
They comment on how well courses align with national standards, and on how well the teaching, learning and assessment methods allow students to develop and demonstrate the relevant knowledge and skills needed to achieve their awards.
External Examiners who are responsible for awards are key members of Boards of Examiners. These boards make decisions about student progression within their course and about whether students can receive their final award.
Programme aims
MSc Cloud Computing is a programme of study designed for graduates with a first degree in computer science.
Its main aims are:
1. To prepare students for careers in advanced research and/or development environments by extending their knowledge and skills in the specialisation of cloud computing.
2. To develop the students' ability to make a critical evaluation of the theories, techniques, tools and systems used in cloud computing.
3. To enable students to contribute to future developments in their field by providing them with an understanding of recent advances and current research activity.
4. To develop the students' ability to undertake research by providing appropriate resources and guidance in their use.
5. To develop the students' ability to make an effective contribution to team-based activity to encourage students to adopt an investigative approach and develop autonomous study skills in order to assist their continuing professional development.
Learning outcomes and learning, teaching and assessment methods
On successful completion of the programme a graduate should demonstrate knowledge and skills as follows:
A: Knowledge and understanding
A1: A comprehensive understanding of the relevant scientific principles of the specialisation.
A2: A critical awareness of current problems and/or new insights most of which is at, or informed by, the forefront of the specialisation.
A3: Knowledge and understanding of cloud based systems and the technologies that support it.
Learning methods
Lectures are the principal method of delivery for the concepts and principles involved in the majority of the learning outcomes.
Students are also directed to reading from textbooks, academic papers and material available on-line.
Understanding is reinforced by means of exercise classes, discussion groups, laboratories, assignments and project work.
Specialist knowledge is further developed during supervision of the individual dissertation.
Assessment methods
Achievement of knowledge outcomes is assessed primarily through unseen closed-book examinations, and also through marked coursework.
An assessment of the understanding of underlying concepts and principles forms part of the overall assessment of the individual dissertation report and oral presentation.
B: Intellectual and cognitive skills
B1: Understanding of concepts relevant to the discipline, some from outside engineering, and the ability to evaluate them critically and to apply them effectively, including in engineering projects.
B2: Ability both to apply appropriate engineering analysis methods for solving complex problems in engineering and to assess their limitations.
B3: Ability to use fundamental knowledge to investigate new and emerging technologies.
B4: Knowledge, understanding and skills to work with information that may be incomplete or uncertain, quantify the effect of this on the design and, where appropriate, use theory or experimental research to mitigate deficiencies.
B5: Knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations.
B6: Apply engineering design principles to cloud based systems.
Learning methods
The basis for intellectual skills is provided in lectures, and they are developed by means of recommended reading, guided and self directed study, assignments and project work.
Assessment methods
Achievement of intellectual skills is assessed primarily through unseen closed-book examinations, and also through marked assignments and project work.
C: Practical skills
C1: Ability to collect and analyse research data and to use appropriate engineering analysis tools in tackling unfamiliar problems, such as those with uncertain or incomplete data or specifications, by the appropriate innovation, use or adaptation of engineering analytical methods.
C2: Advanced level knowledge and understanding of a wide range of engineering materials and components.
C3: A thorough understanding of current practice and its limitations, and some appreciation of likely new developments.
C4: Ability to apply engineering techniques taking account of a range of commercial and industrial constraints
C5: Ability to design, construct and analyse cloud based systems.
Learning methods
Practical skills are developed in exercise classes, laboratory classes, assignments and project work.
Assessment methods
Achievement of practical skills is assessed through marked coursework, project reports, oral presentations and demonstrations of completed systems.
D: Key skills
D1: Ability to generate an innovative design for products, systems, components or processes to fulfil new needs.
D2: Awareness of the need for a high level of professional and ethical conduct in engineering.
D3: Awareness that engineers need to take account of the commercial and social contexts in which they operate.
D4: Knowledge and understanding of management and business practices, their limitations, and how these may be applied in the context of the particular specialisation.
D5: Awareness that engineering activities should promote sustainable development and ability to apply quantitative techniques where appropriate.
D6: Awareness of relevant regulatory requirements governing engineering activities in the context of the particular specialisation.
D7: Awareness of and ability to make general evaluations of risk issues in the context of the particular specialisation, including health and safety, environmental and commercial risk.
D8: Understanding of different roles within an engineering team and the ability to exercise initiative and personal responsibility, which may be as a team member or leader.
D9: Communicate their work to technical and non-technical audiences.
Learning methods
Students learn key skills in research, problem solving, communication and team project work in projects, the Professional Practice and Research Methodology module and the individual dissertation.
Assessment methods
Assessment of the key skills is intrinsic to subject based assessment.
The assessment of project work includes specific allocations of credit for project management and the quality of presentations.
An individual's contribution to team projects is determined by means of a submission containing reflective and self-assessment components.
The assessment of the dissertation report includes specific allocation of credit for the quality, extent and relevance of a bibliography, including internet sources.