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Big Data and Text Analytics

Course overview

(MSc) Master of Science
Big Data and Text Analytics
Current
University of Essex
University of Essex
Computer Science and Electronic Engineering (School of)
Colchester Campus
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.
Masters
Full-time or part-time
None
None
None
MSC G51512
http://www.essex.ac.uk/students/exams-and-coursework/ppg/pgt/assess-rules.aspx
12/06/2018

A 2.2 in Computer Science; Computer Engineering; Computer Networks; Computer Games; Computing; Software Engineering, Electronic Engineering; Electrical Engineering; Telecommunication Engineering; Automation; Mechatronic Engineering; Mathematics or Physics.

Graduates of Computer Science; Computer Engineering; Computer Networks; Computer Games; Computing; Software Engineering must have studied :

ONE programming module (e.g. C, C#, C++, Java, Python, Object Oriented programming, Advanced Programming).

ONE maths module (e.g.Mathematics; Calculus; Algebra; Differential Equations).

and ONE other computing related module (e.g. Database, Web development, Software engineering, Operating system, Computer architecture; Computer systems etc.).

Graduates of Electronic Engineering; Electrical Engineering; Telecommunication Engineering; Automation; Mechatronic Engineering; Mathematics; Physics must have studied:

ONE programming module (e.g. C, C#, C++, Java, Python, Object Oriented programming, Advanced Programming).

ONE maths module (e.g.Mathematics; Calculus; Algebra; Differential Equations).

and ONE other math module (e.g. Mathematics, Calculus, Algebra, Differential Equations, Probability and statistics, Signals and systems, Control theory, Control systems, Computer systems, Embedded systems, Microprocessors).

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.

External Examiners

Dr Robert Mark Stevenson
Senior Lecturer

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.

eNROL, the module enrolment system, is now open until Monday 21 October 2019 8:59AM, for students wishing to make changes to their module options.

Key

Core You must take this module You must pass this module. No failure can be permitted.
Core with Options You can choose which module to study
Compulsory You must take this module There may be limited opportunities to continue on the course/be eligible for the degree if you fail.
Compulsory with Options You can choose which module to study
Optional You can choose which module to study

Year 1 - 2019/20

Exit Award Status
Component Number Module Code Module Title Status Credits PG Diploma PG Certificate
01 CE901-7-SU MSc Project and Dissertation Core 60
02 CE802-7-AU Machine Learning and Data Mining Compulsory 15
03 CE706-7-SP Information Retrieval Compulsory 15
04 CE807-7-SP Text Analytics Compulsory 15
05 CE902-7-FY Professional Practice and Research Methodology Compulsory 15
06 CE903-7-SP Group Project Compulsory 15
07 CE887-7-AU Natural Language Engineering Compulsory 15
08 Option from list Optional 30

Exit awards

A module is given one of the following statuses: 'core' – meaning it must be taken and passed; 'compulsory' – meaning it must be taken; or 'optional' – meaning that students can choose the module from a designated list. The rules of assessment may allow for limited condonement of fails in 'compulsory' or 'optional' modules, but 'core' modules cannot be failed. The status of the module may be different in any exit awards which are available for the course. Exam Boards will consider students' eligibility for an exit award if they fail the main award or do not complete their studies.

Programme aims

MSc Big Data and Text Analytics 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 big data and text analytics
2. To develop the students' ability to make a critical evaluation of the theories, techniques, tools and systems used in big data and text analytics
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 encourage students to adopt an investigative approach and develop autonomous study skills in order
6. 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 Knowlege and understanding of big data systems and the text analytics that supports them.
Learning Methods: Lectures are the principal method of delivery for the concepts and principles involved in A1 - A4.

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 and assignments.

Knowledge of a particular topic, chosen by the student from within his/her areas of specialisation, is gained in CE902 through a staff led literature search which forms the basis for weekly group discussions.

Individual supervision of the summer project and dissertation provides further support for the development of those areas of knowledge relevant to the student's chosen topic.
Assessment Methods: Achievement of knowledge outcomes is assessed primarily through unseen closed-book examinations and marked coursework.

Understanding of professional issues (A4) is assessed by MCT during the course of the term.

The assessment of the CE902 essay includes specific allocation of marks for the breadth and depth of the knowledge gained during the study of the chosen topic.

An assessment of the understanding of principles and implementation techniques forms part of the overall assessment of the summer project and dissertation

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 software engineering principles to the design of cloud based systems and text analytics.
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.

B1 is developed through exercises and exposure to a range of systems software.

B2 is a key element of most assignments and central to the group project.

In CE902, the acquisition of B3 and B4 is supported by lectures about research methodology and report writing, and further developed during tutor led group discussions.

Skills B1 - B4 are all required for the successful completion of the summer project, and are developed in the course of individual supervision.
Assessment Methods: Achievement of intellectual skills B1 and B2 is assessed primarily through unseen closed-book examinations, marked assignments and project work.

The assessment of the CE902 essay includes specific allocation of marks for use of original sources (B3), clarity of description and originality (B4).

An assessment of the extent to which students have developed skills B1 - B4 forms part of the overall assessment of the summer project and dissertation.

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 big data systems including systems that use text analytics.
Learning Methods: Learning methods Practical skills are developed in exercise classes, laboratory classes, assignments and project work.

C1 is developed through exercises and exposure to a range of systems.

Various aspects of C2 are acquired in design, programming and other assignments, and further developed in individual project work.

C3 is developed during the supervision of the summer project and dissertation.
Assessment Methods: Achievement of practical skills is assessed through marked coursework, project reports, oral presentations and demonstrations of completed systems.

An assessment of the extent to which students have demonstrated practical research skills (C3) forms part of the overall assessment of the summer project and dissertation.

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: D1 is developed through a range of reports, including the dissertation which uses D2 to support this outcome.

D3 and D4 are developed through assignments and problems set within modules.

D5 is acquired as part of Professional Practice and Development (CE902).

D6 is developed in CE902 that encourages reflective learning and is put into practice in the dissertation work.
Assessment Methods: Assessment is through a range of assignments, written reports and oral presentation within the teaching modules and dissertation.

In particular D6 is assessed within the dissertation and CE902


Note

The University makes every effort to ensure that this information on its programme specification is accurate and up-to-date. Exceptionally it can be necessary to make changes, for example to courses, facilities or fees. Examples of such reasons might include a change of law or regulatory requirements, industrial action, lack of demand, departure of key personnel, change in government policy, or withdrawal/reduction of funding. Changes to courses may for example consist of variations to the content and method of delivery of programmes, courses and other services, to discontinue programmes, courses and other services and to merge or combine programmes or courses. The University will endeavour to keep such changes to a minimum, and will also keep students informed appropriately by updating our programme specifications.

The full Procedures, Rules and Regulations of the University governing how it operates are set out in the Charter, Statutes and Ordinances and in the University Regulations, Policy and Procedures.

Should you have any questions about programme specifications, please contact Course Records, Quality and Academic Development; email: crt@essex.ac.uk.