MSc Knowledge Discovery and Datamining (Part Time 2 Year)

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Key facts

(2014 Research Excellence Framework)

Great business decisions are underpinned by high quality data. As a data scientist you are absolutely integral to the success of an organisation – you will source, analyse and utilise vast amounts of data to support strategic decision-making.

If that’s where you aspire to be, then this course is for you. You will gain an advanced practical and theoretical grounding in data mining and statistics, with the chance to customise your degree through modules in artificial intelligence, visualisation, programming and database manipulation.

We have a large data mining, machine learning and statistics research group, which has made significant contributions to the field in the last 15 years, so you’ll be working directly with pioneering experts.

Data scientists are highly prized in almost any industry, so you’ll have great graduate career prospects as well as a wide range of transferable skills.

Overview

This degree follows the same programme as its full-time equivalent but is spread over two years.

Module enrolment for each year is discussed with the Course Director at the start of the course.

Course Modules 2019/0

Students must study the following modules for 40 credits:

Name Code Credits

DATA MINING

This module is designed for postgraduate students studying on MSc courses. You will explore the methodologies of Knowledge Discovery and Data Mining (KDD). You will cover each stage of the KDD process, including preliminary data exploration, data cleansing, pre-processing and the various data analysis tasks that fall under the heading of data mining, focusing on clustering, classification and association rule induction. Through this module, you will gain knowledge of algorithms and methods for data analysis, as well as practical experience using leading KDD software packages.

CMP-7023B

20

RESEARCH TECHNIQUES (RESEARCH METHODS)

This module aims to prepare postgraduate students with necessary intellectual and practical skills for successfully carrying out research work for their MSc Dissertation in Computing Sciences and Computational Biology. Specifically, it teaches research methodologies, techniques and tools used in computing sciences, and more importantly, provides systematic trainings to enhance students' transferable skills and their understanding in ethics, social and legal issues involved in computing professions.

CMP-7030Y

20

Students will select 0 - 20 credits from the following modules:

Students must select 20 credits from Option Range A in either their 1st or 2nd year of study.

Name Code Credits

ARTIFICIAL INTELLIGENCE

This module will introduce you to core techniques in Artificial Intelligence. Topics covered may include introduction to Prolog programming, state space representation and search algorithms, knowledge representation, expert systems, Bayesian networks, neural networks and deep learning.

CMP-7028A

20

INFORMATION VISUALISATION

This module is an introduction to information visualisation. You will learn techniques for summarising and presenting a wide range of data. There is a strong emphasis on understanding the appropriate context and use of visualisation techniques. You will also learn about problems and techniques for dealing with large data flows and issues of integrating multiple data sources.

CMP-7022B

20

Students will select 20 - 40 credits from the following modules:

Students without database experience MUST take CMP-7025A and students without programming experience MUST take CMP-7000A

Name Code Credits

ARTIFICIAL INTELLIGENCE

This module will introduce you to core techniques in Artificial Intelligence. Topics covered may include introduction to Prolog programming, state space representation and search algorithms, knowledge representation, expert systems, Bayesian networks, neural networks and deep learning.

CMP-7028A

20

AUDIO AND VISUAL PROCESSING

This module explores how computers process audio and video signals. In the audio component, the focus is on understanding how humans produce speech and how this can be processed by computer for speech recognition and enhancement. Similarly, the visual component considers the human eye and camera, and how video is processed by computer. The theoretical material covered in lectures is reinforced with practical laboratory sessions. The module is coursework only and requires you to build a speech recogniser capable of recognising the names of students studying the module using both audio and visual speech information.

CMP-7016A

20

COMPUTER VISION

Computer Vision is about "teaching machines how to see". You will study methods for acquiring, analysing and understanding images in both lectures and laboratories. The practical exercises and projects that you undertake in the laboratory will support the underpinning theory and enable you to implement contemporary computer vision algorithms.

CMP-7026B

20

DATABASE MANIPULATION

This module introduces you to important aspects of databases, database manipulation and database management systems. The module is based on the relational model. You will explore the tools and methods for database design and manipulation as well as the programming of database applications. Part of the practical experience you will gain will be acquired using a modern relational database management system. You will also gain programming experience using SQL, and using a high level programming language to write applications that access the database.

CMP-7025A

20

HUMAN COMPUTER INTERACTION

Human Computer Interaction (or UX) covers a very wide range of devices, including conventional computers, mobile devices and "hidden" computing devices. In this module you will learn about interactions from a variety of perspectives, such as cognitive psychology, ethnographic methods, security issues, UI failures, the principles of good user experience, heuristic and experimental evaluation approaches and the needs of a range of different audiences.

CMP-7018A

20

INFORMATION VISUALISATION

This module is an introduction to information visualisation. You will learn techniques for summarising and presenting a wide range of data. There is a strong emphasis on understanding the appropriate context and use of visualisation techniques. You will also learn about problems and techniques for dealing with large data flows and issues of integrating multiple data sources.

CMP-7022B

20

Students must study the following modules for 80 credits:

Name Code Credits

APPLIED STATISTICS

This is a module designed to give students the opportunity to apply statistical methods in realistic situations. While no advanced knowledge of probability and statistics is required, we expect students to have some background in probability and statistics before taking this module. The aim is to teach the R statistical language and to cover 3 topics: Linear regression, ANOVA, and Survival Analysis.

CMP-7008B

20

DISSERTATION

Reserved for postgraduates in the School of Computing Sciences, this module provides the student with a piece of individual work, with substantial research and practical elements. The subject of the dissertation will be determined by agreement between the student and his or her supervisor. The work may be undertaken as part of a large collaborative or group project.

CMP-7027X

60

Students will select 0 - 20 credits from the following modules:

Students must select 20 credits from Option Range A in either their 1st or 2nd year of study.

Name Code Credits

ARTIFICIAL INTELLIGENCE

This module will introduce you to core techniques in Artificial Intelligence. Topics covered may include introduction to Prolog programming, state space representation and search algorithms, knowledge representation, expert systems, Bayesian networks, neural networks and deep learning.

CMP-7028A

20

INFORMATION VISUALISATION

This module is an introduction to information visualisation. You will learn techniques for summarising and presenting a wide range of data. There is a strong emphasis on understanding the appropriate context and use of visualisation techniques. You will also learn about problems and techniques for dealing with large data flows and issues of integrating multiple data sources.

CMP-7022B

20

Students will select 20 - 40 credits from the following modules:

Students without database experience MUST take CMP-7025A and students without programming experience MUST take CMP-7000A.

Name Code Credits

ARTIFICIAL INTELLIGENCE

This module will introduce you to core techniques in Artificial Intelligence. Topics covered may include introduction to Prolog programming, state space representation and search algorithms, knowledge representation, expert systems, Bayesian networks, neural networks and deep learning.

CMP-7028A

20

AUDIO AND VISUAL PROCESSING

This module explores how computers process audio and video signals. In the audio component, the focus is on understanding how humans produce speech and how this can be processed by computer for speech recognition and enhancement. Similarly, the visual component considers the human eye and camera, and how video is processed by computer. The theoretical material covered in lectures is reinforced with practical laboratory sessions. The module is coursework only and requires you to build a speech recogniser capable of recognising the names of students studying the module using both audio and visual speech information.

CMP-7016A

20

COMPUTER VISION

Computer Vision is about "teaching machines how to see". You will study methods for acquiring, analysing and understanding images in both lectures and laboratories. The practical exercises and projects that you undertake in the laboratory will support the underpinning theory and enable you to implement contemporary computer vision algorithms.

CMP-7026B

20

DATABASE MANIPULATION

This module introduces you to important aspects of databases, database manipulation and database management systems. The module is based on the relational model. You will explore the tools and methods for database design and manipulation as well as the programming of database applications. Part of the practical experience you will gain will be acquired using a modern relational database management system. You will also gain programming experience using SQL, and using a high level programming language to write applications that access the database.

CMP-7025A

20

HUMAN COMPUTER INTERACTION

Human Computer Interaction (or UX) covers a very wide range of devices, including conventional computers, mobile devices and "hidden" computing devices. In this module you will learn about interactions from a variety of perspectives, such as cognitive psychology, ethnographic methods, security issues, UI failures, the principles of good user experience, heuristic and experimental evaluation approaches and the needs of a range of different audiences.

CMP-7018A

20

INFORMATION VISUALISATION

This module is an introduction to information visualisation. You will learn techniques for summarising and presenting a wide range of data. There is a strong emphasis on understanding the appropriate context and use of visualisation techniques. You will also learn about problems and techniques for dealing with large data flows and issues of integrating multiple data sources.

CMP-7022B

20

Disclaimer

Whilst the University will make every effort to offer the modules listed, changes may sometimes be made arising from the annual monitoring, review and update of modules and regular (five-yearly) review of course programmes. Where this activity leads to significant (but not minor) changes to programmes and their constituent modules, there will normally be prior consultation of students and others. It is also possible that the University may not be able to offer a module for reasons outside of its control, such as the illness of a member of staff or sabbatical leave. In some cases optional modules can have limited places available and so you may be asked to make additional module choices in the event you do not gain a place on your first choice. Where this is the case, the University will endeavour to inform students.

Further Reading

Entry Requirements

  • Degree Subject Computing, Mathematics or a related subject.
  • Degree Classification Bachelors degree (minimum 2.1 or equivalent).

Students for whom English is a Foreign language

We welcome applications from students whose first language is not English. To ensure such students benefit from postgraduate study, we require evidence of proficiency in English. Our usual entry requirements are as follows:

  • IELTS: 6.5 (minimum 6.0 in all components)
  • PTE (Pearson): 58 (minimum 50 in all components)

Test dates should be within two years of the course start date.

Other tests, including Cambridge English exams and the Trinity Integrated Skills in English are also accepted by the university. The full list of accepted tests can be found here: Accepted English Language Tests

INTO UEA also run pre-sessional courses which can be taken prior to the start of your course. For further information and to see if you qualify please contact intopre-sessional@uea.ac.uk

Fees and Funding

Tuition fees for the academic year 2019/20 are:

  • UK/EU Students: £7,700 (full time)
  • International Students: £16,100 (full time)

If you choose to study part-time, the fee per annum will be half the annual fee for that year, or a pro-rata fee for the module credit you are taking (only available for UK/EU students).

 

Living Expenses

We estimate living expenses at £1,015 per month.

 

Scholarships

A variety of Scholarships may be offered to UK/EU and International students. Scholarships are normally awarded to students on the basis of academic merit and are usually for the duration of the period of study. Please click here for more detailed information about funding for prospective students.

How to Apply

Applications for Postgraduate Taught programmes at the University of East Anglia should be made directly to the University.

You can apply online, or by downloading the application form.

Further Information

To request further information & to be kept up to date with news & events please use our online enquiry form.

If you would like to discuss your individual circumstances prior to applying please do contact us:

Postgraduate Admissions Office
Tel: +44 (0)1603 591515
Email: admissions@uea.ac.uk

International candidates are also encouraged to access the International Students section of our website.

    Next Steps

    We can’t wait to hear from you. Just pop any questions about this course into the form below and our enquiries team will answer as soon as they can.

    Admissions enquiries:
    admissions@uea.ac.uk or
    telephone +44 (0)1603 591515