MSc Knowledge Discovery and Datamining (Part time 3 Yr)


Attendance
Part Time
Award
Degree of Master of Science



This course is designed to train highly qualified data analysts – or data scientists – to embark on careers in a wide range of industries. You’ll be given an excellent practical and theoretical grounding in data mining, statistics and artificial intelligence with the chance to customise your degree through modules in programming, database manipulation and NLP.

Data Scientists are highly prized for their advanced, practical skill set and their increasing importance to the success of a modern business. Organisations in almost any industry need to source, analyse and utilise vast amounts of data to aid strategic decision-making, so you’ll have great graduate career prospects as well as a wide range of transferrable skills.

We have one of the largest Data Mining, Machine Learning and Statistics research groups in the UK, which has made significant contributions to the field in the last 10 years, so you’ll be working directly with pioneering experts.

Overview

The unique structure of this course offers a truly part-time route for mature professionals to supplement their work with an accredited qualification. The MSc requires students to study one module per semester over a 3 year period. The timetable for this course is designed so that students are able to study alongside working, and contact time for each module is scheduled as a maximum of one day per week. 

The course follows the successful model of the KDD MSc (Industry Based), which we have run for our partner Aviva for over 14 years. During this time we have produced 80 outstanding graduates for Aviva, bolstering their workforce with Master’s-level recognition.

The course was short-listed as one of the most innovative collaborations between Business and a University by the East of England Development Agency.

This MSc is one of the few similar academic qualifications to have been conceived and developed to meet the specific needs of industry partners.

The course teaches skills which are directly relevant to industry, as the sector increasingly seeks to expand its use of data analytics.

Students will be able to see the direct impact of the course on their vocational work, as some of the modules will involve projects using their company’s data. This will allow students to integrate their university projects into their job, putting the principles they have learnt from the classroom into practice.

Companies will directly benefit from a relationship with the university which will involve access to state-of-the-art expertise in topical subjects such as data mining, statistics and information retrieval as well as artificial intelligence and database manipulation.

Some modules consider the experience and knowledge which students have acquired at work, and may seek to involve line managers in assessing participants’ skills.

The MSc represents excellent value for money, as employers are able to part fund high quality training to incentivise staff and increase retention. The added bonus of only having to give participants a single day off per module makes the programme much more cost effective than other similar programmes.

Full details about the course structure can be found here.

Course Modules

Students will select 40 credits from the following modules:

Students must select 40 credits from the following modules. During their 3-years of study, students must have taken CMP-7023B and CMP-7008B, and either or both CMP-7022B and CMP-7028A. Students without database experience must take CMP-7025A and students without programming experience must take CMP-7000A.

Name Code Credits

APPLICATIONS PROGRAMMING

The module aims to establish a clear understanding of Object Oriented Programming (OOP) and essential Objected Oriented Methodologies for developing application software. It teaches Java programming language and uses it as a vehicle to learn important concepts, such as objects, classes, inheritance, encapsulation and polymorphism. It also covers the Unified Modelling Language (UML) as a tool for object-oriented analysis and design, software development life cycle models, and software testing strategies and techniques.

CMP-7000A

20

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 introduce students to R statistical language and to cover Regression, Analysis of Variance and Survival analysis. Other topics from a list including: Extremes and quartiles, Bootstrap methods and their application, Sample surveys, Simulations, Subjective statistics, Forecasting and Clustering methods, may be offered to cover the interests of those in the class. BEFORE TAKING THIS MODULE you have taken CMP-4004Y or CMP-4005Y or CMP-4006Y or have an equivalent basic knowledge of probability and statistics.

CMP-7008B

20

ARTIFICIAL INTELLIGENCE

This module introduces the students to core techniques in Artificial Intelligence and some topics in algorithmics. Topics covered include First-Order logic and resolution proofs, introduction to Prolog programming, state space representation and search algorithms, knowledge representation, and expert systems, Bayesian and neural networks.

CMP-7028A

20

DATA MINING

This module is designed for postgraduate students studying on MSc courses. The module explores the methodologies of Knowledge Discovery and Data Mining (KDD). It aims to 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. Through this module, students should gain knowledge of algorithms and methods for data analysis, as well as practical experience using leading KDD software packages.

CMP-7023B

20

DATABASE MANIPULATION

This module introduces most aspects of databases, database manipulation and database management systems. Practical experience of database manipulation is provided through the use of SQL and the Java JDBC interface on a relational database management system. Database design is introduced using Entity-Relationship modelling and normalisation.

CMP-7025A

20

HUMAN COMPUTER INTERACTION

An overview of Human Computer Interaction, including user interfaces on conventional computers and small footprint devices (e.g. smartphones). Human-Computer interactions are approached from a variety of perspectives, with an emphasis on experimental evaluation.

CMP-7018A

20

INFORMATION VISUALISATION

This module is an introduction to information visualization. It covers techniques for summarizing and presenting a wide range of data. The problems and techniques for dealing with large data flows are a major theme and there is a strong emphasis on understanding the appropriate context and use of visualization techniques.

CMP-7022B

20

Students must study the following modules for 20 credits:

Name Code Credits

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 20 credits from the following modules:

Students must select 20 credits from the following modules. During their 3-years of study, students must have taken CMP-7023B and CMP-7008B, and either or both CMP-7022B and CMP-7028A. Students without database experience must take CMP-7025A and students without programming experience must take CMP-7000A.

Name Code Credits

APPLICATIONS PROGRAMMING

The module aims to establish a clear understanding of Object Oriented Programming (OOP) and essential Objected Oriented Methodologies for developing application software. It teaches Java programming language and uses it as a vehicle to learn important concepts, such as objects, classes, inheritance, encapsulation and polymorphism. It also covers the Unified Modelling Language (UML) as a tool for object-oriented analysis and design, software development life cycle models, and software testing strategies and techniques.

CMP-7000A

20

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 introduce students to R statistical language and to cover Regression, Analysis of Variance and Survival analysis. Other topics from a list including: Extremes and quartiles, Bootstrap methods and their application, Sample surveys, Simulations, Subjective statistics, Forecasting and Clustering methods, may be offered to cover the interests of those in the class. BEFORE TAKING THIS MODULE you have taken CMP-4004Y or CMP-4005Y or CMP-4006Y or have an equivalent basic knowledge of probability and statistics.

CMP-7008B

20

ARTIFICIAL INTELLIGENCE

This module introduces the students to core techniques in Artificial Intelligence and some topics in algorithmics. Topics covered include First-Order logic and resolution proofs, introduction to Prolog programming, state space representation and search algorithms, knowledge representation, and expert systems, Bayesian and neural networks.

CMP-7028A

20

DATA MINING

This module is designed for postgraduate students studying on MSc courses. The module explores the methodologies of Knowledge Discovery and Data Mining (KDD). It aims to 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. Through this module, students should gain knowledge of algorithms and methods for data analysis, as well as practical experience using leading KDD software packages.

CMP-7023B

20

DATABASE MANIPULATION

This module introduces most aspects of databases, database manipulation and database management systems. Practical experience of database manipulation is provided through the use of SQL and the Java JDBC interface on a relational database management system. Database design is introduced using Entity-Relationship modelling and normalisation.

CMP-7025A

20

HUMAN COMPUTER INTERACTION

An overview of Human Computer Interaction, including user interfaces on conventional computers and small footprint devices (e.g. smartphones). Human-Computer interactions are approached from a variety of perspectives, with an emphasis on experimental evaluation.

CMP-7018A

20

INFORMATION VISUALISATION

This module is an introduction to information visualization. It covers techniques for summarizing and presenting a wide range of data. The problems and techniques for dealing with large data flows are a major theme and there is a strong emphasis on understanding the appropriate context and use of visualization techniques.

CMP-7022B

20

Students must study the following modules for 60 credits:

Name Code Credits

DISSERTATION

In this module, each Masters student is required to carry out project work with substantial research and practical elements on a specified topic for their MSc dissertation from January to late August. The topic can be chosen and allocated from the lists of proposals from faculty members, or proposed by students themselves with an agreement from their supervisor and also an approval from the module organiser. The work may be undertaken as part of a large collaborative or group project. A dissertation must be written as the outcome of the module.

CMP-7027X

60

Students will select 40 credits from the following modules:

Students must select 40 credits from the following modules. During their 3-years of study, students must have taken CMP-7023B and CMP-7008B, and either or both CMP-7022B and CMP-7028A. Students without database experience must take CMP-7025A and students without programming experience must take CMP-7000A.

Name Code Credits

APPLICATIONS PROGRAMMING

The module aims to establish a clear understanding of Object Oriented Programming (OOP) and essential Objected Oriented Methodologies for developing application software. It teaches Java programming language and uses it as a vehicle to learn important concepts, such as objects, classes, inheritance, encapsulation and polymorphism. It also covers the Unified Modelling Language (UML) as a tool for object-oriented analysis and design, software development life cycle models, and software testing strategies and techniques.

CMP-7000A

20

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 introduce students to R statistical language and to cover Regression, Analysis of Variance and Survival analysis. Other topics from a list including: Extremes and quartiles, Bootstrap methods and their application, Sample surveys, Simulations, Subjective statistics, Forecasting and Clustering methods, may be offered to cover the interests of those in the class. BEFORE TAKING THIS MODULE you have taken CMP-4004Y or CMP-4005Y or CMP-4006Y or have an equivalent basic knowledge of probability and statistics.

CMP-7008B

20

ARTIFICIAL INTELLIGENCE

This module introduces the students to core techniques in Artificial Intelligence and some topics in algorithmics. Topics covered include First-Order logic and resolution proofs, introduction to Prolog programming, state space representation and search algorithms, knowledge representation, and expert systems, Bayesian and neural networks.

CMP-7028A

20

DATA MINING

This module is designed for postgraduate students studying on MSc courses. The module explores the methodologies of Knowledge Discovery and Data Mining (KDD). It aims to 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. Through this module, students should gain knowledge of algorithms and methods for data analysis, as well as practical experience using leading KDD software packages.

CMP-7023B

20

DATABASE MANIPULATION

This module introduces most aspects of databases, database manipulation and database management systems. Practical experience of database manipulation is provided through the use of SQL and the Java JDBC interface on a relational database management system. Database design is introduced using Entity-Relationship modelling and normalisation.

CMP-7025A

20

HUMAN COMPUTER INTERACTION

An overview of Human Computer Interaction, including user interfaces on conventional computers and small footprint devices (e.g. smartphones). Human-Computer interactions are approached from a variety of perspectives, with an emphasis on experimental evaluation.

CMP-7018A

20

INFORMATION VISUALISATION

This module is an introduction to information visualization. It covers techniques for summarizing and presenting a wide range of data. The problems and techniques for dealing with large data flows are a major theme and there is a strong emphasis on understanding the appropriate context and use of visualization techniques.

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. Where this is the case, the University will endeavour to inform students.

Entry Requirements

  • Degree Subject Computing, Mathematics or a related subject.
  • Degree Classification Good first 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): 62 (minimum 55 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 2017/18

  • Home/EU:

     Full-time £7,300, Part-time £3,650

     If you choose to study part-time, please assume a pro-rata fee for the credits you are taking, or 50% of the equivalent fee per year if you are taking a full-time course on a part-time basis.  

  • Overseas:

      Full-time £14,800

      If you are classed as an 'overseas' student and are coming to UEA on a student or visitor's visa, UK visa rules won't normally allow you to study on a part-time course. You should always check with the UKVI for the latest requirement.

 

Scholarships

50% Final Year Undergraduate Continuation Scholarship

Current final year UEA undergraduate students who gain a First class degree and progress onto a postgraduate course in September 2016 will receive a 50% fee reduction scholarship. Who do not gain a First class degree will be eligible for the 10% UEA Alumni Scholarship outlined below. Terms and conditions apply.

 

UEA Alumni 10% Scholarship

A scholarship of 10% fee reduction is available to UEA Alumni looking to return for postgraduate study at UEA in September 2016. Terms and conditions apply.

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

    Need to know more? Take a look at these pages to discover more about Postgraduate opportunities at UEA…

    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