The process of identifying valid, novel, understandable and potentially useful patterns in data. The process of identifying valid, novel, understandable and potentially useful patterns in data.

Why should I do this course?

Customer segmentation, customer profiling, fraud detection, the generation of more accurate pricing models, targeted marketing campaigns, the discovery of cross-selling opportunities, improved customer service: those are all activities which are becoming crucial for competitive advantage in the financial service sector.  Data is the wealth of a company and can inform and drive all of those activities but only those that learn to exploit it well will be the market leaders.  This course will help you to understand the opportunities and will also give you a good grounding on some of the leading technology.

Download Knowledge Discovery and Datamining video (youtube video)

Target Audience

The five-day course is suitable for those wishing to gain a detailed understanding of the stages of a typical Knowledge Discovery and Data mining project and the key techniques used in data mining.

No previous knowledge of datamining is required, but participants will benefit from having some basic knowledge of mathematics and statistics and good IT skills.

Course Objectives

The course aims to deliver an introduction to data mining techniques.  It will present the process of KDD and will give a review of available tools.  The course will then cover the main tasks of data mining: clustering and classification and introduce some of the algorithms available. It will also introduce tools available for data cleaning and preprocessing.  The concepts will be introduced in the context of application to the Financial Services industry and will include relevant examples and case studies.  The course will also serve to highlight further training opportunities.

At the end of the course, you will have:

  • An introduction to the principles of Knowledge Discovery and Datamining. 
  • A detailed methodology for KDD. 
  • A detailed look at the tools used through the cleaning and preprocessing phases of the KDD project.
  • A detailed look at the data mining tasks of clustering and classification, and the tools available for those.
  • An understanding of the other data mining tasks.
  • An understanding of the use of data mining, and in particular of the tools studied, in the Financial Services industry.
  • An introduction to data mining software packages with practical sessions in clustering and classification.
  • An understanding of further training requirements and opportunities.

There will be practical sessions using commercial datamining software packages illustrating their suitability for different types of project. The course is structured to provide time to discuss potential datamining projects with other delegates and our consultants.

Structure of the course

Day 1: Introduction to the course structure and teaching the team; Introduction to datamining concepts and techniques; Case studies; Introduction to the datamining software (practical session)

Day 2: The KDD roadmap – a methodology; Data warehousing; support for the KDD roadmap in the software (practical session)

Day 3: Data cleaning and preprocessing; Support for the early stages of KDD in the software (practical session)

Day 4: Datamining – the task of classification; Datamining – the task of clustering; Clustering and classification using data mining software (practical session)

Day 5: Text mining and other datamining task; Practical exercise; Wrap up session 

Course Leader

The course will be led by Dr. Beatriz De La Iglesia, who is a member of the Machine Learning and Statistics Research group at the University of East Anglia. She has published more than 40 papers on data mining, optimisation and related topics. She has commercial and consultancy experience with several large finance and technology companies. Dr. de la Iglesia has also participated a number of research collaborations in the analysis of medical data. She is also regularly invited to give data mining courses in other international institutions such as the University of Bologna, Italy.

Course delivery

Contact us for details of the next course.

More Information

We can also deliver this course at an employer's premises and would be happy to discuss details of this and any customisation.

For more information on the courses and services we can offer please contact:
Sue Johnson
Centre for Professional Development
University of East Anglia
Norwich Research Park
Tel: +44 (0) 1603 591578
Fax: +44 (0) 1603 591550