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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2013/2014 -
- ARCHIVE as at 1 September 2013 for reference only
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DRPS : Course Catalogue : School of Mathematics : Mathematics

Postgraduate Course: Credit Scoring and Data Mining (MATH11040)

Course Outline
SchoolSchool of Mathematics CollegeCollege of Science and Engineering
Course typeStandard AvailabilityNot available to visiting students
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) Credits10
Home subject areaMathematics Other subject areaOperational Research
Course website https://info.maths.ed.ac.uk/teaching Taught in Gaelic?No
Course descriptionLarge scale databases - data warehouse and data archives; statistical approaches (clustering, discrimination, regression); non statistical approaches, including neural networks and genetic algorithms; commercial software; applications such as clustering, segmenting and scoring. Introduction to credit scoring. Setting up a scoring system. Statistical techniques used in credit scoring. Other approaches to credit scoring. Use of behavioural scoring. Techniques used in behavioural scoring systems. Monitoring and updating scoring systems. Developments in scoring systems.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Additional Costs None
Course Delivery Information
Delivery period: 2013/14 Block 4 (Sem 2), Not available to visiting students (SS1) Learn enabled:  Yes Quota:  None
Web Timetable Web Timetable
Course Start Date 24/02/2014
Breakdown of Learning and Teaching activities (Further Info) Total Hours: 100 ( Lecture Hours 13, Seminar/Tutorial Hours 6, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 79 )
Additional Notes
Breakdown of Assessment Methods (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
No Exam Information
Summary of Intended Learning Outcomes
Understanding of statistical and alternative methods of constructing scoring rules. Understanding how to process data prior to model building. Ability to assess and monitor a scorecard. Awareness of current and new applications of credit scoring techniques. Understanding of real life application of data mining, including clustering, segmentation and scoring.
Assessment Information
See 'Breakdown of Assessment Methods' and 'Additional Notes' above.
Special Arrangements
None
Additional Information
Academic description Not entered
Syllabus Not entered
Transferable skills Not entered
Reading list Not entered
Study Abroad Not entered
Study Pattern Not entered
KeywordsCSDM
Contacts
Course organiserDr Julian Hall
Tel: (0131 6)50 5075
Email: J.A.J.Hall@ed.ac.uk
Course secretaryMrs Frances Reid
Tel: (0131 6)50 4883
Email: f.c.reid@ed.ac.uk
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