Module Descriptors
KNOWLEDGE DISCOVERY AND DATA MINING
COSE60592
Key Facts
School of Computing and Digital Technologies
Level 6
15 credits
Contact
Leader: Euan Wilson
Email: E.D.Wilson@staffs.ac.uk
Hours of Study
Scheduled Learning and Teaching Activities: 24
Independent Study Hours: 126
Total Learning Hours: 150
Assessment
- ASSIGNMENT weighted at 100%
Module Details
Module Additional Assessment Details
An Assignment length 3000 words weighted at 100%. (Learning outcomes 1 to 4)
Module Indicative Content
Knowledge discovery and data mining in context.
Data mining primitives, languages and system architecture.
Data mining methodology and algorithms.
Text mining algorithms and Information extraction systems.
Data mining and data privacy.
Social impact and ethical issues
Data mining primitives, languages and system architecture.
Data mining methodology and algorithms.
Text mining algorithms and Information extraction systems.
Data mining and data privacy.
Social impact and ethical issues
Module Special Admissions Requirements
Prior study of CESCOM10077-4 Structured Systems Analysis or equivalent
Module Resources
Data Mining software: MATLAB, WEKA
Module Texts
Data Mining : A Knowledge Discovery Approach, K. Cios, W. Pedrycz, R. Swiniarski, L. Kurgan,: 2007., Springer, ISBN: 978-0-387-33333-5
Data Mining : Concepts and Techniques Jiawei Han, Micheline Kamber, , 2006, Morgan Kaufmann, ISBN 1558609016
Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining, Glenn J. Myatt,:2006 , John Wiley, ISBN: 0-470-07471-0
Data Mining : Concepts and Techniques Jiawei Han, Micheline Kamber, , 2006, Morgan Kaufmann, ISBN 1558609016
Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining, Glenn J. Myatt,:2006 , John Wiley, ISBN: 0-470-07471-0
Module Learning Strategies
12 lecture hours and 12 tutorial hours