The aim of this module is to provide the student with and understanding of the role data mining and data quality techniques play in our lives. The students will develop a basic toolbox allowing them to use methods for learning and evaluation information. This will be paired with a consideration of the ethical implications surrounding gathering and using information in an automated manner. 

1. Execute and evaluate various techniques related to knowledge discovery and data mining 
    

2. Analyse and critically evaluate methods for assuring quality of information 
    

3. Appraise the ethical implications and societal risks associated with data mining and data quality assurance 

The module will be delivered through a combination of lectures and supervised lab sessions/tutorials as appropriate. You will be expected to attend all timetabled sessions and engage with online materials. Online drop-in sessions will be scheduled for students who miss sessions or require further assistance. 

Please refer to the learning outcomes.

The module will be assessed with two individual portfolios. Portfolio 1 will consist of online mini-tests and coded tasks relating to data mining. Portfolio 2 will consist of online mini-tests and written/coded tasks pertaining to data quality and data ethics. 

Similarity measures 

Knowledge discovery process 

Data mining 

Classification 

Clustering 

Association rule learning 

Data quality dimensions, activities and methodologies 

Ethical considerations concerning gathering and using information