COMP8400 - Course content and schedule

• Check the current COMP8400 lecture and tutorial/lab times from ANU timetabling.

• There will be one two-hour lecture per week (ten two-hour lectures - 20 hours - in total).

• There will be four tutorials (based on selected readings).

• There will be four practical laboratory sessions.

• There will be two assignments (programming / data analysis projects).

• There will be one student presentation of a research paper.

Note: The course lecturer Peter Christen will be away in the first week after the semester break (27 April to 1 May). He will attend the PAKDD'09 conference in Bangkok.

Course content

The course will cover the following topics:

1. Course introduction and data mining overview   (1 hour)
2. Data mining process   (1 hour)
3. Data issues in data mining (including data warehouses) and data pre-processing   (2 hours)
4. Data integration and linkage   (2 hours)
5. Mining frequent patterns and associations   (2 hours)
6. Cluster analysis   (2 hours)
7. Classification and prediction: Decision trees, Bayes classification, neural networks, support vector machines, predictive modelling, accuracy and evaluation measures, model selection   (4 hours)
8. Mining time series and data streams   (1 hour)
9. Privacy-preserving data mining   (1 hour)
10. Text data mining   (1 hour)
11. Web data mining   (1 hour)
12. End-to-end data mining (guest speaker)   (1 hour)
13. Data mining trends, social impacts and course review   (1 hour)

Course schedule   (last update 18 May 2009)