Data mining is the computational process of discovering patterns from large data sets. This unit (NIT6160) discusses concepts and techniques of data warehousing and mining. Data mining is one of the most advanced tools used by IT industries. The topics covered include introduction to data warehousing, data pre-processing and foundational data mining techniques such as supervised learning including regression and classification, and unsupervised learning such as clustering and association rules. Students are introduced to perform data mining tasks with neural networks, as well as exposed to open-source data mining software.
Unit details
Location:
Study level:
Postgraduate
Credit points:
12
Unit code:
NIT6160
Prerequisites
NIT5150 - Advanced Object Oriented Programming
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Learning Outcomes
| 1. | Critically analyse the application of data warehousing concepts; | ||
| 2. | Critically evaluate data quality to advocate application of data pre-processing techniques; | ||
| 3. | Devise implementation solutions that involve supervised learning including regression and classification on real world data sets; | ||
| 4. | Experiment and evaluate unsupervised learning solutions including clustering and association rules mining on large datasets; and | ||
| 5. | Critically reflect on advantages and disadvantages of particular data mining solutions to solve real life problems with considerations of data privacy and professional ethics, and evaluate their usefulness and useability. |
Assessment
| Assessment type | Description | Grade |
|---|---|---|
| Laboratory Work | Practical labs | 20% |
| Test | Open-book test | 40% |
| Project | Final Project | 40% |
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