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Code Module Credits Duration Prerequisite(s)
Table III: Electives (Cont.)

COMP6169 Selected Topics I 3 45 hrs ---
The selected topics are designed to accommodate new, advanced and state-of-the-art

technologies that are not included in this curriculum. One example is environmental data
mining. Data Mining is one of the most popular research fields in Computer Science. The
aim of this is to give an applicable understanding of the usage of data mining as of
decision making. In this module, several essential fields would be discussed, including
the classes of different algorithms and models, and the methodology of how to choose
a suitable algorithm. Classification, pattern recognition and different learning types
would be discussed and covered. Besides, other interdisciplinary topics, such as
mathematical and statistical modelling in transportation systems, can also be covered.
COMP6170 Selected Topics II 3 45 hrs ---
The selected topics are designed to accommodate new, advanced and state-of-the-art

technologies that are not included in this curriculum. One example is environmental data
mining. Data Mining is one of the most popular research fields in Computer Science. The
aim of this is to give an applicable understanding of the usage of data mining as of
decision making. In this module, several essential fields would be discussed, including
the classes of different algorithms and models, and the methodology of how to choose
a suitable algorithm. Classification, pattern recognition and different learning types
would be discussed and covered. Besides, other interdisciplinary topics, such as
mathematical and statistical modelling in transportation systems, can also be covered.

Remarks:
*In order to fulfill the graduation requirement, students must complete 30 credits, including 15 credits from
the compulsory modules listed in Table I, 9 credits from the Project Report in Table II ,and 6 credits from the
optional modules in Table III.

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