Stream

Knowledge Sys. and Data Mining - COMPKS8684

This Stream is no longer accepting new enrolments

Stream Summary

Faculty: ENG - Faculty of Engineering

School: School of Computer Science and Engineering

Contact: http://www.cse.unsw.edu.au

Program: 8684 - Information Technology

Award(s):

Master of Information Technology (Specialisation)

Information valid for students commencing 2013.
Students who commenced prior to 2013 should go to the Handbook's Previous Editions

Stream Outline

Knowledge Systems & Data Mining

Knowledge systems and data mining are key technologies for making sense of the information now being generated and stored on an unprecedented scale. Data mining is the process of discovering significant knowledge from complex data. Knowledge systems employ artificial intelligence for planning, decision support and reasoning. Our increasingly information-intensive world will drive successful organisations to adopt these approaches in many different ways, from risk management to scientific discovery.

On graduation, students can expect to have gained attributes that will prepare them to the development, implementation and ongoing management of systems for knowledge workers. A career based on strategic and operational responsibility in these areas can lead to a progression to senior technical and management roles in areas such as business, technology, science, health, government, education and entertainment.

The Knowledge Systems and Data Mining major in the MIT and MCIT programs covers the fundamentals of knowledge engineering, including database systems, artificial intelligence, knowledge systems, data mining and machine learning. These fundamentals can be complemented with specialised knowledge in neural networks, intelligent agents, e-Commerce and security.

Stream Structure

Knowledge Systems & Data Mining majors are required to complete the following two courses:

Group B/C courses:
Knowledge Systems & Data Mining majors must also take at least two courses from the following four:

Group D courses:
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Study Levels

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