This course provides an overview about important past and current developments, concepts, and applications in the fast evolving field of machine intelligence. It is an introductory course and could later be extended by higher studies in areas such as, advanced machine learning, data mining, bioinformatics, deep learning, optimisation, autonomous agents, computer vision, computer graphics, and related fields. The course’s topic is a central part of computer science and software engineering. Many of the concepts addressed by this course were initially biologically motivated and fall under the umbrella of brain theory. The aim is to get an understanding of intelligence, learning, memory, language, and the workings of the human brain by modelling and implementing aspects of these concepts in the computer. With the availability of faster workstations and sophisticated robotic hardware, machine intelligence methods can find more widespread applications. This course will address applications and systems where machine intelligence methods can lead to significant advancements, often surprising solutions, and sometimes triumphal success.
|Faculty||Faculty of Engineering and Built Environment|
|School||School of Electrical Engineering and Computing|
Semester 1 - 2017
On successful completion of this course, students will be able to:
|Assumed Knowledge||Equivalent to a completed 2nd year Bachelor of Computer Science|
* This assessment has a compulsory requirement.
Face to Face On Campus
per Week for
Face to Face On Campus 2 hour(s) per Week for Full Term
|Timetable||2017 Course Timetables for COMP6380|