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Course timetabling usually arises every academic year and is solved by academic staff with/without course timetabling tool. The desirable timetable must be satisfied by hard constraints whilst soft constraints are not absolutely essential. Course timetabling is known to be NP-hard problem, which means that the computational time required to find the solution increases exponentially with problem size. Automated timetabling tool has been developed for university courses scheduling. In this work, two variants of Ant Colony Optimisation algorithms called Max-Min Ant System and Ant Colony System were applied to solve university course timetabling problem. A two-step sequential experiment was sensibly designed and carried out using six benchmarking course timetabling problems. The analysis of the obtained results suggested that each method performed best on one another based on its parameter configuration.