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This paper deals with the problem of course scheduling where we have a set of courses, lecturers and classrooms. Courses are assigned and scheduled in such a way that the total preference is maximized. We develop the mathematical model of the problem in form of a linear integer program. The small sized problem can be solved to optimality using commercial software. We then develop three different metaheuristics based on artificial immune, genetic and simulated annealing algorithms. These three solution methods are equipped with novel procedures such as move and crossing operators. The parameters of the proposed metaheuristics are first tuned, and then they are evaluated with optimal solutions found by the model. They are, furthermore, evaluated by comparing their performance. The experiments demonstrate that the artificial immune algorithm performs better than the other algorithms.