This course is concerned with the study of algorithms for solving practical problems efficiently, and the theoretical analysis of their behaviour. There will also be a brief introduction to complexity theory, the formal study of algorithm performance.
A large variety of algorithms are candidates for study. These include, but are not limited to, the following: greedy algorithms, dynamic programming, network flow algorithms, algorithms for string matching, parallel algorithms, graph algorithms and approximation algorithms.
Upon successful completion, students will have the knowledge and skills to:Upon completion of this course, the student will:
- Analyse a variety of algorithms with practical applications and the resource requirements of each.
- Determine the most suitable algorithm for any given task and then apply it to the problem.
- Demonstrate adequate comprehension of the theory of intractability and prove when certain kinds of problems are intractable.
Assignments (50%); Final Exam (50%)
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WorkloadTwenty-six one-hour lectures, together with occasional seminars
Requisite and Incompatibility
Cormen, Thomas H., Leiserson, Charles E. & Rivest, Ronald L. Introduction to Algorithms, The MIT Electrical Engineering and Computer Science Series. The MIT Press, Cambridge, Massachusetts, 3rd EDdition, 2009.
Tuition fees are for the academic year indicated at the top of the page.
Commonwealth Support (CSP) Students
If you have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). More information about your student contribution amount for each course at Fees.
- Student Contribution Band:
- Unit value:
- 6 units
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