MAT1830 – Discrete mathematics for computer science
This unit introduces fundamental discrete mathematics topics including combinatorics, sets, relations and functions; methods of logic and proof, especially proof by induction; probability theory, Bayes’ theorem; recursion; recurrence relations; trees and other graphs. It establishes the mathematical basis required for studies in Computer Science and Software Engineering.
Faculty of Information Technology
Study level:
Undergraduate
Open to exchange or study abroad students?
Owning organisational unit:
Faculty of Information Technology
Credit points:
Computer Science Tutoring
Offerings OCT-MY-01-MALAYSIA-ON-CAMPUS
Location: Malaysia
Teaching period: October intake teaching period, Malaysia campus Attendance mode: On-campus
S1-01-CLAYTON-ON-CAMPUS
Location: Clayton
Teaching period: First semester Attendance mode: On-campus
S1-01-MALAYSIA-ON-CAMPUS
Location: Malaysia
Teaching period: First semester Attendance mode: On-campus
S2-01-MALAYSIA-ON-CAMPUS
Location: Malaysia
Teaching period: Second semester Attendance mode: On-campus
Requisites
Programming Help, Add QQ: 749389476
Rules Enrolment Rule
Prerequisite: VCE Specialist Mathematics or Mathematical Methods units 3 and 4 with a raw study score of at least 25 or Further maths with a raw study score of at least 35.
Prohibition: MAT1077, MTH1112
Prohibition
ITI9004 6 CP Mathematical foundations for data science and AI
Chief Examiner(s) Associate Professor Daniel Horsley
Email: Offering(s):
Applies to all offerings
Unit Coordinator(s)
Learning outcomes
On successful completion of this unit, you should be able to:
1. Identify basic methods of proof, particularly induction, and apply them to solve problems in mathematics and computer science;
2. Manipulate sets, relations, functions and their associated concepts, and apply these to solve problems in mathematics and computer science;
3. Use and analyse simple first and second order recurrence relations;
4. Use trees and graphs to solve problems in computer science;
5. Apply counting principles in combinatorics;
6. Describe the principles of elementary probability theory, evaluate conditional probabilities and use Bayes’ Theorem.
Mr Tham WengKee
Email: Offering(s):
First semester, Malaysia, On-campus Second semester, Malaysia, On-campus
Associate Professor Daniel Horsley
Email: Offering(s):
First semester, Clayton, On-campus
Assessment
Continuous assessment Value %: 40
Scheduled final assessment (3 hours and 10 minutes)
Value %: 60
Hurdle type: Threshold
Hurdle description:
If you would otherwise have passed the unit but you do not achieve at least 45% of the marks available for the end of semester examination you will receive a Hurdle Fail (NH) grade and a mark of 45 on your transcript.
Teaching approach Active learning
Scheduled teaching activities Applied sessions
Total hours: 22 hours Offerings:
October intake teaching period, Malaysia campus, Malaysia, On-campus Second semester, Malaysia, On-campus
Total hours: 22 hours Offerings:
Workload requirements Workload
Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled online and face to face learning activities and independent study. Independent study may include associated reading and preparation for scheduled activities. Applied sessions start from Week 2 of the semester.
First semester, Clayton, On-campus First semester, Malaysia, On-campus
Total hours: 36 hours Offerings:
First semester, Clayton, On-campus First semester, Malaysia, On-campus
Total hours: 36 hours Offerings:
October intake teaching period, Malaysia campus, Malaysia, On-campus Second semester, Malaysia, On-campus
Learning resources
Required resources
Course notes booklet (available as a pdf from the course Moodle page
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Availability in areas of study
Applied mathematics Computational science Mathematics
Software engineering
Recommended resources
The following textbooks are available at the library and may prove useful if you want additional resources beyond the course notes. It is not recommended that you buy them unless you find that you need your own copy.
“Discrete Mathematics” (7th Ed) by Richard Johnsonbaugh. ISBN: 0131354302.
“Discrete Mathematics for Computing” (3rd Ed) by Peter Grossman. ISBN: 9780230216112
Technology resources
Students should regularly check the course Moodle page for announcements. Students may bring whatever resources they wish to classes.