# Courses Offered

COMP2121 Discrete Mathematics

### COMP2121 Discrete Mathematics

2022-23
Instructor(s):Chan Hubert
(Class A) No. of credit(s):6
Ramanathan Ravishankar
(Class B)
Yang Yuxiang
(Class C)
Recommended Learning Hours:
 Lecture: 33 Tutorial: 6
Pre-requisite(s):
Co-requisite(s):
Mutually exclusive with:MATH3600
Remarks:

Course Learning Outcomes

 1 [Abstract Concepts] Understand abstract mathematical concepts which are fundamental to computer science, e.g., logic, sets, functions, basic probability, graph theory. 2 [Proof Techniques] Be able to perform abstract thinking and present logical argument using techniques such as mathematical induction, proof by contradiction. 3 [Basic analysis techniques] able to apply formal reasoning to analyze and enumerate the possible outcomes of a computational problem e.g. model and compute the number of operations using recursion, counting and combinatorics.
Mapping from Course Learning Outcomes to Programme Learning Outcomes
PLO aPLO bPLO cPLO dPLO ePLO fPLO gPLO hPLO iPLO j
CLO 1T,P
CLO 2T,P
CLO 3T,P

T - Teach, P - Practice
For BEng(CompSc) Programme Learning Outcomes, please refer to here.

Syllabus

Calendar Entry:
This course provides students a solid background on discrete mathematics and structures pertinent to computer science. Topics include logic; set theory; mathematical reasoning; counting techniques; discrete probability; trees, graphs, and related algorithms; modeling computation.

Detailed Description:

Basic Concepts Mapped to CLOs
Logic1
Proof Mathematical Reasoning1, 2
Recurrence1, 3
Sets, Relations and Functions1, 2
Counting and Probability Mapped to CLOs
Counting Techniques1, 3
Probability1, 3
Random Variables1, 3
Expectation and Variance1, 2
Graph Theory Mapped to CLOs
Graph Properties1, 2
Euler and Hamiltonian Circuits1, 2, 3
Graph Coloring1, 2, 3

Assessment:
Continuous Assessment: 50%
Written Examination: 50%

Teaching Plan

Please refer to the corresponding Moodle course.

Moodle Course(s)