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 a | PLO b | PLO c | PLO d | PLO e | PLO f | PLO g | PLO h | PLO i | PLO j |
CLO 1 | T,P | | | | | | | | | |
CLO 2 | T,P | | | | | | | | | |
CLO 3 | | | T,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
|
Logic | 1 |
Proof Mathematical Reasoning | 1, 2 |
Recurrence | 1, 3 |
Sets, Relations and Functions | 1, 2 |
Counting and Probability |
Mapped to CLOs
|
Counting Techniques | 1, 3 |
Probability | 1, 3 |
Random Variables | 1, 3 |
Expectation and Variance | 1, 2 |
Graph Theory |
Mapped to CLOs
|
Graph Properties | 1, 2 |
Euler and Hamiltonian Circuits | 1, 2, 3 |
Graph Coloring | 1, 2, 3 |
|
Assessment:
Continuous Assessment:
50% Written Examination:
50%
|
Teaching Plan |
Please refer to the corresponding Moodle course.
|
Moodle Course(s) |
|