| Module Code | CSU12002 |
| Module Name | Mathematics II |
| ECTS Weighting [1] | 5 ECTS |
| Semester Taught | Semester 2 |
| Module Coordinator/s | Laura Byrne |
Module Learning Outcomes
On successful completion of this module, students will be able to:
- Use the language, notation and methods of symbolic logic, set theory and number theory;
- Produce coherent, convincing mathematical proofs using formal symbol manipulation and logical reasoning;
- Distinguish valid from invalid arguments;
- Demonstrate the use of set theory in applications to computer science;
- State and prove theorems in number theory;
- Relate and apply concepts from number theory to practical application in computer science.
Module Content
Mathematics is of interest to computer scientists due to the fact that it is both practical and theoretical in nature. Not only does it have a myriad of applications (e.g. in machine learning and cryptography), it is also of intrinsic interest to theoretical computer scientists. This module aims to reflect these properties by providing students with an introduction to the discrete mathematics which lies at the foundation of all reasoning about computer systems.
The module aims to develop student skills in propositional and predicate logic, set theory and number theory. Students are actively encouraged to exercise these skills in applications that arise in computer science and discrete mathematics. In particular, students should develop some key skills in formal mathematical proof construction.
The module also aims to encourage and foster the development of independent, reflective learning skills. During the module it is expected that students will adapt their learning style to become more independent, self-motivated learners.
Teaching and Learning Methods
The module will employ a variety of teaching and learning methods including formal lectures, large group problem solving classes and small group tutorials.
Assessment Details
| Assessment Component | Brief Description | Learning Outcomes Addressed | % of Total | Week Set | Week Due |
| Examination | 2 hour Realtime Online Examination | LO1, LO2, LO3, LO4, LO5, LO6 | 65% | N/A | N/A |
| Mid-Semester Test | Mid-Semester Test | LO1, LO2, LO3, | 20% | Week 7 | Week 7 |
| Assignments | Assignments | LO1, LO2, LO3, LO4, LO5, LO6 | 15% | Week 3, 9 | Week 5, 12 |
Note that it may be necessary to reduce the number of assessed assignments (if insufficient demonstrators are available). The weights of these assignments will be redistributed over the other assignments in the semester.
Reassessment Details
Realtime online Examination 2 hours, 100%.
Contact Hours and Indicative Student Workload
| Contact Hours (scheduled hours per student over full module), broken down by: | 44 hours |
| Lecture | 33 hours |
| Tutorial or seminar | 11 hours |
| Independent study (outside scheduled contact hours), broken down by: | 72 hours |
| Preparation for classes and review of material (including preparation for examination, if applicable) | 36 hours |
| Completion of assessments (including examination, if applicable) | 36 hours |
| Total Hours | 116 hours |
Required Reading List
- Discrete Mathematics and Its Applications, Kenneth Rosen (McGraw Hill).
Module Pre-requisites
Prerequisite modules: CSU11001
Other/alternative non-module prerequisites: N/A
Module Co-requisites
N/A