Postgraduate Programme and Module Handbook 2023-2024 (archived)
Module COMP52215: Advanced Algorithms and Discrete Systems
Department: Computer Science
COMP52215:
Advanced Algorithms and Discrete Systems
Type |
Tied |
Level |
5 |
Credits |
15 |
Availability |
Available in 2023/24 |
Module Cap |
None. |
Tied to |
G5T109 |
Tied to |
G5T209 |
Tied to |
G5T309 |
Tied to |
G5T409 |
Prerequisites
- PHYS52015 Introduction to Scientific and High Performance Computing
Corequisites
Excluded Combination of Modules
Aims
- Provide advanced knowledge and critical understanding of paradigms, fundamental ideas, algorithms and methods behind the modelling and simulation of discrete systems
- Provide advanced knowledge and critical understanding of paradigms, fundamental ideas and methods behind advanced algorithms
Content
- Advanced Algorithms
- Discrete Systems
Learning Outcomes
- Understanding and critical reflection of advanced ideas, numerical techniques and algorithms used to study discrete models
- Understanding and critical reflection of advanced engineering algorithms in high-performance computing and data analysis
- Basic familiarity with state-of-the-art algorithms to solve large-scale and data intense challenges
- Competence to translate discrete problem descriptions into algorithmic formulations; competent and educated selection of appropriate solution algorithms
- Familiarity with advanced paradigms and modern algorithms underlying scientific computing for discrete systems, and their analysis
Modes of Teaching, Learning and Assessment and how these contribute to
the learning outcomes of the module
- Teaching will be by lectures and workshops.
- The lectures provide the means to give a concise, focused presentation of the subject matter of the module.
- When appropriate, the lectures will also be supported by the distribution of written material, or by information and relevant links on Ultra.
- Regular problem exercises and workshops will give students the chance to develop their theoretical understanding and problem solving skills.
- Students will be able to obtain further help in their studies by approaching their lecturers, either after lectures or at other mutually convenient times.
- Student performance will be summatively assessed through coursework.
- The formative coursework provides opportunities for feedback, for students to gauge their progress and for staff to monitor progress throughout the duration of the module.
Teaching Methods and Learning Hours
Activity |
Number |
Frequency |
Duration |
Total/Hours |
|
Lectures for Advanced Algorithms |
12 |
3 per week |
60 minutes |
12 |
|
Practical Classes for Advanced Algorithms |
4 |
1 per week |
60 minutes |
4 |
|
Lectures for Discrete Systems |
12 |
3 per week |
60 minutes |
12 |
|
Practical Classes for Discrete Systems |
4 |
1 per week |
60 minutes |
4 |
|
Self Study |
|
|
|
118 |
|
Total |
|
|
|
150 |
|
Summative Assessment
Component: Summative Coursework |
Component Weighting: 100% |
Element |
Length / duration |
Element Weighting |
Resit Opportunity |
Advanced Algorithms Coursework |
1 week |
50% |
Yes |
Discrete Systems Coursework |
1 week |
50% |
Yes |
n/a
■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University