CSC3423 : Biologically-inspired Computing (Inactive)
- Inactive for Year: 2022/23
- Module Leader(s): Dr Jaume Bacardit
- Teaching Assistant: Mr Chris Napier
- Owning School: Computing
- Teaching Location: Newcastle City Campus
Semesters
| Semester 1 Credit Value: | 10 |
| ECTS Credits: | 5.0 |
Aims
1) To familiarise students with computational concepts and methods inspired by biological systems
2) To introduce the concepts of algorithm design for biologically inspired computing
3) To develop skills in biologically inspired algorithm design with an emphasis on solving real world problems
4) To understand the most appropriate types of algorithms for different data analysis problems and to introduce some of the most appropriate implementation strategies.
Outline Of Syllabus
1. Brief introduction to biological systems and computational tasks of such systems.
2. Evolutionary Computation
3. Swarm Intelligence
4. Neural Networks
5. Cellular Automata
Teaching Methods
Teaching Activities
| Category | Activity | Number | Length | Student Hours | Comment |
|---|---|---|---|---|---|
| Guided Independent Study | Assessment preparation and completion | 20 | 1:00 | 20:00 | coursework 2 |
| Structured Guided Learning | Lecture materials | 30 | 0:30 | 15:00 | Materials for lectures (split into 30 sessions) non synchronous online |
| Guided Independent Study | Assessment preparation and completion | 20 | 1:00 | 20:00 | coursework 1 |
| Guided Independent Study | Assessment preparation and completion | 12 | 1:00 | 12:00 | Lec follow up |
| Scheduled Learning And Teaching Activities | Practical | 8 | 1:00 | 8:00 | Practicals, non-synchronous online |
| Guided Independent Study | Independent study | 16 | 1:00 | 16:00 | Background reading |
| Scheduled Learning And Teaching Activities | Module talk | 9 | 0:30 | 4:30 | synchronous online sessions, one per week to ask questions on the lectures (x9 30 mins) |
| Scheduled Learning And Teaching Activities | Module talk | 6 | 0:45 | 4:30 | x6 PiP sessions (also online) to ask questions on the practicals and coursework - 45 mins each |
| Total | 100:00 |
Teaching Rationale And Relationship
Online lectures will be used to introduce the basic material and the more advanced theoretical topics.
Practical sessions, mostly computer based, will give the student opportunity to build up skills in algorithm design development and implementation.
Assessment Methods
The format of resits will be determined by the Board of Examiners
Other Assessment
| Description | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|
| Practical/lab report | 1 | M | 100 | Optimisation coursework (2000 words) |
Formative Assessments
| Description | Semester | When Set | Comment |
|---|---|---|---|
| Practical/lab report | 1 | M | Machine Learning report (2000 words) |
Assessment Rationale And Relationship
The coursework-based assessment will test skills both the understanding of the students on the covered topics as well as their practical skills in algorithm design and solving real world problems.
Reading Lists
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- CSC3423's Timetable