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Module

CSC3423 : Biologically-inspired Computing

  • Offered for Year: 2020/21
  • 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

Please note that module leaders are reviewing the module teaching and assessment methods for Semester 2 modules, in light of the Covid-19 restrictions. There may also be a few further changes to Semester 1 modules. Final information will be available by the end of August 2020 in for Semester 1 modules and the end of October 2020 for Semester 2 modules.

Teaching Activities
Category Activity Number Length Student Hours Comment
Structured Guided LearningLecture materials300:3015:00Materials for lectures (split into 30 sessions) non synchronous online
Guided Independent StudyAssessment preparation and completion121:0012:00Lec follow up
Guided Independent StudyAssessment preparation and completion201:0020:00coursework 1
Guided Independent StudyAssessment preparation and completion201:0020:00coursework 2
Scheduled Learning And Teaching ActivitiesPractical81:008:00Practicals, non-synchronous online
Guided Independent StudyIndependent study161:0016:00Background reading
Scheduled Learning And Teaching ActivitiesModule talk60:454:30x6 PiP sessions (also online) to ask questions on the practicals and coursework - 45 mins each
Scheduled Learning And Teaching ActivitiesModule talk90:304:30synchronous online sessions, one per week to ask questions on the lectures (x9 30 mins)
Total100:00
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

Please note that module leaders are reviewing the module teaching and assessment methods for Semester 2 modules, in light of the Covid-19 restrictions. There may also be a few further changes to Semester 1 modules. Final information will be available by the end of August 2020 in for Semester 1 modules and the end of October 2020 for Semester 2 modules.

The format of resits will be determined by the Board of Examiners

Other Assessment
Description Semester When Set Percentage Comment
Practical/lab report1M50Optimisation coursework (2000 words)
Practical/lab report1M50Machine learning coursework (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