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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2019/2020

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DRPS : Course Catalogue : Edinburgh College of Art : Music

Undergraduate Course: Algorithmic Composition (MUSI10087)

Course Outline
SchoolEdinburgh College of Art CollegeCollege of Arts, Humanities and Social Sciences
Credit level (Normal year taken)SCQF Level 10 (Year 3 Undergraduate) AvailabilityAvailable to all students
SCQF Credits20 ECTS Credits10
SummaryThis course explores the use of algorithms in music and sound design. You will engage with digital formalisations of processes for sonic ends, engaging with practical and theoretical aspects. The course looks at algorithms as processes in musical composition, in the sonification of data, working with data from video games to generate sound and music, generative music at different scales and in different contexts, the practice of live coding performance, nonlinear composition, and approaches that foreground the algorithm in creative work. Your primary tool for these explorations will be the graphical programming environment MaxMSP.
Course description The ubiquity of algorithmic processes in our daily lives has started to come under greater focus, and algorithms are being explored across a range of dimensions, from ethical, political and philosophical considerations to algorithms as creative, entertaining and aesthetic. The relationships between artistic creativity and machine creativity are of particular significance for contemporary sound producers, sound explorers, and for those working at the border of creative sound and technology.

This course examines algorithms both in practical terms¿how algorithms are effectively implemented in musical and sound design projects, and how they might be in the future¿and in critical terms¿how algorithms change our relationships with sound and creative practices. You will explore past examples of algorithms and processes in musical composition, the sonification of data, working with data from video games to generate sound and music, the practice of live coding performance, macro-, meso-, and micro-level generative music, nonlinear composition, and approaches that foreground the algorithm in creative work. The primary tool for these explorations will be the graphical programming environment MaxMSP - a relevant program for rapidly exploring sonic processes.

Entry Requirements (not applicable to Visiting Students)
Pre-requisites It is RECOMMENDED that students have passed Music 2D: Theory and Practice of Music Technology (MUSI08053)
Co-requisites
Prohibited Combinations Other requirements Students outside of Music should seek approval from the Course Organiser before enrolling on the course.
Information for Visiting Students
Pre-requisitesVisiting students should have experience of digital audio software and an interest in exploring creative coding for creative musical ends.
High Demand Course? Yes
Course Delivery Information
Academic year 2019/20, Available to all students (SV1) Quota:  None
Course Start Semester 2
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 200 ( Lecture Hours 22, Seminar/Tutorial Hours 10, Programme Level Learning and Teaching Hours 4, Directed Learning and Independent Learning Hours 164 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) Two projects will be submitted, worth 35% and 65% respectively. Collaboration is not permitted on either project.

Project 1 (35%): A synthesis and/or signal processing assignment will be completed in a musical programming environment. The result will be the generation of a short piece of music in the form of a sound file.

Project 2 (65%): An algorithmic composition project of the student's own choosing should be realised using any environment or combination thereof presented thus far. The project should be distinct from and clearly more ambitious and substantial than Project 1. The result may be an installation, score, sound file, or interactive computer environment. The project must be agreed in advance with the course organiser.

Both projects should be accompanied by a short (c. 1000 word) report detailing the project goals; the methods used to realise these goals; any problems or interesting points encountered along the way (with their solutions/incorporation); an appraisal/critique of the project; and suggestions as to how, with hindsight, the project may have been improved and how it could be developed in the future. The report should be written in formal academic language, using clearly defined sections; it should correctly reference articles and musical works relevant to the subject matter and include a full bibliography. A CD-ROM containing the patches/programmes/sounds used, as well as a recording of the project, should also be submitted in both cases. More details on both assignments will be provided in a revised project brief document.

Feedback Written feedback will be provided for both Projects.
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. demonstrate insights into algorithmic composition systems and the benefits of such in the top-down planning of musical processes
  2. demonstrate a practical understanding of computer programming paradigms and their relation to and potential generation of compositional structure
  3. demonstrate an understanding and appreciation of the advantages of non-real time computer music systems and when to use them instead of real-time environments
  4. demonstrate an insight into the history, theory, repertoire, and aesthetics of computer music.
Reading List
None
Additional Information
Graduate Attributes and Skills Not entered
Keywordsalgorithmic composition,digital signal processing,computer music
Contacts
Course organiserDr Tom Mudd
Tel: (0131 6)50 2808
Email: tmudd@exseed.ed.ac.uk
Course secretaryMiss Laura Varga
Tel: (0131 6)50 2430
Email: laura.varga@ed.ac.uk
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