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• USB Stick or portable hard drive with enough capacity to store files associated with the course and formatted as "exFAT" to provide suitable compatability between MacOS and Windows.
• Stereo headphones with a 6.5mm male adaptor. Recommended Type: Closed-Back, Over-the-Ear  Headphones.
• Note – students must bring both their USB storage and Headphones (with adaptor) to university, as they are required for various classes, completing exercises and for using laboratories and studios.

In order to minimise risk in noise-prone situations, the Conservatorium makes both reusable gel ear-plugs and disposable foam ear-plugs available to students and staff free of charge at all times. Students and staff are also urged to consider purchase of customised personal hearing protection.

For more information regarding sound levels, hearing and hearing loss please refer both to the full content of the O'Brien Report and to the excellent publication by Canadian audiologist/academic Marshall Chasin, entitled Hear the Music: Hearing Loss Prevention for Musicians both available here: 

Collins, Nick. Introduction to Computer Music. Chichester, U.K.: John Wiley & Sons, 2010.

Elsea, Peter author. The Art and Technique of Electroacoustic Music. A-R Editions, Inc., 2013.

Essl, Karlheinz. Algorithmic Composition. Cambridge University Press, 2007. doi:10.1017/CCOL9780521868617.008.

Manning, Peter. Electronic and Computer Music. New York: New York: Oxford University Press, 2004. doi:10.1093/acprof:oso/9780199746392.001.0001.

Miranda, Eduardo Reck editor, and John Al editor Biles. Evolutionary Computer Music. Springer London, 2007.

Miranda, Eduardo Reck editor, and Eduardo Reck editor Mirando. A-Life for Music : Music and Computer Models of Living Systems. A-R Editions, 2011.

Nierhaus, Gerhard editor. Patterns of Intuition Musical Creativity in the Light of Algorithmic Composition. Springer Netherlands : Imprint: Springer, 2015.

Pareyon, Gabriel, Silvia Pina-Romero, Octavio A. Agustín-Aquino, and Emilio Lluis-Puebla. The Musical-Mathematical Mind : Patterns and Transformations. Cham: Cham: Springer, 2017. doi:10.1007/978-3-319-47337-6.

Roads, Curtis. The Computer Music Tutorial. Cambridge, Mass.: MIT Press, 1996.

———. Microsound. Cambridge, Mass.: MIT Press, 2001.

———. Composing Electronic Music a New Aesthetic. Oxford University Press, 2015.

Rowe, Robert. Machine Musicianship. Cambridge, Mass.: MIT Press, 2001.

Taube, Heinrich. Notes from the Metalevel : An Introduction to Computer Composition. London: London: Routledge, 2004. doi:10.4324/9781315078182.

Wilson, Scott Nov, Nick Collins, and David Cottle. The Supercollider Book. Cambridge, Mass.: MIT Press, 2011.

• SuperCollider.  2019. 18 July 2019. <>.

MyUni is a crucial part of this course and will provide students with access to assessment and learning materials, such as quizzes, discussion boards, slide presentations, readings, links, sound and video. Materials will be provided on a topic-by-topic basis over the semester: .

The course structure and content is delivered through a range of classes and materials. The classes in this course consist of lectures and workshops.

Lecture

• Lectures will deliver a specific topic each week. The topic will consist of ideas and concepts; technologies; and  practitioners in the field. Students must view the  lecture prior to the attending the workshop.

Workshop

• Workshops will explore a wide range of practical aspects of the course and its associated topics and concepts.
• Students will be set regular practical tasks as part of their portfolio assessment and maybe required to present their work during the workshop.
• Although workshops will from time to time contain presentations from the instructor, the workshop will largely be an opportunity for students to obtain assistance with their practical and creative development and practice. Students need to actively and on a week-by-week basis maintain their practical and creative development, using the workshop to raise issues and solve problems.
• Finally, the workshops provide a forum by which students can begin to explore their own ideas and practice using lecture materials as inspiration and points of departure.

This course consists of up to 32 hours of online or direct contact or structured non-contact where students will play an active role in the practice, refinement, consolidation and extension of their knowledge and understanding. This includes lectures: 1 hour per week over 12 weeks & workshops: 2 hours per week over 10 weeks. In addition students will spend a minimum of 124 non-contact hours over the duration of the course on self-initiated learning and research, reading, writing, practice and assessment in order to pass the course, making the minimum workload 156 hours.

Topics

1. Machine Music
2. The history of programmable machines (Jacquard looms, automata etc);Babbages Difference and Analytical Engines;Turing machines; universal computers; the limits of computation; indeterminacyand incompleteness; the Turing test applied to music.
3. Music and mathematics; music, mathematics, geometry and logic as formalsystems or abstractsystems of thought; logical operations; weird computers; symmetry and form;group theory; pitch and temporal symmetry; the symmetry of scales.
4. Probability and random processes: randomness and pseudo-randomness;probabilitydistributions; conditional probabilities; John Cage and I Ching computation.
5. Simple algorithmic procedures applied to composition; deterministic andprobabilisticalgorithms.
6. The physical and psycho-acoustic foundations of tuning; frequency vs. pitch;pitch as adimension of timbre; quantum indeterminacy and the limits of tuning; theimplementation of tuning systems in synthesizers and comput
7. Composition as process: rule-governed composition from ancient models to themodern era.
8. The early history of computer music composition. Early programminglanguages: MUSIGOL,MUSIC IV, MUSIC V; Lejaren Hiller: Illiac Suite. James Tenney: Stochastic Quartet. Charles Dodge: EarthsMagnetic Field. Xenakis: SMP (Stochastic Music Program.)
9. Markov models in computer music.
10. Generative grammar in computer music.
11. Artificial neural networks and artificial intelligence in computer music.

Learning Outcomes

• Knowledge of the historical context of computer music
• Ability to analyse formal systems and apply them to music
• Ability to apply algorithmic methods to musical composition
• Ability to write programs to realise compositions with algorithmic structures
• Ability to solve problems in programming and implementation
• Ability to distinguish between technical and aesthetic aims, and to be able to articulate both aspects of a project

This course will involve using the resources of the Electronic Music Unit (EMU). This includes facilities such as studios, recording spaces and digital audio workstations.

In order for students to complete the course they must gain ongoing and permanent access to EMU. Access and use of EMU is based upon  completing the EMU Access Test.

More information can be found here:

Except where otherwise indicated by the lecturer, tutor or workshop instructor – mobile phones, laptops, PDAs, recording devices and other similar technology must be switched off before lessons or classes begin, and kept off for the duration.

Due Dates:
Specific information regarding due dates is provided on myUni.

Formative Assessment:
Classes will contain embedded formative assessment tasks that may include student presentations, discussions, practical exercises, demonstrations and out-of-class work that will enable students to engage with the practical and theoretical concepts presented in order to complete their summative assessments.

All students must complete the requirements under “SPECIFIC COURSE REQUIREMENTS ‘EMU Facilities Access Provisions’”. Students who fail to complete these items may be deemed to have failed the course.

Students are expected to attend all classes. If a student fails to attend at least 70% of tutorials or workshops in a course the student may be deemed to have failed that course, irrespective of assessments completed. Students who arrive 10 minutes or later after the start of a class will be marked as absent.

Extenuating circumstances may occasionally affect a student’s ability to participate in a rehearsal, workshop, class, lecture, tutorial or performance. In such cases a student should email their course coordinator regarding the circumstances within 7 days and include the following information:

• Type of Leave: Sick Leave, Compassionate Leave or Professional Development Leave
• Student Name
• Student ID
• Dates of Leave
• Total Number of Days
• Reason for Absence
• Supporting Documentation (e.g. medical certicificate, counsellor note etc)

Students must be available during the identified University teaching, academic and examination periods. Students are not entitled to sit an examination or submit an assessment at another time, nor are they entitled to any other concessions if an examination or assessment conflicts with a planned vacation or special event. Results from assessments and examinations are usually sent to students via email and/or myUni.

Assignments where late submissions are permitted and that are submitted after the due date and time will incur a 2% penalty (from the assignment total of 100%) per day (24 hour period) for a maximum of 7 days (including weekends and public holidays ). 

• an assignment that is 3 days late: raw score of 80% - 6 marks lateness deduction = 74% final mark.

• typically this does not apply to assessments where the assessment is conducted at a fixed time and location, such as an exam, workshop, practical test, performance or presentation – please refer to the individual assessments for further information.
• for work with a formal extension, these penalties will apply from the extended due date.

There will be a cut-off date for each assignment 7 days (including weekends and public holidays) after the original due date unless otherwise stipulated on MyUni. Work will not be accepted after the cut-off date, and a mark of zero will automatically be awarded for the assignment.