Universidad Nacional Autónoma de México
Composición algorítmica en Supercollider
Universidad Nacional Autónoma de México

Composición algorítmica en Supercollider

This course is part of multiple programs.

Mauro Herrera Machuca
Cristian Manuel Bañuelos Hinojosa

Instructors: Mauro Herrera Machuca

1,744 already enrolled

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Gain insight into a topic and learn the fundamentals.
4.5

(22 reviews)

Intermediate level
Some related experience required
6 hours to complete
3 weeks at 2 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
4.5

(22 reviews)

Intermediate level
Some related experience required
6 hours to complete
3 weeks at 2 hours a week
Flexible schedule
Learn at your own pace

Details to know

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Assessments

3 assignments

Taught in Spanish

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There are 4 modules in this course

En este primer módulo se introducirán los principales elementos del ambiente de programación SuperCollider. Entre otras cosas, se revisarán los principales generadores de señal (UGENS) y aprenderemos a cargar y manipular archivos de audio.

What's included

3 videos4 readings1 assignment1 discussion prompt

En este segundo módulo aprenderemos a generar sintetizadores y secuenciadores en SuperCollider. Veremos objetos que sirven para definir procesos de síntesis (SynthDefs) y otros que generan rutinas y patrones (Pbinds, Pdefs, Pseqs).

What's included

3 videos2 readings1 assignment

LLegamos finalmente a nuestro módulo 3. Aquí, aprenderemos algunas herramientas de síntesis avanzada, como son objetos de síntesis granular, sintetizadores multicanal y generadores de series basadas en patrones. Todo esto permitirá llevar a un nivel más alto las herramientas de síntesis que vimos en los módulos pasados.

What's included

3 videos2 readings1 assignment1 discussion prompt

En este módulo revisaremos algunas herramientas de composición algorítmica que sirven para vincular los procesos de síntesis con el “mundo real”, se a partir de metáforas del funcionamiento biológico (particularmente de la genética), o sea a partir de la asignación de sonido a datos que tomamos de fenómenos físicos (sonificación, musificación).

What's included

9 videos1 reading1 peer review1 discussion prompt

Instructors

Instructor ratings
3.8 (7 ratings)
Mauro Herrera Machuca
Universidad Nacional Autónoma de México
2 Courses4,004 learners

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4.5

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