Universidad Nacional Autónoma de México
Composición algorítmica en Supercollider

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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 Courses4,006 learners

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4.5

22 reviews

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JA
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Reviewed on Sep 7, 2020

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Reviewed on Aug 30, 2020

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Reviewed on May 10, 2021

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