Membership plan: Going Deeper | Topics: Music Production
Course overview
For centuries, musicians have incorporated chance-based elements into their compositions, first through coin flips and dice rolls and more recently through computer software. Today, building music-oriented algorithmic systems is easier than ever with Max.
What you'll learn
In this workshop you will learn a variety of algorithmic processes and useful tools to construct your own systems: including drunken walks, list manipulation and step-sequencer pattern generation. Primarily focusing on MIDI-controlled instruments, you will gain an understanding of how chance can be factored into numerous aspects of composition, from melody and harmony to overall piece structure and instrumentation.
By the end of the workshop you will have built a system for algorithmically generating a short multi-instrumental composition which you will be able to go on to improve and expand upon to fit your own preferences.
Who is this course for?
Learn to construct music-generating algorithms in Max, to compose semi-autonomously or supplement your compositional practice.
Course content
Max patches
Part 1 - MIDI Setup & Guitar Synth
Part 2 - Sequencer Setup
Part 3 - Basic Melody Generation
Part 4 - Bell Synth Setup
Part 5 - Ostinato Generation
Part 6 - Chord Voicing Generation & Organ Synth
Part 7 - Chord Sequence Generation
Part 8 - Transport Setup
Part 9 - Piece Structuring and Final Composition
Requirements
You should be comfortable with the general workflow and data formatting in Max
Knowledge of MIDI format and routing to DAWs (Ableton, Logic etc) would be a plus, although Max instruments will be provided
A basic familiarity with Git, C++ and audio processing
You should have some basic knowledge of music theory: chords, scales, modes etc
Meet your instructor
Samuel Pearce-Davies is a composer, performer, music programmer and Max hacker living in Cornwall, UK.
With a classical music background, it was his introduction to Max/MSP during undergraduate studies at Falmouth University that sparked Sam’s passion for music programming and algorithmic composition.
Going on to complete a Research Masters in computer music, Sam is now studying a PhD at Plymouth University in music-focused AI.
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