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Free Online Textbooks & Courses

A list of free online textbooks and courses on audio DSP.

  • Discrete Time Signal Processing by Ekeeda
    • A large collection of free DSP video lectures.
  • Julius Orion Smith III Collection
    • A great collection of books and resources by Julius Orion Smith III.
    • Very comprehensive, and covers many topics on the mathematics and applications of audio DSP. Good for getting a solid foundation.
    • Contains code examples in C and MatLab (although GNU Octave can be used as well).
    • Relatively heavy on mathematics.
  • MIT OCW: Signals and Systems by Prof. Dennis Freeman
    • A free online college level course including pre-recorded video lectures, lecture notes, and assignments.
    • Here is a link to the video lectures on Youtube if you can't get the videos to play on their website.
  • projet μ by Yü Fang
    • A great free online course that teaches the basics of DSP from scratch using the C programming language. It's my personal go-to recommendation to beginners.
    • Does a great job of explaining concepts in code, along with helpful graphics.
    • Requires some knowledge of complex numbers and basic integral calculus. (There's really no way around this if you're learning DSP). It is also very Linux-focused, but the course can still be done using Windows or MacOS.
  • The Art of VA Filter Design by Vadim Zavalishin
    • Teaches good techniques for adapting analogue designs into the digital realm.
    • Relatively heavy on mathematics.
  • The Scientist and Engineer's Guide to Digital Signal Processing by Steven W. Smith, Ph.D.
    • A common recommendation from many folks.
    • Focuses on DSP in general, not just audio DSP.
    • Relatively heavy on mathematics.
  • The Theory and Technique of Electronic Music by Miller Puckette
    • Focuses more on musical DSP.
    • Teaches core concepts of many common audio effects and synthesizers.
    • Relatively heavy on mathematics.
  • Think DSP by Allen B. Downey
    • A great free online book for beginners that teaches many fundamental DSP concepts using Python.
    • Teaches concepts from a programming-based approach, rather than an abstract mathematical approach.
    • Requires knowledge of Python, and some knowledge of complex numbers and integral calculus.