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Audio Engineering

Digital Signal Processing for Audio Engineers

4 weeks
0 Learners
eulerfoldeulerfold
Jul 23

“FFT, filtering, and spectral analysis: the math behind every audio plugin and music tool. This comprehensive curriculum is designed to give you hands-on experience with Digital Signal Processing for Audio Engineers.”

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About this Course

FFT, filtering, and spectral analysis: the math behind every audio plugin and music tool. This comprehensive curriculum is designed to give you hands-on experience with Digital Signal Processing for Audio Engineers. This Audio Engineering curriculum is designed to give you hands-on experience and deep conceptual understanding. Across 4 intensive modules, you'll tackle real-world challenges and build practical projects that reinforce your learning. By the end of this journey, you'll have the skills and proof of work to demonstrate your expertise.

What you'll learn

Understand analog-to-digital conversion, aliasing, and the Nyquist theorem in code.
Implement the FFT to analyze the frequency spectrum of audio signals.
Design and apply low-pass and high-pass filters to audio signals.
Build a real-time spectrogram and apply effects to live audio streams.

Prerequisites

intermediate Level

Requires basic familiarity with the tech stack.

  • Familiarity with core concepts

Ideal for

Audio Engineers & DSP Enthusiasts

Audio Engineering Professionals
Tech Enthusiasts
W1

Signals, Waves & Sampling Theory

Understand analog-to-digital conversion, aliasing, and the Nyquist theorem in code.

3 videos•83m
3 readings
3 topics
1 homework
Learn

Topics

1.1
Analog vs Digital Audio
50 minutes
1.2
The Nyquist-Shannon Theorem
21 minutes
1.3
Bit Depth & Quantization Error
12 minutes

Study Resources

→Nyquist frequency - Wikipedia→Nyquist–Shannon sampling theorem - Wikipedia→Nyquist Sampling Theorem - Statement, Working, Aliasing, Applications - GeeksforGeeks
W2

The Fast Fourier Transform (FFT)

Implement the FFT to analyze the frequency spectrum of audio signals.

3 videos•29m
3 readings
3 topics
1 homework
Learn
W3

Digital Filtering (FIR & IIR)

Design and apply low-pass and high-pass filters to audio signals.

3 videos•64m
3 readings
3 topics
1 homework
Learn
W4

Spectral Analysis & Real-Time Audio Processing

Build a real-time spectrogram and apply effects to live audio streams.

3 videos•56m
3 readings
3 topics
1 homework
Learn
01

Learn

Watch curated videos and read study resources

02

Practice

Practice what you learned

03

Build Projects

Build projects using your new gained knowledge

04

Submit & Verify

Submit your project and get verified by our system

References

01Nyquist frequency - Wikipedia
02Nyquist–Shannon sampling theorem - Wikipedia
03Nyquist Sampling Theorem - Statement, Working, Aliasing, Applications - GeeksforGeeks
04Audio FFT - A Deep Dive into Audio Signal Processing
05Sound Spectrum Analyzer – Free Real-Time FFT Tool
06snehasb-hub/audio_fft_project - GitHub
07Free Digital Filter Designer (FIR / IIR) | Simulations4All
08Interactive Digital Filter Designer (FIR/IIR Sim)
09Topic 8: Filter Design: IIR - Columbia University
10GitHub - srrtth/Spectrogram-generator-from-live-audio: This code generates a live spectrogram from the connected microphone. · GitHub
11A Real-time Audio Spectrogram with Application to Sound-Driven Games in Python 3, Pygame and Pyaudio | Renyuan Lyu | PyCon APAC 2014
12Complete Guide to Audio Processing in Python: From Spectrograms to Real-Time Applications - DEV Community

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