Digital Signal Processing
Course Index
31 Lessons · 3 Levels
Implement DSP algorithms in Python from scratch — FFT, FIR/IIR filter design, wavelets, adaptive filtering, and real-time processing with sounddevice. Covers biomedical ECG/EEG signals, GPU-accelerated CuPy DSP, deep learning for signals & 4 real builds.
31Lessons
3Levels
4Projects
FreeAccess
Level IDSP Foundations & Spectral AnalysisLessons 1–10
LESSON 01
DSP: Global Developer Overview
LESSON 02
Discrete-Time Signals & Systems
LESSON 03
Python DSP Setup: NumPy & SciPy
LESSON 04
Sampling Theory & Nyquist Theorem
LESSON 05
Convolution & Impulse Response
LESSON 06
Z-Transform & Transfer Functions
LESSON 07
Discrete Fourier Transform (DFT)
LESSON 08
Fast Fourier Transform (FFT)
LESSON 09
Short-Time Fourier Transform (STFT)
LESSON 10
Power Spectral Density (PSD)
Level IIFilter Design, Transforms & ApplicationsLessons 11–22
LESSON 11
FIR Filter Design
LESSON 12
IIR Filter: Butterworth & Chebyshev
LESSON 13
Window Functions in Filter Design
LESSON 14
Frequency Response & Pole-Zero
LESSON 15
Multirate DSP: Decimation & Interp
LESSON 16
Adaptive Filtering: LMS & RLS
LESSON 17
Wavelet Transform & PyWavelets
LESSON 18
Signal Denoising Techniques
LESSON 19
Cross-Correlation & Detection
LESSON 20
DSP for Audio Signals
LESSON 21
Biomedical DSP: ECG & EEG
LESSON 22
DSP for Image Processing
Level IIIReal-Time, ML & ProjectsLessons 23–31
LESSON 23
Real-Time DSP: Python & sounddevice
LESSON 24
Deep Learning for Signal Processing
LESSON 25
DSP for IoT & Embedded Systems
LESSON 26
Radar & Communications DSP
LESSON 27
GPU-Accelerated DSP with CuPy
LESSON 28
Build an Audio Equalizer
LESSON 29
Build a Signal Denoising Pipeline
LESSON 30
Build a Real-Time Spectrum Analyzer
LESSON 31
Build an ECG Peak Detection System