Digital Signal Processing (DSP) From Ground Up in Python (Udemy.com)

Practical DSP in Python : Over 70 examples, FFT,Filter Design, IIR,FIR, Window Filters,Convolution,Linear Systems etc

( 88 Reviews )

Created by: Israel Gbati

Produced in 2021

What you will learn

Develop the Convolution Kernel algorithm in Python
Design and develop 17 different window filters in Python
Develop the Discrete Fourier Transform (DFT) algorithm in Python
Design and develop Type I Chebyshev filters in Python
Design and develop Type II Chebyshev filters in Python
Develop the Inverse Discrete Fourier Transform (IDFT) algorithm in Pyhton
Develop the Fast Fourier Transform (FFT) algorithm in Python
Perform spectral analysis on ECG signals in Python
Design and develop Windowed-Sinc filters in Python
Design and develop Finite Impulse Response (FIR) filters in Python
Design and develop Infinite Impulse Response (IIR) filters in Python
Develop the First Difference algorithm in Python
Develop the Running Sum algorithm in Python
Develop the Moving Average filter algorithm in Python
Develop the Recursive Moving Average filter algorithm in Python
Desig

Quality Score

Content Quality

Video Quality

Qualified Instructor

Course Pace

Course Depth & Coverage

Overall Score : 80 / 100

Course Description

With a programming based approach, this course is designed to give you a solid foundation in the most useful aspects of Digital Signal Processing (DSP) in an engaging and easy to follow way. The goal of this course is to present practical techniques while avoiding obstacles of abstract mathematical theories. To achieve this goal, the DSP techniques are explained in plain language, not simply proven to be true through mathematical derivations. Still keeping it simple, this course comes in different programming languages and hardware architectures so that students can put the techniques to practice using a programming language or hardware architecture of their choice. This version of the course uses the Python programming language.
By the end of this course you should be able develop the Convolution Kernel algorithm in python, develop 17 different types of window filters in python, develop the Discrete Fourier Transform (DFT) algorithm in python, develop the Inverse Discrete Fourier Transform (IDFT) algorithm in pyhton, design and develop Finite Impulse Response (FIR) filters in python, design and develop Infinite Impulse Response (IIR) filters in python, develop Type I Chebyshev filters in python, develop Type II Chebyshev filters in python, perform spectral analysis on ECG signals in python, develop Butterworth filters in python, develop Match filters in python,simulate Linear Time Invariant (LTI) Systems in python, even give a lecture on DSP and so much more. Please take a look at the full course curriculum.
Who this course is for:
People working in the field of signal processingUniversity students taking classes in signal processingPython developers who wish to expand their skillsPeople who want to understand signal processing practically and apply it to their respective fields.

Time: 12.5h

Instructor Details

Israel Gbati

4.0 Rating
88 Reviews

My name is Israel, I have been researching and working in the embedded system space for over 7 years. On Udemy I have trained tens of thousands of students in embedded systems focusing on topics such as Assembly Programming, Real-time Operating Systems Design, Firmware Development and Digital Signal Processing. I am able to teach these topics because in my everyday work I apply concepts from these topics.
Join one of my courses and see how it goes. You can always request a refund.

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Reviews

4.0

88 total reviews

5 star 4 star 3 star 2 star 1 star

Write a Review

By Phil Samandar on 12/13/2020

Topic substance good. Flow can be better. Jupyter or Spyder better than IDLE to teach

By Nathan Mogk on 11/12/2020

Great course overall, I wish there were some more application focus for the later topics. Not just "what is the call" to generate x filter, but how one might use it.

By Fareed Suri on 11/11/2020

It goes into good detail with appropriate speed, but would be nice if at times we are not just seeing a frozen screen with narration of equations going on. Also most of the lectures regarding coding are just repetition.

By Yusif Ibrahimov on 11/7/2020

Speech tone is not attractive
I don't understand the theory part

By Prafull Patil on 10/16/2020

audio and video quality is not good.

By Christian Valdivieso on 10/10/2020

Bastante bueno, me gustaran ms ejemplos del rea mdica

By Danilo Dara on 9/27/2020

instructions were clear. However, much too slow.
A BIG lot of time spent by typing on the keyboard, and much of that by reviewing typos. Coming with some pre-written code just to be run and commented would have made things MUCH faster.
I will add that there are MANY mistakes in the code, some of them could be even recognized by looking at the plots, but since there was no comments nor diagrams review, this was not understood.
Moreover, the audio is barely hearable here and there, due to sudden volume reduction.
So, the point is - there was no review at all by the author.
However, the topics are presented quite well, and the speaker is prepared and understandable.

By Leonardo Rosenfeld on 9/17/2020

a great course very taming

By Anush Kapoor on 9/3/2020

The course is well-structured for quick learning. The instructor is good at delivering the concepts. Some portions and syntaxes in the code are not well-explained.

By Emil Gejl Lauritzen on 8/26/2020

Easy to understand og great pacing in terms of information transfered to the viewer

By Ashok Mulchandani on 8/6/2020

It's good course helping hand-on practise using python on a very abstract topic like digital signal processing. 3 star because quality of video and sound could potentially be improved. I thank the trainer for hard work gone into preparing such a detailed course

By Omar Abu-Hijleh on 8/2/2020