Udemy – How the Fourier Transform Works 2025-7

Updated August 10, 2026 3.2 GB

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Description

How the Fourier Transform Works. This course takes a completely intuitive and practical approach to explaining the Fourier transform without using complex mathematical language and is designed for students and engineers who are looking for a deep and concrete understanding of the concept. The instructor, an electronics engineer with 25 years of experience in research and development, offers a new and accessible way to learn the topic, leaving aside technical jargon and difficult equations. Rather than relying on complex algebraic calculations, the course uses visual explanations, storytelling, and illustrative animations to clearly demonstrate the real-world application of the Fourier transform in signal and system analysis. Through practical examples and step-by-step exercises, participants learn how this mathematical tool works in real-world situations and how it can be used to solve engineering problems. This teaching method ensures that even those who have struggled with the Fourier transform for years will be able to grasp this fundamental concept in a consistent and clear manner.

What you will learn

Intuitive and deep understanding:
Gain an intuitive and deep understanding of how the Fourier transform works, by visualizing complex concepts through animations and diagrams.
Signal analysis:
Understanding how sine waves form the “basic building blocks of signals.”
Understand why the Fourier transform is essential for analyzing everyday signals such as sound, images, or radio waves.
Mastery of key concepts:
Understand the concept of “Convolution” and its vital role as a “bridge to the Frequency Domain”.
Analysis of periodic and non-periodic signals:
Ability to apply Fourier Series to detect frequencies in repetitive signals.
The ability to apply the Fourier transform to detect frequencies in signals that do not repeat.
Strong theoretical foundations:
Building a strong theoretical foundation in the Fourier transform, which is essential for practical implementations such as DFT (Discrete Fourier Transform) and FFT (Fast Fourier Transform).
Understanding the limitations:
Recognize the limitations of the Fourier transform, which involve infinities and make its application to everyday random signals impractical, and explore some solutions to overcome these problems.
Creating lasting insights:
Go beyond rote memorization and develop a deep, practical understanding of signal analysis principles that can be directly applied to the engineering profession.

This course is suitable for people who:

Engineering students:
Electrical, electronic, mechanical, or computer engineering students seeking to master one of the key tools used in signals and systems.
University students in engineering, physics, mathematics, and computer science who need a clear and intuitive foundation in the Fourier transform.
Aspiring engineers:
Engineers who want a clear and intuitive foundation in frequency domain analysis.
Active specialists:
Working engineers (electrical, mechanical, software, data scientists) who want to really understand the Fourier transform for their professional work, especially if they struggled with it in college.
Professionals looking to update or deepen their understanding of signal processing fundamentals.
Curious people:
Curious individuals and lifelong learners who are fascinated by how complex signals are analyzed and are looking for a highly visual and conceptual learning experience.

Course details

Publisher: Udemy
Instructor: Mark Newman
Training level: Beginner to advanced
Training duration: 3 hours and 33 minutes
Number of lessons: 36

Course topics

Prerequisites for the How the Fourier Transform Works course

Designed for university-level students seeking a deeper, intuitive understanding of signals and systems.
A basic grasp of algebraic manipulation and trigonometry is beneficial, but the course is specifically built to explain complex math visually.
No prior experience with the Fourier Transform or advanced mathematical degrees are required.
Bring your curiosity and a willingness to “see” math in a new, intuitive way!