This course provides a comprehensive, enterprise-focused introduction to deepfake detection, digital content authentication, and organisational response to synthetic media threats. You will begin by defining deepfakes, distinguishing them from traditional media manipulation such as Photoshop and CGI, and exploring how core generative AI architectures—Generative Adversarial Networks (GANs), autoencoders, and Diffusion Models—produce synthetic media and create distinct detection challenges. You will map the evolving deepfake threat landscape for organisations, covering major attack vectors, real-world case studies, criminal tools and services, regulatory pressures, and the business, security, and reputational impact of successful attacks.

AI-Powered Deepfake Detection: Image, Video & Audio

AI-Powered Deepfake Detection: Image, Video & Audio

Instructor: Board Infinity
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Gain insight into a topic and learn the fundamentals.
Beginner level
Recommended experience
6 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Understand how deepfakes are created GANs, diffusion models and voice cloning and why each generation method leaves different detectable artifacts.
Detect synthetic audio and cloned voices using spectral analysis, prosodic anomaly detection, and AI-based voice authentication
Build a structured detection workflow that moves from initial suspicion through forensic analysis to a documented, confidence-scored verdict.
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Recently updated!
September 2026
Assessments
6 assignments
Taught in English
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There are 3 modules in this course
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