This beginner-friendly tutorial explains how deepfake videos are created using Python and deep learning techniques. The course starts with an introduction to deepfakes, explaining how artificial intelligence can manipulate and synthesize realistic human faces in videos. You will understand the core technologies behind deepfake generation, including autoencoders, convolutional neural networks (CNNs), and generative models such as GANs.

The tutorial walks step-by-step through the workflow required to create a deepfake video. You will learn how to collect and preprocess facial datasets, extract frames from videos, train a face-swapping model, and merge the generated face back into the original video. The course also explains hardware requirements and how GPU acceleration improves training performance.

In addition to video generation, the tutorial highlights ethical considerations and the importance of responsible AI usage. By the end of this course, beginners will understand the technical pipeline behind deepfake creation and gain practical exposure to Python-based deep learning tools used in synthetic media projects. This course is ideal for AI enthusiasts, students, and developers exploring computer vision and generative AI applications.