This course introduces generative AI by combining theory with practical examples. Student will learn basic deep learning concepts like neural networks, back-propagation, and optimization. The course then covers modern AI models such as GANs, VAEs, and transformer-based systems that shows how they work in imaging, text, audio, and cross-modal projects. The course also addresses ethical issues, including algorithmic bias, privacy concerns, and proper AI practices. Through hands-on coding labs, project-based tasks, and group discussions, students will apply the theory to real-world problems. By the end of the course, students will understand how generative AI works and be ready to apply in the industrial applications.
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