Generative AI
“Generative AI” is an exploration of the fascinating world of generative artificial intelligence. This module will take participants on a journey through the principles, model architectures, applications, creative use cases, ethical considerations, and best practices in the realm of generative AI.
By the end of this module, participants will have gained a profound understanding of generative AI, enabling them to leverage its capabilities across a spectrum of creative and practical applications while also upholding the highest ethical standards in their work.
In this foundational module, participants will be introduced to the world of generative AI and will gain a basic understanding of the core principles and concepts that underlie generative AI, setting the stage for a deeper exploration of generative model architectures and their applications in subsequent subtopics.
Participants will dive into the diverse landscape of generative model architectures. Participants will gain an understanding of the foundational concepts, including Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and other cutting-edge frameworks that power generative AI.
This part explores the practical applications of generative AI across various domains. Participants will learn how generative AI is used to create images, text, and other forms of content, enabling them to appreciate the versatile applications of generative models in the real world.
This part delves into real-world applications and creative use cases of generative AI. participants will discover how generative AI is transforming industries such as art, entertainment, design, and more. The module will provide insights into innovative and unconventional applications of generative models.
Ethical considerations are paramount when working with generative AI. In this subtopic, participants will explore the ethical implications and best practices associated with generative AI, including issues related to bias, privacy, and accountability. Participants will learn how to navigate these challenges and ensure responsible use of generative models.
