In this section of our AI Engineering bootcamp, you'll gain a comprehensive understanding of generative AI models, explore their evolution and real-world applications, and develop the technical skills to build and deploy these models effectively.

We'll cover the statistical foundations of Generative AI, delve into key architectures like GANs, VAEs, and Transformers, and examine cutting-edge tools and techniques like diffusion models and RAGs.

By the end, you'll have the knowledge and practical experience necessary to contribute to this rapidly evolving field, from understanding data distributions to implementing and optimizing your own generative AI solutions.

In this section of our AI Engineering bootcamp, you will master Generative Adversarial Networks (GANs), beginning with foundational concepts like the Generator and Discriminator architecture, loss functions, and training dynamics.

We'll explore different GAN architectures, including DCGANs, CycleGANs, and StyleGANs, and delve into advanced training techniques like Wasserstein GANs and Spectral Normalization.

This comprehensive coverage, including practical applications in image generation, style transfer, and data augmentation, equips you to build and deploy cutting-edge GAN models confidently.

You'll solidify your understanding through a hands-on project, generating realistic synthetic data and demonstrating your GAN mastery.

VAEs enable powerful generative AI and insightful representation learning. This module unlocks their potential by explaining VAE principles and their importance in AI.

Explore real-world applications to learn how VAEs innovate anomaly detection and image generation. The module then covers VAE architecture, giving you the foundation to build and implement these models.

Learning the fundamental maths will help you understand VAEs. Finally, you'll learn practical training techniques and complete a hands-on project to demonstrate your VAE skills.

In this module, you'll master Transformers, a driving force behind modern AI advancements, and leverage them to build cutting-edge models.

This comprehensive training takes you from foundational concepts to advanced techniques, covering the history and architecture of Transformers, along with crucial concepts like attention mechanisms and multi-head attention.

You'll build your own language model, gaining hands-on experience and unlocking the potential of this revolutionary technology.

Large language models are at the core of Generative AI—the driving force of modern AI innovation. By completing this module, you will gain the expertise needed to confidently build and implement LLM-based solutions, whether at your own startup, another fast-paced venture, or a large enterprise.

We begin with the essential foundations of large language models and progress into advanced topics like attention mechanisms and transformers. You’ll dive deep into high-impact models such as Mixtral, Falcon, and various GPTs, dissecting their architecture, operations, strengths, and limitations.

Finally, you’ll construct your own large language models from the ground up, mastering data collection, fine-tuning, and optimization for practical, real-world application.

Through hands-on case studies focusing on pre-training and fine-tuning, you'll gain practical experience, preparing you to develop your own LLM applications and join the ranks of cutting-edge organizations pushing the boundaries of AI.

Unleash the transformative potential of LLMs and shape the future of language-based AI.