Oracle Cloud Infrastructure AI Foundations Associate: Transformers and Their Architecture

Recurrent neural networks (RNNs) were once the standard for sequence tasks like language, but struggled with long-range dependencies and slow sequential training. Attention mechanisms addressed these challenges, and the transformer architecture revolutionized deep learning.In this course, discover the challenges faced by RNNs, including vanishing and exploding gradients that reduce effectiveness. Next, explore how attention mechanisms, introduced in sequence-to-sequence models with LSTMs and GRUs, inspired the development of transformers. Finally, learn about the transformer architecture, multi-head self-attention, and the role of Add & Norm layers.This course is part of a series that prepares learners for the Oracle Cloud Infrastructure 2025 AI Foundations Associate (1Z0-1122-25) certification.