Transformer Architectures and Multimodal Models

This course explores the foundations and evolution of modern transformer architectures, taking you from early sequence models to advanced multimodal systems that power today’s AI breakthroughs. Combining strong conceptual depth with practical demonstrations, this course provides a structured journey through attention mechanisms, transformer design, efficiency innovations, and large-scale training strategies. You will begin by understanding Recurrent Neural Networks (RNNs), LSTMs, and GRUs—examining their strengths and limitations in modeling sequential data. From there, you’ll transition into…