This Transformers course is designed to help you understand the core concepts of modern deep learning architectures used in NLP and AI applications. It covers fundamental topics like Word2Vec, Attention mechanisms, and Multi-Head Attention, along with practical LAB sessions to enhance your hands-on experience.

You’ll also learn about Masked Multi-Head Attention, Inter Attention, and Positional Encodings, which play a crucial role in improving model performance. The series further explores the Transformer Encoder-Decoder framework, breaking down its working principles and applications in real-world AI systems.

Whether you’re a data scientist, AI enthusiast, or an aspiring NLP expert, this playlist will guide you through the essential knowledge required to build and understand Transformer models. Stay tuned for interactive sessions, structured explanations, and practical demonstrations to help you master Transformers effectively.