Learning Path

Transformer Architecture Fundamentals → Hands-on Project: Optimizing a BERT Model

This advanced learning path equips NLP engineers with the knowledge and skills to compress and optimize large language models for efficient deployment. It covers core compression techniques—pruning, quantization, and distillation—along with efficient architectures and practical inference optimization for on-device and server-side production environments. The path emphasizes hands-on application and critical evaluation of trade-offs.