From Standard Transformers to Modern LLMs: Bringing Dialogue Models, RAG, and Agents to the Classroom

AbstractModern LLM education is increasingly centered on system building: grounding generation with retrieval, enabling tool use, and deploying models under latency and cost constraints.We present an updated release of our open course on Transformer-based LLMs and multimodal models (Nikishina et al, 2024).The update introduces topics which became importance since the first edition, namely session on Retrieval Augmented Generation (RAG), a hands-on session on tool-using agents, an API-based track for applied work with LLM, and practical local inference with vLLM.We also add a dedicated session on multimodal dialog models with a focus on dialog grounding. We enriched the course with a discussion on long-context transformers, focusing on KV-cache efficiency along with the related models and benchmarks.All materials are released online.