This course provides a comprehensive exploration of Large Language Models (LLMs), focusing on their foundational technologies, applications, and advanced techniques in deploying, fine-tuning, and evaluating them. Students will gain hands-on experience with transformer architectures, semantic search, retrieval-augmented generation (RAG), and AI agents. The course will also delve into cutting-edge methods for deploying LLMs locally, as well as leveraging Knowledge Graphs to enhance LLM-based systems for structured reasoning and improved retrieval. By the end of the course, students will be able to design, implement, and evaluate complex LLM applications in real-world settings, from personalized chatbots to AI agents working in collaborative environments. The course will prepare students to tackle cutting-edge research and practical challenges in Natural Language Processing (NLP) and AI-driven systems.