The Agentic RAG & Knowledge Engineering course is designed to equip learners with advanced skills to build next-generation AI systems that reason, plan, retrieve, and act autonomously. Unlike traditional Retrieval-Augmented Generation, Agentic RAG introduces intelligent agents capable of task decomposition, tool usage, memory management, and iterative decision-making over structured and unstructured knowledge. This course covers the full lifecycle of knowledge engineering, including data ingestion, semantic chunking, embeddings, vector databases, knowledge graphs, hybrid retrieval, and agent orchestration using modern LLM frameworks. Learners will explore multi-agent architectures, long-term memory, reasoning loops, and evaluation strategies to ensure accuracy, reliability, and scalability in enterprise-grade AI solutions. Through real-world use cases, hands-on projects, and system-level design patterns, participants gain practical expertise to build AI copilots, enterprise search engines, autonomous analysts, and domain-specific assistants. Delivered through Jast Tech, this course bridges theory and implementation, enabling professionals to confidently deploy intelligent, trustworthy, and production-ready Agentic RAG systems across industries.