Published 1/2026
Created by Modern Professional Academy
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 17 Lectures ( 1h 12m ) | Size: 737 MB
Master RAG pipelines, Vector Stores, and tool-calling to build autonomous Java AI agents for complex business tasks.
What you’ll learn
✓ Architect Retrieval-Augmented Generation (RAG) pipelines to ground AI responses in private enterprise data.
✓ Implement high-performance semantic search using vector embeddings and vector databases.
✓ Enable autonomous function-calling, allowing LLMs to execute Java methods for real-world business actions.
✓ Build complex agentic loops using reasoning models that perceive, plan, act, and reflect.
Requirements
● Completion of “Java AI Foundations” or a solid grasp of LangChain4j basics.
● Basic understanding of databases (SQL/NoSQL) and REST API principles.
Description
This course contains the use of artificial intelligence.
In the professional landscape of 2025, simply calling an LLM API is no longer enough. To deliver true business value, AI must be grounded in reality and capable of taking action. This course, “Enterprise RAG & AI Agents: Advanced Java LLM Workflows,” is a strategic deep dive into building production-ready AI systems that integrate seamlessly with your private data and business logic.
We begin by architecting the modern Retrieval-Augmented Generation (RAG) pipeline. You will master the complex workflow of data ingestion: from loading diverse document sources (PDF, Word, Text) to parsing and strategic chunking. We explore the mathematical foundations of semantic similarity and vector embeddings, teaching you how to store and retrieve high-quality context from professional vector databases like Milvus, Pinecone, or Qdrant. This ensures your Java applications provide accurate, trustworthy responses while eliminating the risk of AI hallucinations.
Beyond data retrieval, we move into the era of Agentic AI. You will learn to bridge the gap between AI reasoning and actual execution through Function-Calling. By using LangChain4j’s high-level tool primitives and the @Tool annotation, you will empower Large Language Models to call your Java methods autonomously to solve complex, multi-step tasks. We cover advanced agent architectures—including Sequential, Parallel, and Loop workflows—giving you the blueprint to build systems that don’t just “talk,” but “act” with professional precision. Whether you are a Senior Engineer or a Software Architect, this course provides the technical expertise required to lead AI transformation in an enterprise environment while maintaining strict security and reliability standards.
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