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Beyond The Basics: Building Generative Ai Java Applications Using Langchain4j
Released 1/2026
With Frank Greco
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 3h 22m | Size: 342 MB [/center]
Learn how to build generative AI applications using LangChain4j, focusing on AiServices, streaming, embeddings, data ingestion, similarity, RAG, invoking Java methods, and agents.
Course details
In this intensive, hands-on course, AI expert and senior consultant Frank Greco proves that Java is a first-class citizen in the world of generative AI. Learn how to master LangChain4j, the de facto Java library for working with LLMs and generative AI tools. Using a large repo of example code, Frank demonstrates how to write Java code to build intelligent, context-rich Java applications that combine effective prompts with the power of embeddings, vector stores, ingestion architecture, and retrieval-augmented generation (RAG).Additional topics covered include advanced prompting with templates, streaming LLM responses in real time, understanding embeddings and similarity, chunking strategies, invoking Java methods, agents, and more.
Skills covered
Retrieval-Augmented Generation (RAG), Artificial Intelligence (AI), Java
Beyond The Basics: Building Generative Ai Java Applications Using Langchain4j
Released 1/2026
With Frank Greco
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 3h 22m | Size: 342 MB [/center]
Learn how to build generative AI applications using LangChain4j, focusing on AiServices, streaming, embeddings, data ingestion, similarity, RAG, invoking Java methods, and agents.
Course details
In this intensive, hands-on course, AI expert and senior consultant Frank Greco proves that Java is a first-class citizen in the world of generative AI. Learn how to master LangChain4j, the de facto Java library for working with LLMs and generative AI tools. Using a large repo of example code, Frank demonstrates how to write Java code to build intelligent, context-rich Java applications that combine effective prompts with the power of embeddings, vector stores, ingestion architecture, and retrieval-augmented generation (RAG).Additional topics covered include advanced prompting with templates, streaming LLM responses in real time, understanding embeddings and similarity, chunking strategies, invoking Java methods, agents, and more.
Skills covered
Retrieval-Augmented Generation (RAG), Artificial Intelligence (AI), Java
Cytat:https://rapidgator.net/file/28fdbcfaaa4b...j.rar.html
https://nitroflare.com/view/D971506FF4BF...hain4j.rar