Udemy – Master Advanced Agentic AI + LangGraph + RAG+Memory -JAN’26 2025-11

Description

Master Advanced Agentic AI + LangGraph + RAG+Memory -JAN’26. Updated in January 2026 with the latest versions of Langchain and LangGraph, this course is recognized as the only specialized reference on the Udemy platform that turns simple intelligent agents into enterprise-level systems. Today, the demand for skills such as working with Multi-Agent systems and implementing RAG (Recovery-Enhanced Generation) is growing rapidly, and large technology companies are looking for specialists with these capabilities for senior AI engineering and quality assurance (QA) roles. In this educational path, concepts go beyond the basic level and focus on complex architectures so that intelligent agents not only execute commands, but also have memory and learn from their previous interactions. One of the distinguishing features of this course is its evolutionary approach, in which code written in regular Python is gradually migrated to powerful frameworks such as LangGraph. This helps students clearly understand the difference between performance and scalability. Also, topics related to cost optimization and context management are fully covered so that the systems built are operational in real environments. With this training, engineers can build systems that use company-specific data using Vector Databases instead of using general knowledge from the Internet. The course includes several practical projects that integrate directly with real-world tools like Jira and Slack, preparing the student for high-level job interviews.

What you will learn

• Mastering modern frameworks: Specialized learning of Langchain and LangGraph for building production-level intelligent agents.
• RAG implementation: Using vector databases like ChromaDB to retrieve proprietary company knowledge and avoid generic responses.
• Multi-Agent Systems: Design and implement supervisory patterns in which multiple expert agents collaborate to solve complex tasks.
• Memory and context management: Adding short-term and long-term memory to intelligent agents to remember behavioral patterns.
• Workflow Automation: Integrate AI with real-world tools like TestRail, Jira, and Slack to automate processes.
• Human-in-the-Loop workflow: Implement human-in-the-loop nodes to monitor sensitive system actions.
• Optimization and Scalability: Learn production-ready patterns and best practices to reduce costs and increase system speed.

This course is suitable for people who:

• Quality Assurance (QA) Engineers: Individuals who want to advance their skills to the level of production-ready intelligent systems.
• Senior Test Automation Engineers: Those looking to integrate AI into organizational test workflows.
• Python Developers: Programmers who are building applications powered by Large Language Models (LLM).
• Tech Leads: People who are responsible for evaluating and selecting Langchain and LangGraph frameworks for their team.
• Artificial Intelligence Engineers: Specialists who focus on operating systems for software quality assurance.

Course details: Master Advanced Agentic AI + LangGraph + RAG+Memory -JAN’26

• Publisher:  Udemy
• Instructor:  Vignesh S
• Training level: Beginner to advanced
• Training duration: 8 hours and 45 minutes
• Number of lessons: 82

Course syllabus as of 1/2026

Prerequisites for the Master Advanced Agentic AI + LangGraph + RAG+Memory course -JAN’26

Course images

Sample course video