Build A Safe & Reliable Agentic App- Zero Install, Zero Cost

The Playbook of Diabetes Companion Using Neo4j AuraDB + Aura Agent

What you’ll learn
Understand the core steps of building an AI-native knowledge graph, from loading source documents to creating structured graph data.
Learn how knowledge graphs can improve RAG and AI applications by making answers more accurate, explainable, and grounded in data.
Learn how Neo4j Aura and Aura Agent can be used to store knowledge graph and support graph-powered AI workflows in the cloud.
Understand the role of guardrails in knowledge-graph-based AI systems and how they help create safer and more reliable solutions.

Requirements
Curiosity about AI, RAG, and knowledge-graph-powered agentic applications is the main prerequisite.
No prior experience with knowledge graphs is required.
Beginners are welcome, although a basic familiarity with AI, data, or databases will be helpful.
You only need a computer and internet connection to follow the course.
A Neo4j Aura account (FREE) is recommended for hands-on exploration and practice.
No download. No installation. No coding.

Description
This course contains the use of artificial intelligence.>>> Build a real AI agent — no coding, no setup, no costWant to build your first agentic AI application but don’t want to deal with complex setup, infrastructure, or coding?In this course, you’ll learn how to build a safe, reliable AI agent grounded in a knowledge graph — using only your browser.No installation. No local environment. No GPU. No cost to start.>>> What you’ll buildBy the end of this course, you will have a working:Neo4j Aura knowledge graphNeo4j Aura AgentGraphRAG-powered AI agentSemantic retrieval (vector + graph queries)Safety guardrails (refusal + escalation)Deterministic reasoning tool (e.g. BGL evaluation)Explainable answers with evidence and citations>>> Why this course is differentMost AI tutorials focus on:prompts onlysimple chatbotsor complex coding setupsThis course shows you how to build production-style AI systems using:Agentic workflows (tool calling + decision logic)Knowledge graphs (not just vector databases)GraphRAG (structured + semantic retrieval)Built-in safety and governance>>> What you’ll learnWhat agentic AI really means (beyond hype)How GraphRAG works in practiceWhy knowledge graphs improve reliabilityHow to use Neo4j Aura (fully cloud-based)How to define agent tools and workflowsHow to implement guardrails and safe responsesHow to combine:vector search (semantic retrieval)graph queries (structured knowledge)>>> Who this course is forAI beginners who want to build something realProduct managers exploring GenAIData / BI professionalsDevelopers curious about GraphRAGAnyone interested in safe and explainable AI systems>>> RequirementsA browser and internet connectionBasic curiosity about AINo coding experience required.

This course is designed for learners who want a practical introduction to AI-native knowledge graphs and their role in modern Agentic AI applications.,It is especially valuable for beginners, developers, architects, data practitioners, and technical product leaders who are exploring RAG, agentic apps, and graph-powered AI workflows.,It is also a strong fit for anyone interested in using knowledge graphs and guardrails to build Agentic AI solutions that are more grounded, reliable, and explainable.

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