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Graph Databases: Neo4j, Rdf, Knowledge Graphs & Graphrag
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charlie
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3 477 posts 3 477 threads Dołączył: Nov 2025
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[center][Obrazek: 6115309091e5080c1740c42b05cecbb8.jpg]
Graph Databases: Neo4j, Rdf, Knowledge Graphs & Graphrag
Published 12/2025
Created by Aritra Basak
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 69 Lectures ( 10h 18m ) | Size: 5.55 GB [/center]
Learn Neo4j with Python and Cypher, GraphQL, Knowledge Graphs, RDF, Graph Algorithms and GraphRAG from Scratch
What you'll learn
You will understand the fundamentals of graph databases and how they differ from traditional databases.
You will learn how to use Neo4j, write Cypher queries, and work with graph data using Python.
You will apply graph algorithms like BFS, DFS, and shortest path to solve real-world problems.
You will build knowledge graphs and understand RDF, SPARQL, GraphQL, and GraphRAG concepts.
Requirements
No prior experience with graph databases is required. This course is designed for complete beginners.
You only need a laptop or desktop computer with a stable internet connection.
Description
Welcome to the Complete Graph Databases CourseThis course is a complete, beginner to advanced guide to graph databases. You will learn how modern systems use graphs to model complex relationships and how to build real world applications using Neo4j, Python, RDF, knowledge graphs, and GraphRAG.What You Will Learn• Understand what graph databases are and how they differ from relational databases• Learn graph theory concepts like nodes, relationships, directed graphs, cyclic graphs, and DAGs• Work confidently with Neo4j and write efficient Cypher queries• Use Python to create pipelines and automate graph data workflows• Apply graph algorithms such as BFS, DFS, shortest path, and Dijkstra's algorithm• Learn RDF, SPARQL, GraphQL, knowledge graphs, and GraphRAGCourse Highlights• Beginner friendly explanations with visual learning• Hands on Neo4j and Python integration• Real world projects including routing systems and fraud detection• Coverage of both property graphs and semantic graphs• Modern AI concepts like knowledge graphs and GraphRAG• Practical focus with code and real use casesWho This Course Is For• Beginners who want to learn graph databases from scratch• Software developers and backend engineers• Data engineers and data scientists• AI and machine learning engineers interested in knowledge graphs• Anyone curious about graph based systems and modern data architecturesWhy EnrollGraph databases are increasingly used in areas like recommendation systems, fraud detection, social networks, and AI powered applications. This course gives you a structured learning path with practical skills that you can directly apply to real world problems, projects, and jobs.By the end of this course, you will have a strong understanding of graph databases and the confidence to work with Neo4j, Python, graph algorithms, RDF, knowledge graphs, and GraphRAG in real world applications.Enroll now and start mastering graph databases step by step.
Who this course is for
This course is for beginners who want to learn graph databases from scratch and build a strong foundation.
It is ideal for software developers, data engineers, and backend engineers who want to work with Neo4j and graph-based systems.
This course is also suitable for data scientists, AI engineers, and machine learning practitioners who want to understand knowledge graphs and GraphRAG.
Anyone interested in modern data systems, graph algorithms, and real-world graph applications will benefit from this course.


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