This 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 GraphRAG
Course 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 cases
Who 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 architectures
Why Enroll
Graph 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.
