Knowledge Graph & AI Course in Pune

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25 hrs of E-Learning Videos
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Knowledge Graph & AI Course Overview

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Upcoming Knowledge Graph & AI Batches

21-09-2026
Mon-FriWeekdays Regular
08:00 AM & 10:00 AM Batches(Class 1Hr - 2Hrs) / Per Session
23-09-2026
Mon - FriWeekdays Regular
06:00 PM & 08:00 PM Batches(Class 1Hr - 2Hrs) / Per Session
25-09-2026
Sat-SunWeekend Batch
09:00 AM & 01:00 PM Batches(Class 2Hr - 4Hrs) / Per Session
Can't find a batch? Pick your own schedule

Knowledge Graph & AI Course Syllabus

This practical Knowledge Graph & AI Training program covers knowledge representation, graph databases, semantic relationships, and AI-powered knowledge discovery. Participants will learn to design knowledge graphs, query graph data, and integrate graphs with LLMs, RAG, and Generative AI applications.

  • What is a Knowledge Graph?
  • Knowledge Graph vs. traditional databases
  • Nodes, edges, properties, and relationships
  • Graph-based knowledge representation
  • Knowledge Graph architecture
  • Industry use cases
  • Entity and relationship modeling
  • Ontologies and schemas
  • Classes, properties, and attributes
  • Taxonomies and hierarchies
  • Graph modeling best practices
  • Designing domain-specific Knowledge Graphs
  • Introduction to Graph Databases
  • Property graphs vs. RDF graphs
  • Neo4j fundamentals
  • Nodes, relationships, and properties
  • Graph database architecture
  • CRUD operations
  • Introduction to Cypher
  • Writing graph queries
  • Pattern matching
  • Filtering and aggregation
  • Traversals and path queries
  • Advanced Cypher queries
  • RDF fundamentals
  • Triples and semantic relationships
  • SPARQL query language
  • OWL and ontology concepts
  • Knowledge representation standards
  • Semantic Web fundamentals
  • Data extraction from structured and unstructured sources
  • Entity extraction
  • Entity resolution and deduplication
  • Relationship extraction
  • Data integration
  • Knowledge Graph construction pipelines
  • LLM fundamentals for Knowledge Graph applications
  • LLM-based entity and relationship extraction
  • Graph-based prompting
  • Connecting LLMs with graph databases
  • Knowledge Graph-enhanced question answering
  • Graph-based AI applications
  • Graph RAG architecture
  • Vector RAG vs. Graph RAG
  • Combining vector search and graph traversal
  • Context retrieval from Knowledge Graphs
  • Multi-hop question answering
  • Building Graph RAG pipelines
  • Graph embeddings
  • Graph Neural Networks fundamentals
  • Link prediction
  • Entity similarity
  • Community detection
  • Graph analytics and recommendation systems
  • Agentic AI with Knowledge Graphs
  • End-to-end Knowledge Graph architecture
  • Graph data pipelines
  • Performance optimization
  • Security and access control
  • Monitoring and maintenance
  • Graph RAG deployment
  • Enterprise AI use cases and best practices
Need customized curriculum?
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Hands On Knowledge Graph & AI Projects

Enroll in our Knowledge Graph & AI classes, where our course focuses on providing high-quality training with a strong foundation in core concepts and a practical approach. Through exposure to current industry use cases and scenarios, participants will enhance their skills and gain the ability to execute real-time projects using best practice

Enterprise Knowledge Graph

  • Design a domain-specific graph schema
  • Extract entities and relationships from documents
  • Store and organize information in Neo4j
  • Create Cypher queries for knowledge discovery
  • Build a graph visualization and exploration interface

Knowledge Graph-Based AI Assistant

  • Build a Knowledge Graph from enterprise documents
  • Extract entities and relationships using LLMs
  • Connect the graph database with an LLM
  • Implement natural-language question answering
  • Generate answers using graph-based context

Graph RAG & Agentic AI Platform

  • Combine vector search with Knowledge Graph retrieval
  • Implement multi-hop and relationship-based retrieval
  • Build Graph RAG pipelines
  • Integrate AI agents with graph tools
  • Evaluate, optimize, and deploy the AI platform

For Corporates

Educate your workforce with new skills to improve their performance and productivity.

Corporate Training
"Leading Companies We've Served"
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Our Instructor
Name
Mr. John
Experience
12+ Years
Specialized in
Specialized in Knowledge Graphs, Neo4j, Graph Databases, RDF, SPARQL, Graph RAG, Generative AI, LLMs, Graph AI, and Agentic AI.
More Details
The instructor is an experienced AI professional specializing in Knowledge Graphs, Graph Databases, Generative AI, and intelligent information systems. The training focuses on practical implementation using graph modeling, Neo4j, Cypher, semantic technologies, LLMs, and Graph RAG architectures. Participants receive hands-on guidance through labs, real-world scenarios, troubleshooting exercises, and end-to-end AI projects.

Knowledge Graph & AI Training Objectives

Our Best Knowledge Graph & AI Training aims to empower participants with comprehensive skills and practical knowledge in this field. Objectives include mastering core concepts, applying skills through real-world projects, critical thinking, and tackling professional challenges. This enhances career development and contributes to industry advancement.

A Knowledge Graph stores explicit relationships between entities, while a vector database stores numerical representations of data for similarity search. Vector databases are useful for semantic retrieval, whereas Knowledge Graphs are particularly useful for relationship and multi-hop queries.

Graph RAG combines Retrieval-Augmented Generation with Knowledge Graph technology. Instead of retrieving only similar text chunks, the system can retrieve entities, relationships, and connected information from a graph.

You will learn graph modeling, Neo4j, Cypher, RDF, SPARQL, ontologies, graph analytics, and Knowledge Graph construction. The course also covers LLM integration, Graph RAG, graph embeddings, and AI agents. Hands-on projects provide practical experience in building complete graph-based AI applications.

Knowledge Graphs can provide structured and connected information that an AI system can retrieve as context. They can help represent relationships between entities and support complex multi-step information retrieval. When combined with LLMs and RAG, they can be used to build more context-aware enterprise AI applications.

Neo4j is a graph database platform designed to store and query highly connected data. It uses nodes, relationships, properties, and the Cypher query language to work with graph data. It is commonly used for knowledge management, recommendations, fraud analysis, network analysis, and graph-based AI applications.

You will build an Enterprise Knowledge Graph, a Knowledge Graph-based AI Assistant, and a Graph RAG & Agentic AI Platform. The projects cover graph modeling, entity extraction, LLM integration, graph retrieval, and multi-hop question answering.

Job Assistance Program

Our Job Assistance Programme offers you special guidance through the course curriculum and helps in your interview preparation.

Specialised Curriculum
Get on-field knowledge and skills from our expert instructors.
Assessment
Upgrade your on-field skills with our assessments and track your progress in real time.
Hands-on Project
Our hands-on project help you gain experience in real-time working.
Certification Guidance
A global certificate always helps you stand out from the crowd.
Portfolio Building
Experts guide you to maximise your profile with current industry trends that employers expect.
Placment Cell
We promote your abilities and showcase your portfolio to employers.

Knowledge Graph & AI Career Opportunity

Knowledge Graph & AI is the most common programming language, and it works on all computers and mobile devices without needing to be upgraded. It is one of the highest-paying careers in the software development industry, and those with the Knowledge Graph & AI certification can earn an average of  8 LPA per year.

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Placement Guidance & Interview Preparation

Infibee’s placement guidance navigates you to your desired role in top organisations, ensuring you stand out and excel in every opportunity.

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Knowledge Graph & AI Training FAQ's

Infibee Knowledge Graph & AI Training offers wide range of services that suits for both fresher and experienced persons via both offline and online at your suitable time slots.

You need not worry about having missed a class. Our dedicated course coordinator will help them with anything and everything related to administration. The coordinator will arrange a session for the student with trainers in place of the missed one.

Yes, of course. You can contact our team at Infibee Technologies, and we will schedule a free demo or a conference call with our mentor for you.

We provide classroom, online, and self-based study material and recorded sessions for students based on their individual preferences.

Yes, all our trainers are industry professionals with extensive experience in their respective domains. They bring hands-on practical and real-world knowledge to the training sessions.

Yes, participants typically receive access to course materials, including recorded sessions, assignments, and additional resources, even after the training concludes.

We provide placement assistance to students, including resume building, interview preparation, and job placement support for a wide range of software courses.

Yes, we offer customisation of the syllabus for both individual candidates and corporate also.

Yes, we offer corporate training solutions. Companies can contact us for customised programmes tailored to their team’s needs.

Participants need a stable internet connection and a device (computer, laptop, or tablet) with the necessary software installed. Detailed technical requirements are provided upon enrollment.

In most cases, such requests can be accommodated. Participants can reach out to our support team to discuss their preferences and explore available options.

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