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Knowledge Graph Courses

Knowledge Graph courses can help you learn data modeling, semantic web principles, and graph database management. You can build skills in entity recognition, relationship mapping, and data integration techniques. Many courses introduce tools like Neo4j and Apache Jena, that support implementing and querying knowledge graphs, enabling you to visualize complex data relationships and enhance AI applications.

Popular Knowledge Graph Courses and Certifications


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    DeepLearning.AI

    Knowledge Graphs for RAG

    Skills you'll gain: Retrieval-Augmented Generation, LLM Application, LangChain, Large Language Modeling, Embeddings, Prompt Engineering, Query Languages, Vector Databases, Data Storage, Unstructured Data, Graph Theory

    4.8
    Rating, 4.8 out of 5 stars
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    104 reviews

    Intermediate · Project · Less Than 2 Hours

  • Status: Free Trial
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    Packt

    AI Enhancement with Knowledge Graphs - Mastering RAG Systems

    Skills you'll gain: Retrieval-Augmented Generation, Vector Databases, LLM Application, AI Workflows, Embeddings, AI Integrations, Large Language Modeling, Graph Theory, Query Languages, Graphing, Interactive Data Visualization, Data Processing, Development Environment

    4.9
    Rating, 4.9 out of 5 stars
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    10 reviews

    Intermediate · Course · 1 - 3 Months

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    Board Infinity

    RAG from Scratch: Build a Knowledge-Powered Chatbot

    Skills you'll gain: Retrieval-Augmented Generation, Large Language Modeling, Generative AI Agents, AI Workflows, Prompt Engineering, Embeddings, Token Optimization, Context Management, Document Management, Unstructured Data, Database Management Systems, Metadata Management, Model Evaluation, Data Wrangling, Machine Learning

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
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    V

    Vanderbilt University

    Prompt Engineering for ChatGPT

    Skills you'll gain: Prompt Engineering, ChatGPT, Prompt Patterns, LLM Application, AI literacy, AI Enablement, AI powered creativity, Artificial Intelligence, Large Language Modeling, Game Design

    4.8
    Rating, 4.8 out of 5 stars
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    8.1K reviews

    Beginner · Course · 1 - 3 Months

  • Status: New
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    Packt

    Building AI Agents with LLMs, RAG, and Knowledge Graphs

    Skills you'll gain: Prompt Engineering, Retrieval-Augmented Generation, LLM Application, Large Language Modeling, Reinforcement Learning, Artificial Intelligence and Machine Learning (AI/ML), LangChain, AI Orchestration, Natural Language Processing, Generative AI Agents, Agentic Workflows, Multimodal Prompts, AI Integrations, Artificial Intelligence, Agentic systems, Machine Learning Methods, Python Programming, Machine Learning, System Design and Implementation, Data Science

    Intermediate · Specialization · 1 - 3 Months

What brings you to Coursera today?

  • Status: New
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    SkillsBooster Academy

    Context Engineering for Beginners

    Skills you'll gain: Context Engineering, Prompt Engineering, ChatGPT, Token Optimization, Context Management, Retrieval-Augmented Generation, Gemini, AI Workflows, Generative AI, AI Personalization, Artificial Intelligence, Artificial Intelligence and Machine Learning (AI/ML), Microsoft Copilot, Large Language Modeling, Workflow Management, Document Management

    Beginner · Course · 1 - 3 Months

  • P

    Packt

    Neo4j: Cypher, GDS, GraphQL, LLM, Knowledge Graphs for RAG

    Skills you'll gain: Retrieval-Augmented Generation, LLM Application, Database Management Systems, Memory Management, Analysis

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
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    Coursera

    LangGraph Framework

    Skills you'll gain: LangGraph, AI Orchestration, LangChain, AI Workflows, LLM Application, Agentic Workflows, Agentic systems, Generative AI Agents, Model Deployment, Large Language Modeling, Artificial Intelligence, Context Management, Data Persistence, Business Logic

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of California San Diego

    Introduction to Graph Theory

    Skills you'll gain: Graph Theory, Combinatorics, Network Analysis, Algorithms, Mathematical Modeling, Traffic Flow Optimization, Program Development

    4.5
    Rating, 4.5 out of 5 stars
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    1.1K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
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    U

    University of California San Diego

    Big Data

    Skills you'll gain: Apache Spark, Model Evaluation, Apache Hadoop, Data Integration, Exploratory Data Analysis, Big Data, Classification Algorithms, Graph Theory, Data Pipelines, Network Model, Model Training, Database Design, Data Modeling, Regression Analysis, Data Mining, Data Management, Data Infrastructure, Data Presentation, Data Processing, MongoDB

    4.6
    Rating, 4.6 out of 5 stars
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    14K reviews

    Beginner · Specialization · 3 - 6 Months

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    Coursera

    Content & Knowledge Management

    Skills you'll gain: Technical Documentation, Document Management, Taking Meeting Minutes, Content Management, Document Control, Project Documentation, Knowledge Transfer, Technical Writing, Content Management Systems, Content Development and Management, Information Architecture, Technical Communication, Content Optimization, Content Strategy, Collaborative Software, Content Creation, Usability, Quality Assurance

    Intermediate · Course · 3 - 6 Months

  • Status: New
    New
    Status: Free Trial
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    Packt

    Building Retrieval-Augmented Systems & Knowledge Graphs

    Skills you'll gain: Retrieval-Augmented Generation, LLM Application, LangChain, Artificial Intelligence and Machine Learning (AI/ML), Agentic Workflows, Generative AI Agents, AI Integrations, Artificial Intelligence, Large Language Modeling, Taxonomy, Agentic systems, Scalability, Python Programming, System Design and Implementation, Machine Learning, Graph Theory

    Intermediate · Course · 1 - 4 Weeks

What brings you to Coursera today?

1234…659

In summary, here are 10 of our most popular knowledge graph courses

  • Knowledge Graphs for RAG: DeepLearning.AI
  • AI Enhancement with Knowledge Graphs - Mastering RAG Systems: Packt
  • RAG from Scratch: Build a Knowledge-Powered Chatbot: Board Infinity
  • Prompt Engineering for ChatGPT: Vanderbilt University
  • Building AI Agents with LLMs, RAG, and Knowledge Graphs: Packt
  • Context Engineering for Beginners: SkillsBooster Academy
  • Neo4j: Cypher, GDS, GraphQL, LLM, Knowledge Graphs for RAG: Packt
  • LangGraph Framework: Coursera
  • Introduction to Graph Theory: University of California San Diego
  • Big Data: University of California San Diego

Frequently Asked Questions about Knowledge Graph

Careers in the field of knowledge graphs are diverse and growing. Potential job titles include Data Scientist, Knowledge Engineer, Semantic Web Developer, and Business Intelligence Analyst. These roles often involve working with data modeling, machine learning, and natural language processing to create and maintain knowledge graphs that support various business functions.‎

Some of the best online courses for learning about knowledge graphs include specialized programs that focus on data science and AI applications. For instance, the AI for Knowledge Workers course provides insights into how AI can be integrated with knowledge management practices. Exploring various courses can help you find the right fit for your learning goals.‎

Typical topics covered in knowledge graph courses include graph theory, data integration, semantic web technologies, and the practical applications of knowledge graphs in various industries. You may also learn about tools and frameworks used to create and manage knowledge graphs, as well as best practices for data governance and quality."‎

For training and upskilling employees in knowledge graph technologies, courses like the Splunk Knowledge Manager Specialization can be particularly beneficial. These programs are designed to enhance skills relevant to knowledge management and data analytics, making them suitable for workforce development.‎

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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