What does the Knowledge Graphs course cover?
Knowledge Graphs is covered here in 6 modules: Introduction to Knowledge Graphs, Entity Disambiguation, Relationship Extraction and 3 more. The outline lists 18 specific topics, opening with defining Knowledge Graphs : Understand the concept of knowledge graphs, and how they're used in real-world applications.
How do you approach Knowledge Graphs step by step?
The work is sequenced in 6 stages. It starts with Introduction to Knowledge Graphs, moves through Entity Disambiguation and Relationship Extraction, and ends at Advanced Topics in Knowledge Graphs. Each stage carries its own topic list, so the sequence is followed rather than summarised.
What is in Module 1 of the Knowledge Graphs course?
Module 1 is Introduction to Knowledge Graphs. It works through defining Knowledge Graphs : Understand the concept of knowledge graphs, and how they're used in real-world applications., history and Evolution of Knowledge Graphs : Learn about the history and evolution of knowledge graphs, and how they've become a crucial tool in data analysis and decision-making.
How is the Knowledge Graphs course delivered?
The Knowledge Graphs course is fully self-paced with immediate online access after enrolment. Access does not expire and future updates are included at no cost. It can be taken on any device, and a certificate of completion is issued by The Art of Service when you finish.
How much does the Knowledge Graphs course cost?
The Knowledge Graphs course is $199 as a one time payment. There is no subscription, no per seat licence and no hidden fee. Enrolment carries a 30 day satisfied or refunded guarantee, so it can be assessed in full before you commit.
Closely related courses: Entity Disambiguation and Semantic Knowledge Graphing Kit, Relationship Extraction Toolkit, Word Sense Disambiguation and Semantic Knowledge Graphing.
More answers: what you get with every course, refund policy, all help answers.
Mastering Knowledge Graphs: Unlocking Entity Disambiguation and Relationship Extraction
Course Overview
This comprehensive course is designed to help you master the concepts of knowledge graphs, entity disambiguation, and relationship extraction. With a focus on practical, real-world applications, you'll gain hands-on experience in creating and utilizing knowledge graphs to unlock new insights and improve decision-making.Course Features
- Interactive and Engaging: Learn through a combination of video lessons, quizzes, and hands-on projects.
- Comprehensive and Personalized: Get access to a tailored learning experience, with content that's up-to-date and relevant to your needs.
- Practical and Real-world Applications: Apply your knowledge to real-world scenarios and projects, with guidance from expert instructors.
- High-quality Content and Expert Instructors: Learn from the best in the industry, with high-quality content that's designed to engage and inform.
- Certification and Flexible Learning: Receive a certificate upon completion, and enjoy flexible learning options that fit your schedule and lifestyle.
- User-friendly and Mobile-accessible: Access your course materials from anywhere, at any time, with our user-friendly and mobile-accessible platform.
- Community-driven and Actionable Insights: Join a community of like-minded learners, and gain actionable insights that you can apply to your work or personal projects.
- Hands-on Projects and Bite-sized Lessons: Learn through hands-on projects and bite-sized lessons, with lifetime access to course materials.
- Gamification and Progress Tracking: Stay motivated with gamification and progress tracking features, designed to help you stay on track and achieve your goals.
Course Outline
Module 1: Introduction to Knowledge Graphs
- Defining Knowledge Graphs: Understand the concept of knowledge graphs, and how they're used in real-world applications.
- History and Evolution of Knowledge Graphs: Learn about the history and evolution of knowledge graphs, and how they've become a crucial tool in data analysis and decision-making.
- Key Components of Knowledge Graphs: Identify the key components of knowledge graphs, including entities, relationships, and ontologies.
Module 2: Entity Disambiguation
- Introduction to Entity Disambiguation: Understand the concept of entity disambiguation, and its importance in knowledge graph construction.
- Types of Entity Disambiguation: Learn about the different types of entity disambiguation, including name disambiguation and entity resolution.
- Techniques for Entity Disambiguation: Explore the various techniques used for entity disambiguation, including machine learning and natural language processing.
Module 3: Relationship Extraction
- Introduction to Relationship Extraction: Understand the concept of relationship extraction, and its importance in knowledge graph construction.
- Types of Relationships: Learn about the different types of relationships, including semantic relationships and ontological relationships.
- Techniques for Relationship Extraction: Explore the various techniques used for relationship extraction, including machine learning and natural language processing.
Module 4: Knowledge Graph Construction
- Introduction to Knowledge Graph Construction: Understand the process of constructing a knowledge graph, and the importance of entity disambiguation and relationship extraction.
- Knowledge Graph Construction Techniques: Learn about the various techniques used for knowledge graph construction, including data integration and data fusion.
- Knowledge Graph Evaluation: Understand how to evaluate the quality and accuracy of a knowledge graph.
Module 5: Knowledge Graph Applications
- Introduction to Knowledge Graph Applications: Understand the various applications of knowledge graphs, including question answering and decision-making.
- Knowledge Graph-based Question Answering: Learn about the use of knowledge graphs for question answering, and the techniques used for query processing and answer generation.
- Knowledge Graph-based Decision-making: Understand how knowledge graphs can be used for decision-making, and the techniques used for reasoning and inference.
Module 6: Advanced Topics in Knowledge Graphs
- Introduction to Advanced Topics in Knowledge Graphs: Understand the advanced topics in knowledge graphs, including knowledge graph embedding and knowledge graph-based recommendation systems.
- Knowledge Graph Embedding: Learn about the techniques used for knowledge graph embedding, including TransE and ConvE.
- Knowledge Graph-based Recommendation Systems: Understand how knowledge graphs can be used for recommendation systems, and the techniques used for personalized recommendation.