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Supercharge AI with Knowledge Graphs: RAG System Mastery - BaDshaH - 08-04-2024
![[Image: f563f8c8472686be14e0418a1219724b.jpg]](https://i123.fastpic.org/big/2024/0804/4b/f563f8c8472686be14e0418a1219724b.jpg)
Published 8/2024
Created by Paulo Dichone | Software Engineer, AWS Cloud Practitioner & Instructor
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 35 Lectures ( 2h 35m ) | Size: 1.85 GB
Enhance Large Language Models Using Structured Context and Retrieval-Augmented Generation - Neo4j, LangChain, Cypher
What you'll learn:
Understand Knowledge Graph Fundamentals
Implement Knowledge Graphs with Neo4j
Enhance the accuracy of RAG application with Knowledge Graphs
Create and Utilize Full-Text Search Indexes
Requirements:
Basic Understanding of Databases
Fundamental Programming Skills
Basic Understanding of AI, LLM
Description:
Are you ready to take your AI skills to the next level? Welcome to "Supercharge AI with Knowledge Graphs: RAG System Mastery", the ultimate course designed to unlock the full potential of Large Language Models (LLMs) using cutting-edge techniques in Knowledge Graphs and Retrieval-Augmented Generation (RAG) systems.What You Will Learn:Foundations of Knowledge Graphs: Understand the core concepts, structure, and components of knowledge graphs and how they represent complex data relationships.Introduction to RAG Systems: Learn what Retrieval-Augmented Generation is and why it's a game-changer for improving the performance of AI models.Integrating Knowledge Graphs with LLMs: Discover how to combine knowledge graphs with large language models to provide structured, relevant context and boost AI capabilities.Building and Querying Knowledge Graphs: Gain hands-on experience in creating and querying knowledge graphs using popular tools and technologies.Optimizing AI with Structured Data: Explore strategies for enhancing AI performance by leveraging the structured data provided by knowledge graphs.Real-World Applications: Dive into practical examples and case studies showcasing the use of knowledge graphs in various industries such as healthcare, finance, and more.Advanced Techniques: Learn advanced methods for fine-tuning LLMs and integrating them with RAG systems for superior results.Course Highlights:Hands-On Projects: Work on real-world projects to build and optimize knowledge graphs and integrate them with AI models.Expert Instructors: Learn from industry experts with years of experience in AI, knowledge graphs, and RAG systems.Interactive Content: Engage with interactive lectures, quizzes, and assignments to reinforce your learning.Community Support: Join a community of learners and professionals to share insights, ask questions, and collaborate on projects.Who This Course Is For:AI and Machine Learning Enthusiasts: Individuals looking to deepen their understanding of AI and enhance the performance of their models.Data Scientists and Engineers: Professionals seeking to leverage knowledge graphs and RAG systems for more effective data management and analysis.Developers and Programmers: Technologists interested in integrating cutting-edge AI techniques into their applications.Business Analysts and Managers: Decision-makers aiming to harness the power of AI for strategic insights and competitive advantage.Why Enroll?In today's data-driven world, the ability to utilize structured data and advanced AI techniques is a significant advantage. This course equips you with the knowledge and skills to stay ahead of the curve, providing practical, actionable insights that you can apply immediately. Whether you're looking to enhance your career, innovate in your current role, or simply explore the fascinating world of AI, this course offers the comprehensive learning experience you need.Enroll now in "Supercharge AI with Knowledge Graphs: RAG System Mastery" and transform your understanding of AI, knowledge graphs, and Retrieval-Augmented Generation. Take the first step towards mastering the future of AI today!
Who this course is for:
Data Scientists and Analysts
Software Developers and Engineers
AI and Machine Learning Enthusiasts
Business Intelligence Professionals
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