Description
Generative AI with Context: RAG, CAG & KAG Applications is a course on basing outputs on structured, relevant, and trusted information published by Udemy Online Academy. Generative AI with Context: RAG, CAG, and KAG Applications focuses on building intelligent AI systems that go beyond generic responses by basing outputs on structured, relevant, and trusted information. This course explores how contextual techniques such as retrieval-based additive manufacturing, context-based additive manufacturing, and knowledge-based additive manufacturing improve accuracy, relevance, and reliability in real-world AI applications. Learners will gain a clear understanding of how to design, integrate, and deploy these approaches to create scalable, context-aware AI solutions for research, enterprise systems, and production environments.
Artificial intelligence is evolving rapidly and is the next frontier in the field. Models that can understand, retrieve, and reason with the right information at the right time are not only more accurate, but also smarter, more reliable, and closer to human intelligence. This course, Text-Aware AI, is designed to give you the skills and confidence to build these systems. By the end, you’ll not only understand how text-aware AI works, but you’ll have built workflows that you can adapt to your own projects, whether you’re developing smarter chatbots, enterprise search tools, or advanced reasoning systems.
What you will learn in Generative AI with Context: RAG, CAG & KAG Applications:
- Build context-aware AI pipelines using Retrieval Augmented Generation (RAG), Cache Augmented Generation (CAG), and Knowledge Augmented Generation (KAG).
- Apply semantic search and embeddings to connect models to external knowledge sources for more accurate answers.
- Optimize AI performance with caching strategies that reduce redundancy and improve efficiency in real-world applications. – Use knowledge graphs to build.
- Use knowledge graphs for structured reasoning and enable AI systems to extract entities, facts, and relationships.
- Debug and refine AI workflows step-by-step, gain confidence in troubleshooting, and improve pipeline reliability.
- And…
Course specifications
Publisher: Udemy
Instructors: Navid Shirzadi, Ph.D.
Language: English
Level: Introductory to Advanced
Number of Lessons: 41
Duration: 8 hours and 28 minutes
Course topics
Generative AI with Context: RAG, CAG & KAG Applications Prerequisites
This course is designed to be accessible, even if you’re new to context‑aware AI. There are no strict prerequisites, but having some basic familiarity with programming and machine learning will make the journey smoother.
Programming Skills: A beginner‑level understanding of Python is helpful, since all hands‑on projects are built in Python.
If you’re a complete beginner, don’t worry – the course is structured to guide you through installations, setup, and every workflow with clear explanations and exercises. The goal is to lower barriers and make advanced AI concepts approachable, so you can focus on learning and building.
Pictures
Generative AI with Context: RAG, CAG & KAG Applications introduction video
Installation guide
After Extract, watch with your favorite Player.
Subtitle: None
Quality: 1080p
Downloadly link
Rapidgator link
File password (s): www.downloadly.ir
Size
5.5 GB
