🔥 Generative AI Certification course: https://www.edureka.co/introduction-generative-ai
🔥Introduction to Generative AI : https://www.edureka.co/introduction-generative-ai

This video will revolve around the concept of *Retrieval-Augmented Generation (RAG)* , exploring its definition, how it works, and its applications. We’ll break down the RAG pipeline step-by-step, highlighting how it enhances accuracy and context in responses. A comparison with traditional models will illuminate the advantages of RAG, including improved contextual relevance and factual accuracy. We’ll showcase a mini demo to bring RAG to life and discuss the challenges it faces, such as latency and data quality dependence. Finally, we’ll explore the future of RAG, its potential improvements, and its role in shaping next-generation AI systems.

✅ 00:00 – Introduction to RAG
✅ 01:35 -What is RAG?
✅ 02:08 – Why is it important?
✅ 03:13 – How it works?
✅ 04:08 – Application of RAG?
✅ 05:01 – Comparison with Traditional model
✅ 06:09 – Challenges of RAG
✅ 07:00 – Future of RAG
✅ 08:33 – Project

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What are Outcomes after learning Generative AI course ?

Upon completing the Introduction to Generative AI Fundamentals Course, participants will attain the following learning outcomes:
Develop a comprehensive understanding of generative AI, including its principles, applications, and significance across various domains.
Gain practical experience through interactive sessions and exercises, enabling participants to apply theoretical concepts to real-world scenarios.
Familiarize with popular generative AI algorithms such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformer models.
Explore the creative potential of generative AI in generating realistic images, text, music, and other forms of media, fostering innovation and experimentation.
Understand the ethical implications and considerations associated with generative AI, including privacy, bias, and misuse, and learn strategies to address them responsibly.
By the course’s conclusion, learners will be equipped with the foundational understanding, practical skills, and ethical awareness necessary to leverage generative AI effectively and responsibly in their respective fields.

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