Edureka! Masterclass

Description

Learn how to build an intelligent Document Q&A Chatbot using RAG (Retrieval-Augmented Generation), ChromaDB, and LLaMA 3. In this hands-on LIVE session, you’ll upload PDFs, create embeddings, store them in a vector database, and build a complete retrieval pipeline to answer questions from documents accurately. Watch a LIVE comparison of Retrieval vs Hallucination and understand how RAG improves AI response quality in real-world applications. 🔥 What you’ll learn: • RAG vs Fine-Tuning —

Agenda

• • RAG vs fine-tuning: when to use what
• • Chunking strategies & embedding models
• • Vector DB setup with ChromaDB / Pinecone
• • Retrieval pipeline: end-to-end build
• • RAGAS evaluation metrics

Description

Learn how to build an intelligent Document Q&A Chatbot using RAG (Retrieval-Augmented Generation), ChromaDB, and LLaMA 3. In this hands-on LIVE session, you’ll upload PDFs, create embeddings, store them in a vector database, and build a complete retrieval pipeline to answer questions from documents accurately. Watch a LIVE comparison of Retrieval vs Hallucination and understand how RAG improves AI response quality in real-world applications. 🔥 What you’ll learn: • RAG vs Fine-Tuning —

Agenda

• • RAG vs fine-tuning: when to use what
• • Chunking strategies & embedding models
• • Vector DB setup with ChromaDB / Pinecone
• • Retrieval pipeline: end-to-end build
• • RAGAS evaluation metrics

Webinar Facts

• There will be 11.5 million jobs in the Data Science field by 2026

• A Senior Data Scientist is expected to earn over 20 to 25 Lacs a year

• Data Analytics Market is expected to grow a CAGR of 30.08%

Description

Learn how to build an intelligent Document Q&A Chatbot using RAG (Retrieval-Augmented Generation), ChromaDB, and LLaMA 3. In this hands-on LIVE session, you’ll upload PDFs, create embeddings, store them in a vector database, and build a complete retrieval pipeline to answer questions from documents accurately. Watch a LIVE comparison of Retrieval vs Hallucination and understand how RAG improves AI response quality in real-world applications. 🔥 What you’ll learn: • RAG vs Fine-Tuning —

Agenda

• • RAG vs fine-tuning: when to use what
• • Chunking strategies & embedding models
• • Vector DB setup with ChromaDB / Pinecone
• • Retrieval pipeline: end-to-end build
• • RAGAS evaluation metrics

Webinar Facts

• The DevOps market size is projected to reach $9,407 million by 2023

• ADP, BBC News, eBay, GE, ING, Intuit, PayPal, Splunk, Uber & other MNCs worldwide use DevOps

• The average salary given to a DevOps Engineer is around Rs. 617K per annum - Indeed.com

Description

Learn how to build an intelligent Document Q&A Chatbot using RAG (Retrieval-Augmented Generation), ChromaDB, and LLaMA 3. In this hands-on LIVE session, you’ll upload PDFs, create embeddings, store them in a vector database, and build a complete retrieval pipeline to answer questions from documents accurately. Watch a LIVE comparison of Retrieval vs Hallucination and understand how RAG improves AI response quality in real-world applications. 🔥 What you’ll learn: • RAG vs Fine-Tuning —

Agenda

• • RAG vs fine-tuning: when to use what
• • Chunking strategies & embedding models
• • Vector DB setup with ChromaDB / Pinecone
• • Retrieval pipeline: end-to-end build
• • RAGAS evaluation metrics

Webinar Facts

• The value of the global machine learning market is likely to reach USD 117 billion by the end of 2027 at a CAGR of 39%. (GlobeNewswire)

• 65% of companies who are planning to adopt machine learning say the technology helps businesses in decision-making.

• The average salary for a machine learning engineer is $150,099 per year in the United States.- Indeed.com