YoVDO

Accelerating Operational Excellence with Generative AI - Implementing RAG for Customer Service Efficiency

Offered By: Databricks via YouTube

Tags

Retrieval Augmented Generation Courses Customer Service Courses Databricks Courses Generative AI Courses Feedback Loops Courses Data Pipelines Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore a 32-minute conference talk showcasing how a Financial/Insurance company implemented a Retrieval Augmented Generation (RAG) system to enhance customer service efficiency. Gain insights into the RAG architecture and learn how Databricks was utilized to build a robust data pipeline for indexing content and collecting user feedback. Discover innovations such as multi-stage content chunking, advanced search retrieval techniques, and an evaluation framework for optimization. Understand how the feedback loop using Databricks workflow improves the RAG implementation. Learn about the unique orchestration layer that accelerates Generative AI use cases. Grasp how Generative AI can transform customer service operations with strategies for efficiency and automation. Apply these learnings to any customer service organization striving for operational excellence. Presented by Gen Li, Lead Data Engineer, and Peter Landis, Principal Engineer from Northwestern Mutual. Access additional resources including the LLM Compact Guide and Big Book of MLOps. Connect with Databricks through their website and various social media platforms for further engagement.

Syllabus

Accelerating Operational Excellence with Generative AI


Taught by

Databricks

Related Courses

Pinecone Vercel Starter Template and RAG - Live Code Review Part 2
Pinecone via YouTube
Will LLMs Kill Search? The Future of Information Retrieval
Aleksa Gordić - The AI Epiphany via YouTube
RAG But Better: Rerankers with Cohere AI - Improving Retrieval Pipelines
James Briggs via YouTube
Advanced RAG - Contextual Compressors and Filters - Lecture 4
Sam Witteveen via YouTube
LangChain Multi-Query Retriever for RAG - Advanced Technique for Broader Vector Space Search
James Briggs via YouTube