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Udemy - Building Ai Applications With Databricks And Gen Ai - OneDDL - 06-30-2025 Free Download Udemy - Building Ai Applications With Databricks And Gen Ai Published 5/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 7.40 GB | Duration: 7h 12m Unlock the power of AI with Databricks & GenAI - Transforming data into intelligence, one application at a time! What you'll learn Use of Vector Search and LLM Models inside Databricks Build Applications and deploy to Databricks Apps Build End - End Data Refresh cycle Automatic refresh data Requirements You should be good in Python Programming Language Description This comprehensive course will teach you how to develop cutting-edge AI applications by combining the power of Databricks and Large Language Models (LLMs). You will explore how to leverage Databricks for large-scale data processing, feature engineering, and model training, while integrating advanced LLMs for natural language processing (NLP) tasks such as text classification, summarization, semantic search, and conversational AI.Through hands-on labs and real-world projects, you will gain practical experience in building intelligent systems that can understand, process, and generate human language. This course is ideal for data scientists, machine learning engineers, and developers who want to stay ahead in the rapidly evolving world of AI.By the end of the course, you will have a strong understanding of how to architect end-to-end AI pipelines using Databricks and LLMs, deploy scalable NLP applications, and apply industry best practices for model integration and performance optimization.Key Highlights:Scalable data processing and ML using DatabricksNLP-powered applications with state-of-the-art LLMsPractical, project-based learning approachReal-world AI use cases and deployment strategiesUse Vector Search indexes to store indexesUse workflows to refresh the data end - end on schedule basisUse Serverless compute to refresh the dataUse Databricks Apps to deploy the application Overview Section 1: Architecture and Prerequiste Lecture 1 Introduction Lecture 2 Understanding of Dataset Lecture 3 Databricks Workspace Setup in AWS Lecture 4 Create S3 Bucket Lecture 5 Download Dataset Lecture 6 Prepare Source System - Upload Datasets in S3 Bucket Section 2: Ingest Data from S3 to Unity Catalog Lecture 7 Create Schema Lecture 8 Understand Groups and Permission Lecture 9 How to get access on S3 bucket and Create Scopes in AWS Databricks Lecture 10 Ingest Data from S3 to Bronze Layer Lecture 11 Create Repo and Link in Databricks Lecture 12 Ingest other data into Bronze Layer and Setup Workflow Section 3: Cleaning the bronze data Lecture 13 Build Lakehouse Quality Dashboard Manually Lecture 14 Create Monitor for all the Bronze Tables - Automation Lecture 15 Create Clean Notebook for Patient Data Lecture 16 Create Clean Notebook for Other Tables - Optimise Lecture 17 Create Clean Notebook for Other Tables Lecture 18 Update Workflow for Silver Notebooks Section 4: Ingest data into Gold Layer Lecture 19 Create Dimension Master Table Gold Layer and Add in Workflows Section 5: Vector Search and Embedding Models Lecture 20 Create Vector Search Endpoint Lecture 21 Create Embedding Model and Serving EndPoint Lecture 22 Create Embeddings and Create VS Index table Lecture 23 Update Workflow - Add VS Notebooks Section 6: Setup Model Serving Endpoint Lecture 24 Create Serving Endpoint with RAG Lecture 25 Query serving endpoint Lecture 26 Run Workflows using SPN Section 7: Build Streamlit Chatbot App Lecture 27 Create Streamlit ChatBot Application Intermediate Databricks Engineer Homepage [To see links please register or login] Recommend Download Link Hight Speed | Please Say Thanks Keep Topic Live [To see links please register or login] No Password - Links are Interchangeable