Data And Ai (Azure Databricks)
Published 12/2024
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz
Generative AI, Data Analytics, Apache Spark, Machine Learning, Deep Learning, RAG, Azure OpenAI, Azure Databricks
What you’ll learn
Data Analytics with Apache Spark in Azure Databricks
Machine Learning with Azure Databricks
Deep Learning with Azure Databricks
Generative AI with Azure Databricks
Implementation of complex concepts like RAG, Hyperparameter tuning, Model Serving with Azure Databricks
Requirements
Familiarity with Python Programming Language is required
A mind open to ideas and new perspectives
Description
Overview
Section 1: Introduction
Lecture 1 Course Introduction
Section 2: Important Concepts
Lecture 2 Understanding Azure Databricks
Lecture 3 Azure Databricks v/s Azure Synapse Analytics
Lecture 4 Microsoft Fabric and Azure Databricks: Match Made in Heaven!!
Section 3: Data Analytics using Apache Spark and SQL
Lecture 5 Understanding Apache Spark and Data Analytics using Azure Databricks
Lecture 6 What is Data Lake and Delta Lake?
Lecture 7 What is a Data Lakehouse?
Lecture 8 What is Apache Spark?
Lecture 9 Unity Catalog ( and MS Purview integration)
Lecture 10 Github Repository for the labs in the course
Lecture 11 Deploying a Databricks Workspace and a Compute Cluster (Hands-On Lab)
Lecture 12 Module 1 (Hands-On Lab)
Lecture 13 Module 2 (Hands-On Lab)
Lecture 14 Module 3 (Hands-On Lab)
Lecture 15 Introduction to Delta Live Tables and Medallion Architecture
Lecture 16 Module 4 (Hands-On Lab)
Section 4: Machine Learning and Deep Learning using Azure Databricks
Lecture 17 Introduction to ML on Azure Databricks
Lecture 18 Understanding Basic ML Concepts
Lecture 19 Understanding Linear Algorithms
Lecture 20 Understanding non-Linear Algorithms
Lecture 21 Module 1: Model Training (Hands-On Lab)
Lecture 22 Module 2: MLflow (Hands-On Lab)
Lecture 23 Module 3: Hyperparameter tuning using Hyperopt (Hands-On Lab)
Lecture 24 Module 4: Using AutoML (Hands-On Lab)
Lecture 25 Introduction to Deep Learning Models
Lecture 26 Module 5: Deep Learning (Hands-On Lab)
Section 5: Generative AI Essentials
Lecture 27 What is Generative AI?
Lecture 28 What is Azure OpenAI?
Lecture 29 What is Prompt Engineering?
Lecture 30 Building Blocks of a Prompt
Lecture 31 Chain Of Thoughts Prompting Technique
Lecture 32 Controlling Output Through Prompt Engineering
Lecture 34 ChatCompletions API to call GPT engine via code (Hands-On Lab)
Lecture 35 What Are Vector Embeddings?
Lecture 36 Making Use of Embedding Engines via code (Hands-On Lab)
Lecture 37 What is RAG (Retrieval Augmented Generation) ?
Section 6: Generative AI and Azure Databricks
Lecture 38 Introduction to Generative AI on Azure Databricks
Lecture 40 Calling Foundational Models via Code (Hands-On Lab)
Lecture 41 Creating a Basic ChatBot using GPT engine (Hands-On Lab)
Lecture 42 Building a RAG Chatbot (Hands-On Lab)
Software Engineers,Data Scientists,Data Analysts,Machine Learning Engineers,AI Enthusiasts,Cloud Architects,Generative AI Enthusiasts
