Free Download Azure Ai Services Complete Guide - Covers AI-102 Cert
Published 11/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 11.30 GB | Duration: 13h 0m
Azure AI Services, OpenAI, LLM, ChatGPT, MLOps, CICD, Containerise AI Applications, Run LLM locally, Azure AI 102 Exam
What you'll learn
Deploy and Manage Azure AI Services
Basic knowledge on neural networks and LLM
Deploy custom azure AI models and MLOps/CICD pipeline.
Container solutions for Azure AI Services
Microsoft Certified: Azure AI Engineer Associate Azure AI 102
Requirements
None
Description
This course provides a comprehensive introduction to Azure AI services, covering fundamentals of neural networks, and AI application development. Students learn to design, implement, and deploy Azure AI solutions using Azure Computer Vision, Language, Decision services and many more.In Chapter 1, we cover the fundamentals of artificial intelligence, focusing on neural networks and large language models (LLMs). We will learn what AI is, why it's valuable, and how neural networks power complex AI capabilities. We will have a look at LLM models, how to download those models and run those models locally.Chapter 2 is all about Azure AI services, offering hands-on guidance for deploying and using Azure AI Services (such as Azure AI Vision, Azure AI Content Safety, Azure AI Language, Azure AI Speech, Azure AI Translator, Azure AI Video Indexer,Azure Document Intelligence, Azure AI Search), Azure OpenAI Models like chatgpt, DallE, embedding models for LLM capabilities and image generation. This chapter also teaches how to build tailored AI solutions by creating custom models and containerising Azure AI services, enabling on-premises or edge deployments. MLOps and CI/CD practices are also covered, showing how to automate continuous deployment and manage lifecycle operations efficiently for AI models and services.Finally, Chapter 3 is dedicated to Azure AI 102 exam preparation for the Azure AI Associate certification, focusing on the exam's requirements and objectives. This chapter provides study guides and practice questions.
Overview
Section 1: Introduction to AI
Lecture 1 Introduction
Lecture 2 Limits of Traditional Computing
Lecture 3 Neural Networks
Lecture 4 Overview of Neural Networks
Lecture 5 Language Model Studio
Lecture 6 Training Resources
Lecture 7 Rest API
Section 2: Azure AI Services
Lecture 8 Azure Content Moderator Explained
Lecture 9 Azure Content Moderator Text Moderation
Lecture 10 Azure Content Moderator Image Moderation
Lecture 11 Azure AI Content Safety - Text & Image Moderation
Lecture 12 Azure AI Content safety - Blocklist
Lecture 13 Analyze images using Azure AI Vision
Lecture 14 Azure AI Vision Landmark Detection
Lecture 15 Azure AI Vison Brand Detection, Extract text, Image Tag
Lecture 16 Custom Vision - Image Classification
Lecture 17 Custom Vision - Image Classification Part - 2
Lecture 18 Custom Vision Studio, Evaluation Metrics & Object Detection
Lecture 19 Conversational Language Understanding Model by Azure AI Language
Lecture 20 Conversational Language understanding model - Demo
Lecture 21 Analyze text using Azure AI Language
Lecture 22 Text to speech using Azure AI Speech Service
Lecture 23 Speech to text conversion and translation using Azure AI Speech
Lecture 24 SSML - Speech Markup Language
Lecture 25 Custom speech Model
Lecture 26 CICD/MLOps concepts
Lecture 27 Deploying a Custom Speech Model using CICD
Lecture 28 Azure AI Translator service
Lecture 29 Azure AI Document Intelligence - prebuilt models
Lecture 30 Custom Document Intelligence model
Lecture 31 Azure AI Search Part-1
Lecture 32 Azure AI Search Part-2
Lecture 33 OpenAI - Deploy gpt Model, Prompts, Parameters, Content Filter
Lecture 34 OpenAI - Fine tune, use private data, DallE
Lecture 35 Azure AI Video Indexer
Lecture 36 Azure AI Vision Spatial Analysis
Lecture 37 Manage, monitor, and secure an Azure AI service
Lecture 38 Plan and implement a container deployment
Lecture 39 Custom Question Answering using AI Language
Section 3: Azure AI 102 Exam
Lecture 40 Intro - Exam AI 102
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