From the course: Microsoft Azure AI Engineer Associate (AI-102) Cert Prep by Microsoft Press

Exam AI-102: Introduction - Azure Tutorial

From the course: Microsoft Azure AI Engineer Associate (AI-102) Cert Prep by Microsoft Press

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Exam AI-102: Introduction

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- Hello, my name is Tim Warner, and I'd like to welcome you to this video training course on Exam AI-102, "Designing and Implementing a Microsoft Azure AI Solution." I've been an IT professional, technical trainer, and Microsoft specialist for over 25 years. For the last several years, I've been a Microsoft Most Valuable Professional, MVP, in Azure AI, as well as in cloud and data center management. We all know how important artificial intelligence is to business today, especially when you're implementing AI solutions in the Microsoft Azure Cloud. The Azure AI engineer is a subject matter expert responsible for planning, designing, and implementing AI solutions for their employers and clients. This course covers every objective in the AI-102 certification exam. I've passed several versions of this exam, so I've lots and lots and whole bunches of test prep tips and proven practices to share with you. The course exercise files are an optional resource to help you on your AI-102 cert prep journey. Point your web browser to go.techtrainertim.com/ai102. There you'll find a plethora of Microsoft certification-related learning assets. I've created this repository specifically to support your learning throughout this course, so be sure to check it out. Now onto business. Let's review the course lessons one by one in sequential order. In lesson one, "Plan Azure AI Solutions," we'll identify appropriate Azure AI services for business scenarios and evaluate solution constraints like cost, compliance, and scalability. In lesson two, "Design AI Architectures," we'll plan solutions to meet business requirements and configure services for optimal performance. In lesson three, "Manage and Secure AI Solutions," we'll implement monitoring and logging for AI services while applying Azure security best practices. In lesson four, "Moderate Text Content," we'll use Azure AI Content Safety for text moderation and automate workflows for compliance reviews. In lesson five, "Moderate Image Content," we'll implement image moderation using Azure AI services and optimize visual content review processes. In lesson six, "Analyze Images with Pre-Built Models," we'll use Azure AI Vision for object detection and analysis and to generate image tags. In lesson seven, "Create Custom Computer Vision Models," we'll train and deploy custom vision models and optimize them for domain-specific tasks. In lesson eight, "Analyze Video Content," we'll implement video indexing and analysis using Azure services and extract actionable insights. In lesson nine, "Process Text with Azure AI Language," we'll perform sentiment analysis, extract key phrases, and detect entities and PII in text. In lesson 10, "Build Conversational AI with Bots," we'll deploy bots using Azure AI bot framework and integrate question answering and custom intent models. In lesson 11, "Implement Speech-to-Text Solutions," we'll use Azure AI Speech to convert speech-to-text and optimize transcription models for accuracy. In lesson 12, "Deploy Text-to-Speech Solutions," we'll implement multilingual text-to-speech solutions and customized voice synthesis using Azure Speech and SSML. In lesson 13, "Translate and Localized Content," we'll use Azure Translator for multilingual scenarios and integrate translation services into applications. In lesson 14, "Deploy Knowledge Mining Solutions," we'll configure Azure Cognitive Search for knowledge discovery and optimize search indexing and relevance. In lesson 15, "Extract Data from Documents," we'll use Azure Form Recognizer for structured data extraction and automate document processing with custom models. In lesson 16, "Leverage Azure OpenAI Services," we'll use GPT models for text generation and summarization and implement Azure OpenAI assistance and agents. In lesson 17, "Optimized Generative AI models," we'll customize pre-trained models for unique use cases and implement orchestration with semantic kernel. In lesson 18, "Implement Responsible AI Practices," we'll ensure fairness and transparency in AI solutions and apply privacy and security measures. In lesson 19, "Monitor and Optimize AI Solutions," we'll instrument Azure AI services, govern cost, autoscale containers, and implement model reflection. Finally, in lesson 20, "Prepare for the AI-102 Exam," we'll use Microsoft Learn, practice tests, and lab sandboxes to learn study tips and to avoid common pitfalls. Are you ready to become a certified Microsoft Azure AI engineer? Great, let's get to work.

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