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Microsoft Azure AI Engineer Associate (AI-102) Cert Prep by Microsoft Press

Microsoft Azure AI Engineer Associate (AI-102) Cert Prep by Microsoft Press

7h 3mBeginner2025-08-08

Authors

Microsoft Press

Microsoft Press

Microsoft

Tim Warner

Tim Warner

Technical Trainer and Content Developer

Course details

This comprehensive course is designed to provide you with a solid understanding of Azure AI services and equip you with the skills required to excel in the AI-102 certification exam. In this course from Microsoft Press, instructor Tim Warner explores topics such as Azure AI resource management, image and video processing, natural language processing, knowledge mining, and using the various OpenAI solutions. Build your understanding of the prerequisites for the subsequent specialized courses in the AI-102 roadmap. By the end of this course and its related specialized courses, you will have a strong grasp of the Azure AI ecosystem and its applications. The skills acquired from this course will empower you to stay at the forefront of the AI revolution.

Concepts

Introduction

  • Exam AI-102 - Introduction

Plan Azure AI Solutions

  • Learning objectives
  • Identify appropriate Azure AI services for business scenarios
  • Evaluate solution constraints (cost, compliance, scalability)

Design AI Architectures

  • Learning objectives
  • Plan AI solution architecture to meet business requirements
  • Configure services for optimal performance

Manage and Secure AI Solutions

  • Learning objectives
  • Implement monitoring and logging for AI services
  • Apply security best practices to Azure AI workloads

Moderate Text Content

  • Learning objectives
  • Use Azure AI Content Safety for text moderation
  • Automate workflows for compliance reviews

Moderate Image Content

  • Learning objectives
  • Implement image moderation using Azure AI services
  • Optimize visual content review processes

Analyze Images with Prebuilt Models

  • Learning objectives
  • Use Azure AI Vision for object detection and analysis
  • Detect objects and generate image tags with Azure AI Vision

Create Custom Computer Vision Models

  • Learning objectives
  • Train and deploy custom vision models
  • Test and optimize models for domain-specific tasks

Analyze Video Content

  • Learning objectives
  • Implement video indexing and analysis using Azure services
  • Extract actionable insights from video content

Process Text with Azure AI Language

  • Learning objectives
  • Perform sentiment analysis and extract key phrases
  • Perform text analysis with sentiment, key phrases, and more

Build Conversational AI with Bots

  • Learning objectives
  • Deploy bots using Azure Bot Service
  • Integrate question answering and custom intent models

Implement Speech-to-Text Solutions

  • Learning objectives
  • Use Azure Speech to convert speech to text
  • Optimize transcription models for accuracy

Deploy Text-to-Speech Solutions

  • Learning objectives
  • Implement text-to-speech solutions for multilingual applications
  • Customize voice synthesis using Azure Speech and SSML

Translate and Localize Content

  • Learning objectives
  • Use Azure Translator for multilingual scenarios
  • Integrate translation services into applications

Deploy Knowledge-Mining Solutions

  • Learning objectives
  • Configure Azure Cognitive Search for knowledge discovery
  • Optimize search indexing and relevance

Extract Data from Documents

  • Learning objectives
  • Use Azure Form Recognizer for structured data extraction
  • Automate document processing and integrate document intelligence

Leverage Azure OpenAI Services

  • Learning objectives
  • Use GPT models for text generation and summarization
  • Use Azure OpenAI Service models for text, code, and image generation
  • Use Azure OpenAI Assistant and Azure AI Agent Service

Optimize Generative AI Models

  • Learning objectives
  • Customize pre-trained models for unique use cases
  • Integrate generative AI into applications
  • Use Semantic Kernel and Autogen in agent workflows

Implement Responsible AI Practices

  • Learning objectives
  • Ensure fairness and transparency in AI solutions
  • Meet compliance requirements with privacy and security measures

Monitor and Optimize Azure AI Solutions

  • Learning objectives
  • Instrument services with diagnostics
  • Govern cost with workbooks and alerts
  • Auto-scale and update container deployments
  • Trace, collect feedback, and reflect models

Prepare for the AI-102 Exam

  • Learning objectives
  • Use Microsoft Learn, practice tests, and sandboxes
  • Study tips and common pitfalls

Conclusion

  • Exam AI-102 summary

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