Designing and Implementing an Azure AI Solution Training

Offered to the Jacksonville and Northeast Florida community through UNF Professional and Lifelong Learning in partnership with Applied Technology Academy — live online or in person, taught by ATA's practitioner instructors.

Course Overview

• Design and implement AI solutions using Azure Cognitive Services
• Build, train, and deploy machine learning models using Azure resources
• Create conversational AI experiences with the Azure Bot Service and Bot Framework
• Implement computer vision, natural language processing, and speech solutions
• Integrate AI services securely and efficiently into existing applications

Course Outline

• Module 1: Introduction to Azure AI Services
  • Overview of Azure AI portfolio
  • Cognitive Services overview
  • Understanding responsible AI principles
• Module 2: Developing AI Apps with Cognitive Services
  • Using SDKs and REST APIs
  • Authentication and authorization with Cognitive Services
  • Managing and monitoring Azure AI resources
• Module 3: Implementing Computer Vision Solutions
  • Analyzing images with the Computer Vision service
  • Detecting and recognizing faces
  • Implementing custom vision models
• Module 4: Implementing Natural Language Processing Solutions
  • Using Azure AI Language services
  • Performing sentiment analysis, key phrase extraction, and translation
  • Building custom text classification models
• Module 5: Implementing Speech Solutions
  • Speech-to-text and text-to-speech capabilities
  • Translating spoken language
  • Implementing speaker recognition
• Module 6: Creating Conversational AI with Azure Bot Service
  • Designing conversational flows
  • Integrating Azure Cognitive Services with bots
  • Deploying and testing bots with Azure Bot Framework Composer
• Module 7: Implementing Knowledge Mining with Azure Cognitive Search
  • Building intelligent search solutions
  • Integrating AI enrichment into data sources
  • Managing indexes and search performance
• Module 8: Integrating AI Models and Services
  • Combining multiple AI services in solutions
  • Using Azure Machine Learning for custom models
  • Managing AI pipelines and deployment
• Module 9: Monitoring, Security, and Compliance
  • Implementing monitoring and diagnostics for AI services
  • Ensuring data privacy and compliance
  • Applying responsible AI principles in deployment

Intended Audience

• AI Engineers
• AI Developers
• Machine Learning Engineers focused on solution integration

Prerequisites

• Knowledge of Microsoft Azure and basic cloud concepts
• Experience in at least one programming language such as Python or C#
• Understanding of REST APIs and JSON data structures