Azure ML & Azure OpenAI Applications Training is an advanced, hands-on program focused on building, deploying, and integrating AI applications using Azure Machine Learning and Azure OpenAI services. This course covers the full AI application lifecycle, including model training, generative AI integration, embeddings, application architecture, deployment, and responsible AI practices for enterprise-grade solutions.

• Understand the integration of Azure Machine Learning and Azure OpenAI Service for AI application development
• Build and deploy AI-powered applications using machine learning and Generative AI workflows
• Integrate LLMs, APIs, and Azure cloud services into intelligent applications
• Apply prompt engineering and AI orchestration techniques for business use cases
• Develop scalable AI solutions with monitoring, automation, and deployment best practices
• Understand responsible AI, security, and governance considerations in enterprise AI environments

• AI and machine learning engineers
• Application developers and cloud engineers
• Solution architects and system integrators
• Data scientists and ML practitioners
• Technical leads building AI-powered applications

• Completion of Azure AI Applied Skills or equivalent experience
• Basic understanding of machine learning and cloud concepts
• Familiarity with application or solution architecture

• Building ML models using Azure Machine Learning
• Integrating Azure OpenAI models into applications
• Designing end-to-end AI application architectures
• Deploying and managing AI models in production
• Applying security, governance, and responsible AI practices

By the end of this training, participants will be able to design, build, and deploy intelligent applications using Azure Machine Learning and Azure OpenAI, confidently integrating predictive models and generative AI into secure, scalable, and production-ready solutions.

Foundations of Azure ML & Azure OpenAI Integration
• Role of Azure ML and Azure OpenAI in modern AI applications
• Understanding the AI application lifecycle
• Selecting the right services for use cases

Model Development with Azure Machine Learning
• Data preparation and feature engineering
• Training and evaluating ML models
• Experiment tracking and model versioning

Deploying Models with Azure ML
• Real-time and batch inference
• Endpoint creation and management
• Monitoring model performance

Day Two

Introduction to Azure OpenAI for Applications
• Azure OpenAI models and capabilities
• Text generation, embeddings, and reasoning
• Prompt engineering fundamentals for applications

Building Generative AI Features
• Integrating Azure OpenAI APIs
• Designing prompts for reliability and control
• Using embeddings for semantic search and retrieval

Combining ML Models and LLMs
• Hybrid AI architectures
• ML predictions with generative AI outputs
• Use cases for enterprise applications

End-to-End AI Application Architecture
• Designing scalable AI application architectures
• Integrating APIs, data sources, and AI services
• Performance and cost optimization

Security, Governance, and Responsible AI
• Identity, access control, and data protection
• Bias, fairness, and transparency
• Compliance and responsible AI deployment

Building an AI Application
• Designing an end-to-end AI-powered application
• Applying Azure ML and Azure OpenAI together
• Review, feedback, and optimization

• Fundamentals of Azure Machine Learning and Azure OpenAI Service
• AI model deployment and cloud integration workflows
• Prompt engineering and Generative AI application development
• Workflow automation and intelligent application orchestration concepts
• Security, governance, and responsible AI practices
• Practical hands-on Azure ML and Azure OpenAI implementation exercises

• Model training and deployment exercises
• Generative AI integration tasks
• Final AI application capstone assessment

Participants will receive course materials, slides, reference materials, exercises and access to resources for further learning.

Participants who successfully complete the training will receive an AcadNXT Certification in Azure ML & Azure OpenAI Applications Training, validating their expertise in building and deploying AI-powered applications on Azure.