Module 1: Azure & AI Fundamentals

• Understand global Azure infrastructure (regions, availability zones)

• Learn core Azure services for data and AI

• Explore Azure AI services and responsible AI principles

Module 2: Data Fundamentals for AI on Azure

• Work with Azure Storage, Azure SQL, and Azure Data Lake

• Ingest and explore data with Azure Data Factory and Azure Synapse

• Clean, transform, and prepare data for machine learning

Module 3: Core Machine Learning Concepts

• Supervised vs. unsupervised learning

• Train/test split, cross-validation, and evaluation metrics

• Overfitting, underfitting, and regularization

Module 4: Building Models with Azure Machine Learning

• Create and manage workspaces, compute, and environments

• Train and register models using Azure ML

• Use automated ML to quickly build baseline models

Module 5: Computer Vision & NLP with Azure AI Services

• Build image analysis solutions with Azure AI Vision

• Use Azure AI Language for text analytics and sentiment analysis

• Design end-to-end scenarios combining multiple AI services

Module 6: Generative AI with Azure OpenAI Service

• Understand large language models and prompt engineering

• Build chatbots and content generation apps with Azure OpenAI

• Apply safety, governance, and responsible AI practices

Module 7: MLOps & Deployment on Azure

• Deploy models as real-time and batch endpoints

• Implement CI/CD for ML with Azure DevOps or GitHub

• Monitor, retrain, and manage models in production

Module 8: Exam Preparation & Practice

• Map each module to Microsoft AI/ML certification exam objectives

• Review key Azure services, patterns, and best practices

• Practice with exam-style questions and case studies

By the end of this program, learners will be ready to design, build, and deploy AI/ML solutions on Microsoft Azure and confidently sit for the Microsoft AI/ML certification exams.