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Microsoft Certified: Azure AI Engineer Associate Exam Study Guide The book is a Study Guide for Microsoft Certified: Azure AI Engineer Associate Exam and covers the following: Chapter 1: Introduction to Azure AI and Machine Learning Introduction to Azure AI services and capabilities Overview of Azure Machine Learning service Azure AI and Machine Learning development process Understanding data science and machine learning concepts Ethical considerations in AI and responsible AI practices Chapter 2: Azure Machine Learning Workspace and Data Preparation Setting up Azure Machine Learning workspace Managing and organizing experiments in Azure ML Working with datastores and datasets in Azure ML Data preprocessing and feature engineering in Azure ML Data sampling, splitting, and balancing techniques in Azure ML Chapter 3: Machine Learning Model Training and Evaluation in Azure ML Choosing the right machine learning algorithm in Azure ML Supervised and unsupervised learning techniques in Azure ML Training and fine-tuning machine learning models in Azure ML Hyperparameter tuning and model optimization in Azure ML Evaluating model performance and metrics selection in Azure ML Chapter 4: Azure Machine Learning Pipelines and Deployments Introduction to Azure ML pipelines and workflows Creating and managing ML pipelines in Azure ML Data ingestion and transformation in pipelines in Azure ML Model training and deployment in Azure ML pipelines Monitoring and versioning ML pipelines in Azure Chapter 5: Natural Language Processing (NLP) in Azure Introduction to NLP and language understanding in Azure Text classification and sentiment analysis in Azure Entity recognition and named entity recognition (NER) in Azure Text summarization and language translation in Azure Building chatbots and conversational AI with Azure Bot Service <