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AWS Certified Machine Learning – Associate Exam Prep and Study Guide: Comprehensive Coverage of all Exam Domains | Scenario-Based Questions | Exam Tips + Hands-on | Practice Test
AWS Certified Machine Learning Engineer – Associate (MLA-C02) Exam Prep & Study Guide helps you build the knowledge, practical skills, and confidence to prepare for the MLA-C02 exam. Through structured explanations, hands-on exercises, and scenario-based questions, this book explores the complete lifecycle of machine learning and generative AI solutions on AWS.
The book also provides a reference to a KnoDAX YouTube tutorial playlist, offering additional AWS walkthroughs and demonstrations to support your learning.
Comprehensive Coverage Across All Exam Domains
Explore data preparation, model development, deployment and orchestration, and the monitoring, maintenance, and security of ML and AI solutions. Learn to evaluate architectural choices and balance quality, performance, reliability, security, and cost.
Traditional ML and Generative AI
Build your understanding of feature engineering, data quality, model selection, training, hyperparameter tuning, evaluation, and explainability. Extend these skills to foundation models, embeddings, vector storage, retrieval-augmented generation (RAG), model customization, and agentic workflows.
AWS Services and Practical Workflows
Learn how Amazon SageMaker AI, Amazon Bedrock, AWS Glue, Amazon S3, Amazon OpenSearch Service, and other AWS services support ML and AI workloads. Explore training and inference strategies, feature management, knowledge bases, agents, automated release pipelines, observability, and access controls.
Practical, Hands-On Learning
Apply chapter concepts through exercises covering ingestion pipelines, leakage-safe data preparation, traceable retrieval corpora, model training, evaluation, deployment, and production monitoring. Practice diagnosing failures, validating permissions, managing resource consumption, and comparing solutions against business requirements.
Exam-Focused Preparation
This guide
• Exam-like scenario-based chapter review questions with answers and explanations.
• A practice test with answers and explanations.
• Coverage organized around the four exam domains.
• Chapter summaries, exam tips, and hands-on exercises.
• Final review decision tables covering service selection, troubleshooting, security, and cost.
• A reference to a KnoDAX YouTube tutorial playlist for additional practical learning.
Develop the reasoning skills needed to identify requirements, recognize common distractors, and select appropriate solutions for AWS scenarios.
Prepare for the MLA-C02 exam while building the skills to develop, deploy, and operate ML and AI solutions on AWS.
The book also provides a reference to a KnoDAX YouTube tutorial playlist, offering additional AWS walkthroughs and demonstrations to support your learning.
Comprehensive Coverage Across All Exam Domains
Explore data preparation, model development, deployment and orchestration, and the monitoring, maintenance, and security of ML and AI solutions. Learn to evaluate architectural choices and balance quality, performance, reliability, security, and cost.
Traditional ML and Generative AI
Build your understanding of feature engineering, data quality, model selection, training, hyperparameter tuning, evaluation, and explainability. Extend these skills to foundation models, embeddings, vector storage, retrieval-augmented generation (RAG), model customization, and agentic workflows.
AWS Services and Practical Workflows
Learn how Amazon SageMaker AI, Amazon Bedrock, AWS Glue, Amazon S3, Amazon OpenSearch Service, and other AWS services support ML and AI workloads. Explore training and inference strategies, feature management, knowledge bases, agents, automated release pipelines, observability, and access controls.
Practical, Hands-On Learning
Apply chapter concepts through exercises covering ingestion pipelines, leakage-safe data preparation, traceable retrieval corpora, model training, evaluation, deployment, and production monitoring. Practice diagnosing failures, validating permissions, managing resource consumption, and comparing solutions against business requirements.
Exam-Focused Preparation
This guide
• Exam-like scenario-based chapter review questions with answers and explanations.
• A practice test with answers and explanations.
• Coverage organized around the four exam domains.
• Chapter summaries, exam tips, and hands-on exercises.
• Final review decision tables covering service selection, troubleshooting, security, and cost.
• A reference to a KnoDAX YouTube tutorial playlist for additional practical learning.
Develop the reasoning skills needed to identify requirements, recognize common distractors, and select appropriate solutions for AWS scenarios.
Prepare for the MLA-C02 exam while building the skills to develop, deploy, and operate ML and AI solutions on AWS.
980 pages, Kindle Edition
Published June 29, 2025
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