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The AWS Certified Machine Learning Engineer – Associate Study Guide gives you the knowledge and practical skills to build, deploy, and manage ML systems on AWS while preparing you for the MLA-C01 exam. This book is designed for data scientists, ML engineers, developers, and cloud professionals who want real-world experience—not just theoretical exam prep.

You’ll work through the entire ML lifecycle using AWS services: ingesting and preparing data with S3, Glue, and SageMaker Data Wrangler; training models with built-in algorithms or custom frameworks; and deploying them using real-time, batch, asynchronous, or serverless endpoints. Each chapter includes hands-on labs, best practices, and exam tips mapped directly to MLA-C01 domains.

You’ll then explore automation with SageMaker Pipelines and CI/CD tooling, as well as critical MLOps skills such as drift detection, bias monitoring, workload security, and cost optimization. The book also features end-to-end case studies and coverage of emerging AWS AI tools—including Amazon Bedrock, JumpStart, and Canvas—so you can apply both traditional and generative AI techniques.

By the end of this guide, you’ll be ready to pass the MLA-C01 exam and confidently design production-ready ML solutions on AWS.