AWS Certified Machine Learning Specialty: Study Guide and Tips

AWS Certified Machine Learning Specialty Study Guide

IMPORTANT NOTICE: The AWS Certified Machine Learning Specialty (MLS-C01) certification is being retired and replaced by the AWS Certified Machine Learning Engineer - Associate (MLA-C01). If you are planning to pursue AWS ML certification, confirm the current status and timeline at aws.amazon.com/certification before starting your study plan. This guide covers MLS-C01, but you should verify whether to pursue this or the newer MLA-C01 certification.

MLS-C01 Exam Specifications

The AWS ML Specialty exam costs $300. You will have 180 minutes (3 hours) to answer 65 questions. The passing score is 750 out of 1,000. This is a multiple-choice and multiple-response exam covering five domains.

The Five Exam Domains

The certification tests knowledge across these five areas:

• Data Engineering: Transforming raw data into ML-ready datasets using AWS Glue, Data Pipeline, and related services.
• Exploratory Data Analysis: Using Amazon SageMaker, Athena, and QuickSight to understand and visualize data patterns.
• Modeling: Training, tuning, and evaluating models using SageMaker, including algorithm selection and hyperparameter optimization.
• Machine Learning Implementation and Operations: Deploying models, setting up endpoints, and monitoring in production.
• ML Security and Governance: IAM, encryption, compliance, and responsible AI practices.

Study Approach for Each Domain

Start with the Data Engineering domain using AWS Glue and Data Pipeline documentation. For Exploratory Data Analysis, practice with SageMaker notebooks and QuickSight dashboards on real datasets. The Modeling domain is the heaviest; allocate the most study time here. Understand XGBoost, Linear Learner, and image classification algorithms deeply. For Implementation and Operations, practice deploying models and monitoring endpoints.

Practice and Resources

Use AWS's official ML learning paths and practice exams. Build projects in SageMaker—this is your best study tool. The AWS ML path includes hands-on labs that directly map to exam domains. Time your practice: spend 6-8 weeks on domains 1-2, then 6-8 weeks heavily on domain 3 (modeling), and 2-3 weeks on domains 4-5.

Important: Verify Current Certification Status

Before scheduling your exam, visit aws.amazon.com/certification to confirm whether MLS-C01 is still active or if you should pursue MLA-C01 instead. AWS periodically updates and retires certifications. The newer MLA-C01 may be a better choice depending on when you plan to test.

Verification: This guide reflects MLS-C01 specifications as of 2026. AWS certification requirements and exam content change periodically. Always verify current exam details and domain focus at the official AWS certification page.

Learn more about AWS ML preparation in the AI/ML Certification Coach.