AWS Certified Machine Learning – Specialty (MLS-C01) certification validates your ability to design, build, train, deploy, and maintain machine learning solutions on AWS. This 2026 guide covers exam details, skills measured, and preparation strategy.
MLS-C01 assesses advanced knowledge of machine learning workflows on AWS, including data engineering, model training, deployment, monitoring, and optimization.
Supervised learning uses labeled data for prediction, while unsupervised learning discovers hidden patterns in unlabeled data.
Question 1: Which AWS service is primarily used to build, train, and deploy machine learning models at scale?
Explanation: Amazon SageMaker provides fully managed infrastructure for building, training, tuning, and deploying ML models.
Question 2: Which AWS service is best suited for large-scale distributed data processing for machine learning?
Explanation: Amazon EMR is used for big data processing with frameworks like Apache Spark and Hadoop, commonly used in ML pipelines.
Question 3: Which Amazon SageMaker feature helps automatically find the best hyperparameters for a model?
Explanation: SageMaker Hyperparameter Tuning runs multiple training jobs to identify the best-performing model parameters.
Question 4: Which AWS service is commonly used to store large volumes of training data for ML workloads?
Explanation: Amazon S3 provides scalable, durable object storage and is widely used for ML datasets and model artifacts.
Question 5: Which metric is most appropriate for evaluating an imbalanced classification model?
Explanation: Precision and recall provide better insight than accuracy when dealing with imbalanced datasets.
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The AWS Certified Machine Learning – Specialty (MLS-C01) is a certification exam offered by Amazon Web Services (AWS) that validates expertise in building, training, and deploying machine learning (ML) models on AWS. It is intended for individuals who perform a development or data science role, particularly those who create machine learning solutions on AWS.
Minimum two year of hands-on experience in architecting, building or running ML/deep learning workloads on the AWS Cloud.
Experience in handling ML/deep learning frameworks.
Basic understanding and ability to express the purpose of the Machine learning algorithms.
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The AWS Certified Machine Learning – Specialty (MLS-C01) exam tests the ability to design, implement, and deploy machine learning solutions on AWS. It includes 65 multiple-choice and multiple-response questions, with a 170-minute time limit. The exam covers four domains: Data Engineering, Exploratory Data Analysis, Modeling, and Machine Learning Operations. It's intended for professionals with hands-on ML experience on AWS. The passing score typically ranges from 700 to 750 out of 1000.
Your results for the examination are reported as a score from 100-1000, with a minimum passing score of 750. Your score shows how you performed on the examination as a whole and whether or not you passed.
The AWS Certified Machine Learning – Specialty (MLS-C01) certification is valid for three years from the date you earn it. After this period, you will need to renew your certification to maintain your status, which can typically be done by taking the current version of the exam or by earning a higher-level AWS certification.
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The AWS MLS-C01 Certified Machine Learning - Specialty Certification exam measures your ability to accomplish the following technical tasks:
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