CertificationsAWSMLA-C01

AWS

Associate

MLA-C01

AWS Certified Machine Learning Engineer – Associate (MLA-C01)

1k+ Learners

4.75(2331 ratings)

Updated 8/18/2026

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0Cheat Sheet(for Quick Exam Reference)

1Mock Tests10 Questions • 20 mins

1Practice Tests5 Questions • 130 mins

1Final Test5 Questions • 130 mins

Overview

The AWS Certified Machine Learning Engineer – Associate certification is designed for individuals who perform a development or data science role and have at least one year of hands-on experience developing, architecting, and maintaining ML or deep learning workloads on the AWS Cloud. This exam validates your ability to build, train, tune, and deploy ML models using the AWS Cloud.

Who Should Take This Course

Developers and data scientists with at least 1 year of experience in building ML solutions using AWS

Professionals aiming to specialize in ML workloads and pipeline automation

Candidates seeking to demonstrate practical skills in implementing, deploying, and monitoring ML models on AWS

Individuals with foundational AWS knowledge and a solid understanding of machine learning principles

Exam Details

Exam Code

MLA-C01

Level

Associate

Duration

170 mins

Total Questions

Scored Questions

Passing Score

720

Fee (USD)

$150

Delivery

Pearson VUE / PSI (testing center or online proctored)

Languages

English, Japanese, Korean, Simplified Chinese

Negative Marking

Domain Distribution

Data Engineering

20%

Design and implement data ingestion and transformation pipelinesChoose appropriate AWS services for data processingPerform feature engineering and feature selection

Exploratory Data Analysis (EDA)

24%

Handle missing and imbalanced dataUse statistics to summarize data characteristicsApply visualization tools to understand data distribution

Modeling

36%

Select appropriate ML models based on task and dataPerform hyperparameter tuningEvaluate model performance using metrics like F1, AUC, RMSEImplement different training strategies (e.g., mini-batch, transfer learning)

Machine Learning Implementation and Operations

20%

Deploy models using Amazon SageMaker endpointsMonitor model performance and data driftAutomate pipelines with SageMaker Pipelines and MLOps best practicesImplement CI/CD practices for ML workflows

Public Questions

Discussion

Every comment below is from a learner who has actually put in practice-exam time on this certification.

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