AWS Certified: Machine Learning Engineer Associate

Intermediate Level

The AWS Certified Machine Learning Engineer – Associate validates your ability to design, deploy, and scale machine learning (ML) solutions on AWS, ensuring robust MLOps practices and operational excellence.
Machine Learning Engineer Associate certification is designed for professionals who build, deploy, and maintain ML solutions on AWS. It targets individuals with at least one year of experience using Amazon SageMaker and other AWS ML services, such as backend developers, DevOps engineers, data engineers, and data scientists.
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Course Summary:

MLOps Engineering on AWS equips you with hands-on skills to build, automate, and manage end-to-end ML pipelines using AWS services, aligning with MLOps best practices.

This AWS Machine Learning course is designed to integrate DevOps methodologies into every stage of machine learning—from development and training to deployment. Participants, including ML data platform engineers, DevOps specialists, and operations professionals, will learn to streamline the transitions among data engineers, data scientists, and software developers by using automation, specialized tools, structured processes, and strong teamwork.

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Fees:

RM5,400

Intakes:

10-12 Mar 2025 | 18-20 Jun 2025

Skills measured:

  • Data Preparation for Machine Learning (ML) – 28%
  • ML Solution Monitoring, Maintenance, and Security – 24%
  • Deployment and Orchestration of ML Workflows – 22%
  • ML Model Development – 26%

Who is this for?

  • ML Engineers and Data Scientists building production-ready ML models.
  • Solutions Architects designing AWS-based ML systems.
  • DevOps Engineers implementing MLOps pipelines.
  • IT Professionals transitioning into ML roles.
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Showcase proficiency in architecting scalable data models, overseeing end-to-end data lifecycle management, and enforcing robust data quality assurance protocols.

AWS ML Engineers earn 25-30% higher salaries in Southeast Asia, with surging demand for cloud-based ML expertise.
Salary Premium: JobStreet Malaysia reports AWS ML-certified roles offer MYR 120,000–180,000/year, 30% above non-certified peers.
Cloud Skills Gap: LinkedIn highlights a 45% shortage of ML engineers in SEA, with AWS certifications listed in 35% of ML job postings.
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Validate ML Expertise:

Prove your ability to operationalize ML workflows on AWS.

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Master AWS Services:

Gain proficiency in SageMaker, Lambda, and MLOps tools.

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Career Advancement:

Unlock roles like ML Engineer, AI Solutions Architect, or MLOps Specialist.

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Industry Recognition:

Join a global network of AWS-certified professionals trusted by enterprises.

Why choose Trainocate?

Trainocate was recognized as the 2024 AWS Training Partner of the Year at AWS re:Invent 2024, highlighting its excellence in cloud skills development and commitment to digital transformation in Malaysia. This award reinforces Trainocate’s reputation as a top-tier AWS training provider, ensuring learners receive industry-recognized education with the latest cloud technologies. By choosing Trainocate, participants benefit from an award-winning institution dedicated to equipping professionals with in-demand AWS skills to drive career growth and business innovation.

Exam Overview

Category:

Associate

Exam Duration:

130 minutes

Exam Format:

65 questions

Cost:

150 USD
Visit Exam pricing for additional cost information, including foreign exchange rates

Language offered:

English, Japanese, Korean, and Simplified Chinese

Intended candidate:

Individuals with at least 1 year of experience using Amazon SageMaker and other ML engineering AWS services

Candidate role examples:

Backend software developer, DevOps engineer, data engineer, MLOps engineer, and data scientist

Testing options:

Pearson VUE testing center or online proctored exam

Open up new possibilities for your career

Frequently Asked Questions (FAQs)

The ideal candidate for this exam has at least 1 year of experience in machine learning engineering or a related field and 1 year of hands-on experience with AWS services. Professionals who do not have prior machine learning experience can take the training available in the Exam Prep Plans and get started building their knowledge and skills.

Per the World Economic Forum Future of Jobs Report 2023, demand for AI and Machine Learning Specialists is expected to grow by 40%. However, 70% of North American IT leaders say they have the greatest difficulty filling AI/ML specialist roles. This certification can position you for in-demand machine learning jobs in AWS Cloud.

AWS Certified Machine Learning Engineer – Associate is a role-based certification designed for ML engineers and MLOps engineers with at least one year of experience in AI/ML.

AWS Machine Learning – Specialty is a specialty certification covering topics across data engineering, data analysis, modeling, and ML implementation and ops. It is more suitable for individuals with 2 or more years of experience developing, architecting, and running ML workloads on AWS.

For professionals looking to dive deeper into machine learning, we recommend AWS Certified Machine Learning – Specialty.

This certification is valid for 3 years. Before your certification expires, you can recertify by passing the latest version of this exam. Learn more about recertification options for AWS Certifications.

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