Applied AI · Practitioner tier
AWS Certified Machine Learning Engineer Associate (MLA-C01 current; MLA-C02 exam guide published, beta only, GA date TBD)
AWS Certified Machine Learning Engineer Associate (MLA-C01 current; MLA-C02 exam guide published, beta only, GA date TBD) is a practitioner-tier Applied AI credential from Amazon Web Services. The exam runs $150 and covers data preparation, feature engineering, and data quality on aws. Most candidates prepare for around 80 hours and pair the credential with a portfolio of platform-aligned work.
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Exam fee
$150
Prep time
80h
Duration
170 min
Level
Practitioner
Where this credential sits
AWS Certified Machine Learning Engineer Associate (MLA-C01 current; MLA-C02 exam guide published, beta only, GA date TBD) sits at the practitioner tier. The credential validates production readiness on the relevant cloud platform: data preparation, model training, deployment, monitoring, MLOps, and generative AI integration. Hiring managers reading the resume see a candidate who has worked the platform at production depth, not someone reading about it.
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What this certification covers
- Data preparation, feature engineering, and data quality on AWS
- Model training, tuning, and evaluation using SageMaker
- Deployment patterns: real-time, batch, asynchronous, and serverless inference
- ML operations: CI/CD pipelines, model registry, drift detection, retraining triggers
- Cost, latency, and reliability tuning for production ML systems
- Security and compliance for ML workloads (IAM, VPC, encryption, audit)
- Generative AI integration patterns including Bedrock and customized foundation models
- Monitoring with CloudWatch, Model Monitor, and Clarify
Who should pursue this
- Practitioners moving from data science notebooks into production ML on AWS
- Software engineers crossing into ML engineering roles at AWS-first companies
- ML engineers consolidating cloud-platform credibility for senior or staff-track promotions
- Cloud engineers who own ML infrastructure and want a vendor-validated baseline
Prerequisites
- No formal prerequisites
- AWS recommends 1+ year of experience using SageMaker and adjacent ML services in production-adjacent settings
Cost breakdown
Exam
$150
Training
$200 to $1500
Recertification
Every 3y
Total first-year cost runs from $150 (exam-only with free self-study) up to $1650 with paid instructor-led training. Recertification every 3 years.
Pricing reflects publicly listed vendor pricing as of April 2026. Verify current pricing at the Amazon Web Services certification page before registering.
Difficulty assessment
Study hours
80h
Exam format
Multiple choice
Passing score
Approximate 720/1000 scaled score
Substantial preparation load at roughly 80 hours of focused study. Most candidates with active cloud and ML engineering background prepare across 8 to 14 weeks. Candidates without prior platform experience should expect closer to 16 weeks. Pass rates are not officially published by Amazon Web Services, so plan against the study-hour estimate rather than guessing at exam difficulty from forum threads.
Full exam format: Multiple choice, multiple response, ordering, matching, and case study. AWS opened MLA-C02 beta registration September 1, 2026 with beta delivery starting September 29, 2026; its exam guide is published but AWS has not announced a GA date or scoring for it yet. MLA-C01 remains the live, scorable version through September 28, 2026 in English (later in Korean, Japanese, and Simplified Chinese, until MLA-C02 reaches general availability).. Total seat time: 170 minutes.
Roles this credential supports
Alternatives and adjacent credentials
- Google Cloud Professional Machine Learning Engineer. Same tier on a different cloud platform. Pick the credential matched to your target employer's primary platform. Studying for one builds most of the conceptual ground for the other.
- Microsoft Certified: Azure AI Engineer Associate (retired; successor: Developing AI Apps and Agents on Azure). Same tier on a different cloud platform. Pick the credential matched to your target employer's primary platform. Studying for one builds most of the conceptual ground for the other.
- AWS Certified Machine Learning Specialty (legacy track, retired March 31, 2026)
AWS Certified Machine Learning Engineer Associate (MLA-C01 current; MLA-C02 exam guide published, beta only, GA date TBD) questions and answers
What is the AWS Certified Machine Learning Engineer Associate (MLA-C01 current; MLA-C02 exam guide published, beta only, GA date TBD)?
AWS Certified Machine Learning Engineer Associate (MLA-C01 current; MLA-C02 exam guide published, beta only, GA date TBD) is a practitioner-tier Applied AI credential from Amazon Web Services. The exam runs $150 and covers data preparation, feature engineering, and data quality on aws. Most candidates prepare for around 80 hours.
How much does the AWS Certified Machine Learning Engineer Associate (MLA-C01 current; MLA-C02 exam guide published, beta only, GA date TBD) cost?
The exam itself is $150 as of April 2026. Training adds $200 to $1500, with free self-study options available for most cloud-platform credentials. Recertification every 3 years. Verify current pricing at the Amazon Web Services website before registering.
Who should pursue the AWS Certified Machine Learning Engineer Associate (MLA-C01 current; MLA-C02 exam guide published, beta only, GA date TBD)?
Practitioners moving from data science notebooks into production ML on AWS. Software engineers crossing into ML engineering roles at AWS-first companies The credential is most useful when paired with a real portfolio of work on the platform.
How does the AWS Certified Machine Learning Engineer Associate (MLA-C01 current; MLA-C02 exam guide published, beta only, GA date TBD) compare to alternatives?
Practitioners typically choose between AWS Certified Machine Learning Engineer Associate (MLA-C01 current; MLA-C02 exam guide published, beta only, GA date TBD) and gcp-professional-ml-engineer or azure-ai-engineer-associate. Pick the credential matched to your target employer's primary cloud or governance stack. Studying for one credential builds 60 to 70 percent of the conceptual ground for the others.
Is the AWS Certified Machine Learning Engineer Associate (MLA-C01 current; MLA-C02 exam guide published, beta only, GA date TBD) worth it for a job search?
Practitioner-tier credentials carry hiring weight when the resume is otherwise platform-aligned. The AWS Certified Machine Learning Engineer Associate (MLA-C01 current; MLA-C02 exam guide published, beta only, GA date TBD) validates that the candidate has worked at production depth on Amazon Web Services tooling, not read about it.
Practice this exam
- AWS Certified Machine Learning Engineer AssociateScenario practice for the AWS Certified Machine Learning Engineer Associate exam, one domain at a time, with the primary source cited after every answer. Built against the published MLA-C02 exam guide. AWS offers MLA-C02 only as an English-only beta so far; its general-availability date, price and pass rule are not announced.
Methodology
This guide reflects DecipherU's standard certification intelligence workflow grounded in official certifying body documentation, publicly listed exam pricing, and independent practitioner sourcing. All details verified against the Amazon Web Services certification page on 2026-09-26.
Certification details are sourced from official certifying body websites. Verify current pricing, exam format, and requirements directly with the certifying organization before making decisions. DecipherU is not affiliated with any certifying body.