AWS Certified Machine Learning Engineer - Associate
Build, deploy, and maintain machine learning solutions in the AWS Cloud for business problems.
Exam Topics
Data preparation for ML
ML model development
Deployment and orchestration of ML workflows
ML solution monitoring, maintenance, and security
Prerequisites
1+ years AWS ML/AI experience
Our Preparation Approach
Structured Curriculum
Aligned with latest exam objectives and updated for current exam patterns
Hands-On Labs
Practical exercises using real cloud environments and enterprise scenarios
Practice Exams
Mock exams modeled on real questions with detailed answer explanations
Expert Guidance
Learn from a trainer with 16+ active certifications and 98% student pass rate
Frequently Asked Questions
What is the MLE-C01 AWS Certified Machine Learning Engineer - Associate certification?
Build, deploy, and maintain machine learning solutions in the AWS Cloud for business problems.
How long is the MLE-C01 exam?
The MLE-C01 exam duration is 170 minutes. The passing score is 720/1000. The exam fee is $150 USD.
What topics does the MLE-C01 exam cover?
The MLE-C01 exam covers: Data preparation for ML; ML model development; Deployment and orchestration of ML workflows; ML solution monitoring, maintenance, and security.
What are the prerequisites for MLE-C01?
Prerequisites include: 1+ years AWS ML/AI experience.
How long is the MLE-C01 certification valid?
The MLE-C01 certification is valid for 3 years.
Does Gennoor Tech offer MLE-C01 preparation training?
Yes, we offer expert-led MLE-C01 preparation with hands-on labs, practice exams, and personalized guidance. Our trainer holds 16+ active certifications with a 98% student pass rate across all exams.
Other AWS Certifications
AWS Certified Cloud Practitioner
Validate overall understanding of the AWS Cloud, independent of specific technical roles.
AWS Certified AI Practitioner
Validate knowledge of AI, machine learning, and generative AI concepts and use cases on AWS.
AWS Certified Machine Learning - Specialty
Design, implement, deploy, and maintain machine learning solutions for given business problems.
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