How to get AWS Machine Learning Specialty
Specialty · AWS
The AWS MLS-C01 exam tests your ability to design, implement, and monitor machine learning solutions on AWS. Prepare with content focused on the SageMaker service family, ML pipelines, and data engineering.
About the exam
MLS-C01 · 65 questions · 180 minutes · 750/1000 passing score
What topics are covered?
Data Engineering
- • Data preparation with S3 and Glue
- • Feature Engineering
- • Data labeling strategies
Model Development
- • SageMaker Studio usage
- • Built-in algorithms
- • Hyperparameter tuning
Model Deployment
- • SageMaker endpoint configuration
- • Multi-model endpoints
- • A/B testing deployment
ML Pipeline
- • SageMaker Pipelines
- • MLflow integration
- • Model registry and approval workflow
Security & Monitoring
- • Drift detection with Model Monitor
- • Bias analysis with SageMaker Clarify
- • Model security with VPC
How to prepare with Cloudpuz
Prepare for AWS Machine Learning Specialty with 18 hands-on labs, realistic mock exams and a step-by-step path. Learn by doing and pass on the first try.
Start AWS Machine Learning Specialty prepFrequently asked questions
What is the AWS Machine Learning Specialty certification for?
AWS Machine Learning Specialty: The AWS MLS-C01 exam tests your ability to design, implement, and monitor machine learning solutions on AWS. Prepare with content focused on the SageMaker service family, ML pipelines, and data engineering. This Specialty certification is verified proof of skill for job applications and promotions.
What is the AWS Machine Learning Specialty exam like?
MLS-C01 · 65 questions · 180 minutes · 750/1000 passing score
How long does prep take?
With Cloudpuz's hands-on content, about 10 weeks and 18 hands-on labs.
Which topics are covered?
Data Engineering, Model Development, Model Deployment, ML Pipeline, Security & Monitoring.