AWS Certified Machine Learning – Specialty
Validate your skills in building, deploying, and maintaining machine learning solutions on AWS. The exam covers Data Engineering, Exploratory Data Analysis, Modeling, and ML Implementation & Operations.
About This Certification
Overview When it comes to providing cloud-based services for worldwide organizations, Amazon Web Services is the industry leader. As more firms begin to recognize AWS-certified specialists and professionals, the number of persons seeking AWS certifications has steadily increased.
What Makes Our Program Different
| Feature | Our Program | Competitors |
|---|---|---|
| Exam Alignment | Fully mapped to AWS ML – Specialty blueprint | Partial exam coverage |
| ML Lifecycle Focus | Data prep → modeling → deployment → monitoring | Model-only learning |
| AWS ML Services | SageMaker, Rekognition, Comprehend, Forecast | Tool overview only |
| Data Engineering | Feature engineering & pipeline design | Limited data handling |
| Hands-On Practice | End-to-end ML use-case labs | Theoretical exercises |
| Exam Preparation | Scenario-based mocks & expert guidance | Basic question sets |
How Certification Transforms Careers
End-to-End Machine Learning on AWS
Learn to build, train, tune, and deploy machine learning models using AWS services with a strong focus on real business use cases.
Advanced Data Engineering & Feature Design
Master data preparation, feature engineering, and scalable ML pipelines using AWS data services and best practices.
Model Deployment, Monitoring & Optimization
Deploy ML models securely, monitor performance, manage drift, and optimize cost and accuracy in production environments.
Specialty-Level Exam Readiness
Prepare with complex ML scenarios, architecture-based questions, and deep-dive exam strategies tailored to the AWS ML Specialty certification.
- Build, deploy, and maintain ML solutions on AWS.
- Perform data preparation, feature engineering, and modeling.
- Apply ML operational best practices on AWS.
- Prepare for the AWS Machine Learning Specialty exam.
Exam Format and Information
|
Exam Name |
AWS Certified Machine Learning – Specialty |
|
Exam Code |
MLS-C01 |
|
Exam Duration |
170 Minutes |
|
Format |
Multiple Choice and Multiple Answer Type Exam |
|
Passing Score |
75-80% |
|
Number of Questions |
65 |
|
Exam Fee |
$300 |
|
Pre-requisite |
None |
|
Languages |
English, Japanese, Korean, and Simplified Chinese |
|
Validity |
3 years |
Prospects for Salary for Machine Learning Certified Professionals
Machine Learning, along with AI, is now proving to be a critical strategic effort for businesses all over the world. Regardless of the size or kind of company, ML and AI are being gradually integrated to develop a key understanding of the technology and how it can be utilized to construct resilient processes with little human intervention to avoid mistakes. Machine Learning certification credentials are quite popular nowadays, as firms undergo huge transformations by embracing all of the newest emerging technologies in order to remain relevant in a competitive market. Let’s have a look at the wages of Machine Learning trained experts from across the world.
|
United States |
USD 108,000 to USD 151,000 |
|
United Kingdom |
Pounds 35,000 to 110,000 |
|
India |
Rupees 5 lakhs to 15 lakhs |
|
Australia |
AUD 59,000 to 130,000 |
|
UAE |
AED 200,000 to 352,000 |
|
Singapore |
SGD 68,000 to 110,000 |
What Our RCDD Graduates Say
Ethan Marshall
Machine Learning Engineer
“This training connected ML theory with real AWS implementation. The SageMaker labs were extremely practical.”
Ritika Sharma
Data Scientist
“The focus on data pipelines and model deployment helped me understand how ML works at scale on AWS.”
Lucas Bennett
AI Solutions Architect
“The scenario-based exam preparation matched the Specialty exam level perfectly. It sharpened both my ML and AWS architecture skills.”