AWS Certified Machine Learning Engineer
Designing, Deploying, and Operating Machine Learning Solutions on AWS
(includes training and materials)
Training Delivery Mode:
- Physical Classroom
- Live Virtual Training
Course Overview
The AWS Certified Machine Learning Engineer course is a professional, hands-on training programme designed to equip learners with the skills required to build, deploy, orchestrate, and maintain machine learning solutions using Amazon Web Services (AWS).
This course focuses on the end-to-end machine learning lifecycle, from data preparation and model development to deployment, monitoring, and security. Participants will gain practical experience working with AWS machine learning and data services, learning how to design scalable, secure, and production-ready ML solutions aligned with industry best practices.
The programme is aligned with AWS’s official certification blueprint and prepares participants for the AWS Certified Machine Learning Engineer – Associate (MLA-C01) certification exam.
Course Module
- Data Preparation for Machine Learning (ML)
- ML Model Development
- Deployment and Orchestration of ML Workflows
- ML Solution Monitoring, Maintenance, and Security
What You Will Learn
By the end of this course, participants will be able to:
- Prepare, clean, and transform data for machine learning on AWS
- Design and develop machine learning models using AWS services
- Deploy and orchestrate end-to-end ML workflows
- Implement scalable and automated ML pipelines
- Monitor, maintain, and optimise ML solutions in production
- Apply security and governance best practices for ML workloads
- Prepare confidently for the AWS Machine Learning Engineer certification exam
Who This Course Is For
This course is ideal for professionals seeking to build or advance machine learning engineering skills on AWS, including:
- Aspiring and practicing Machine Learning Engineers
- Data Scientists transitioning into cloud-based ML roles
- Software Engineers building ML-enabled applications
- Cloud Engineers and Architects
- Data Engineers supporting ML pipelines
- Professionals preparing for AWS Machine Learning certification
Prior experience with Python, basic machine learning concepts, and AWS fundamentals is recommended.
Career Benefits
Participants who complete this course will be able to:
- Build and operate production-grade ML solutions on AWS
- Support enterprise AI and ML initiatives
- Advance into roles such as Machine Learning Engineer or Cloud ML Engineer
- Strengthen technical portfolios with AWS-based ML projects
- Increase employability through AWS-recognised certification
Tools, Frameworks, Or Standards Covered
- Amazon Web Services (AWS)
- AWS ML and data services (e.g., SageMaker, data pipelines)
- ML lifecycle management best practices
- Security and governance for ML workloads
Certification
Participants who successfully complete the course will receive:
Certificate of Completion in AWS Certified Machine Learning Engineer
Issued by SCILS Management Centre
Participants will also be prepared for:
AWS Certified Machine Learning Engineer – Associate (MLA-C01)