Description
AWS Certified Machine Learning Specialty – Hands-On + Exams prepares learners to design, build, deploy, and operate machine learning solutions on AWS while aligning fully with the MLS-C01 certification syllabus. The training blends theory, hands-on labs, and practice questions to cover the entire ML lifecycle using AWS services.
You will work with real AWS tools such as Kinesis, Glue, EMR, and SageMaker to create scalable data pipelines, train and optimize models, and deploy secure production-ready ML systems. The content follows AWS best practices for security, monitoring, and MLOps, enabling learners to gain both certification readiness and real-world implementation skills.
What You’ll Learn
- Design scalable ML data pipelines using AWS analytics and streaming services
- Train, tune, and evaluate machine learning models with Amazon SageMaker
- Deploy ML solutions using AWS security, IAM, VPC, and encryption best practices
- Implement monitoring, A/B testing, automated retraining, and ML operations workflows
Who This Is For
- Data scientists and machine learning engineers
- Cloud architects and AWS professionals
- Developers transitioning into MLOps roles
- Learners preparing for the AWS Machine Learning Specialty certification
Requirements
- Associate-level knowledge of AWS services such as EC2
- Basic familiarity with machine learning concepts
- An AWS account for hands-on labs
Rapidgator
File Size: 14.19 GB