MLOps Engineering on AWS
Design and operate repeatable machine learning delivery pipelines using AWS services for experimentation, automation, deployment, and monitoring.
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-by SkillDynamo
- 0 Students
- Last updated
Course Description
SkillDynamo’s MLOps Engineering on AWS training develops practical, source-aligned skills for design and operate repeatable machine learning delivery pipelines using AWS services for experimentation, automation, deployment, and monitoring.
The 24 Hours curriculum is independently rewritten into four structured lessons. Learners move from essential concepts to implementation, secure operations, troubleshooting, applied scenarios, and solution validation.
What You Will Learn
- MLOps principles and lifecycle
- Data and feature pipeline design
- Experiment tracking and reproducibility
- SageMaker projects and environments
- Automated training pipelines
- Model validation and approval gates
Training Approach
Instructor-guided explanations, AWS service mapping, practical configuration or design activities, scenario analysis, validation checklists, and a final improvement plan.
Curriculum
- 1 Section
- 4 Lessons
- 24 Hours
SkillDynamo Expert Team
SkillDynamo Expert Team
Instructor-led delivery focused on the source-aligned scope of MLOps Engineering on AWS, with practical AWS service mapping, scenarios, validation, and troubleshooting.
- Structured explanations and demonstrations
- Applied exercises and design reviews
- Course-specific validation and improvement guidance
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