Machine Learning with Amazon SageMaker
Develop practical, source-aligned skills in end-to-end machine-learning development with Amazon SageMaker through structured explanations, guided implementation, security and operational review, troubleshooting, and applied validation.
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-by SkillDynamo
- 0 Students
- Last updated
Course Description
SkillDynamo’s Machine Learning with Amazon SageMaker training develops practical, source-aligned skills in end-to-end machine-learning development with Amazon SageMaker.
The 16 Hours curriculum is independently rewritten into four structured lessons. Learners progress from foundations and use-case analysis to implementation, security, operations, troubleshooting, applied validation, and best-practice review.
What You Will Learn
- SageMaker architecture and machine-learning workflow
- Data access, preparation, and feature engineering
- Built-in algorithms and framework options
- Training jobs and experiment management
- Hyperparameter tuning and model evaluation
- Model deployment and endpoint configuration
SkillDynamo Training Approach
Instructor-guided explanations, AWS service or workflow mapping, hands-on planning activities, scenario analysis, validation checklists, troubleshooting discussions, and a final improvement roadmap.
Curriculum
- 1 Section
- 4 Lessons
- 16 Hours
Your Instructors
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