Data preparation, model training with SageMaker, deployment, MLOps and AWS AI/ML services.
Program: Data & AIMachine Learning covers the full lifecycle on AWS: preparing data and engineering features, training models with SageMaker, deploying and operating them with MLOps practices, and using AWS AI/ML services.
The final module focuses on exam preparation.
Who it's for: Data scientists, ML engineers and developers building and deploying machine-learning workloads on AWS.
Prerequisites: Experience with machine learning concepts and AWS. AWS has been evolving its ML certifications (including Machine Learning Engineer - Associate), so confirm the current exam status on AWS's site.
Organisations want repeatable, monitored model pipelines rather than one-off experiments.
Managed services reduce the effort of training and hosting models.
Bias, explainability and governance are now part of the delivery process.
Teams combine traditional models with foundation models in the same platforms.
This class follows the four ML domains and ends with exam preparation. Because AWS updates its ML certification lineup, check the current exam and choose the credential that matches your target role.
No classes are scheduled for this course yet.
Exam codes, objectives and availability are set by each vendor and change over time. Please confirm current details on the vendor's official certification page before booking an exam. Transformed Man Academy is an independent training provider. Product and certification names are trademarks of their respective owners.