AWS Certified Machine Learning Engineer - Associate

Teams often cite this credential when documenting who is trained to handle machine learning workloads on AWS, including IAM access control and network isolation for ML resources. CBT Nuggets team reporting provides per-learner progress, completion and completion exports that IT leaders can use as audit evidence, while the auditor's control crosswalk decides how the certification maps to a formal framework.

It suits the cloud, data and DevOps engineers who will build and run ML workloads on AWS. The linked course prepares them to own data preparation with AWS Glue and Glue DataBrew, streaming data ingestion, SageMaker domain setup, labeling and data augmentation, and feature stores. It also covers framing business problems as ML tasks, training with SageMaker built-in algorithms, and tuning models with SageMaker JumpStart and hyperparameter tuning, all inside IAM-secured, network-isolated environments.

CBT Nuggets AWS Certified Machine Learning Engineer - Associate courses are built by named expert trainers. Where a course includes hands-on virtual labs or a practice exam mapped to AWS's published exam objectives, the course list on this page says so. Team admin reporting tracks assignment, completion and exam readiness per engineer — the view managers use to run a team training program.

From the admin console, managers assign the AWS Certified Machine Learning Engineer - Associate courses directly to specific engineers or role groups and track completion and practice-exam scores per learner. Team-wide reporting rolls up to a single dashboard you can review or export for leadership reviews or compliance reporting.

The linked CBT Nuggets training totals about 24 hours of video. Actual time to certify depends on each engineer's starting point with AWS data services and SageMaker, and team reporting lets IT leaders track course completion across the group before exams are scheduled.

CBT Nuggets updates AWS course content as exam objectives refresh, and this page shows the current exam's status and any retirement date the vendor has announced. When AWS restructures or renames a track, the assigned training stays aligned with the same team training plan, and the training stays current without anyone losing their progress mid-stream.