AWS Certified Machine Learning - Specialty (MLS-C01) Exam

Years of scikit-learn experience did not prepare me for AWS-specific services. Drilling SageMaker endpoint config and hyperparameter tuning here made the actual exam feel familiar.

I'm a data analyst moving into ML engineering. The practice questions around feature engineering and model evaluation showed me exactly where my gaps were.

Solid practice set overall. The algorithm-selection scenarios felt realistic, though I wanted more depth on the MLOps domain. Still passed, so I'll take it.

Coming from a software background, the data engineering domain - Kinesis, Glue, and S3 pipelines - was where I kept stumbling. These questions forced me to actually learn those services.

SageMaker finally clicked. Passed on my first attempt.

The MLS-C01 covers a lot of ground - algorithms, deployment, monitoring, and AWS-specific tooling all in one exam. I found the SageMaker sections genuinely challenging and the practice sets here reflected that difficulty well. Worth the time investment.