CERTALYTH Certified ML & MLOps Professional

CCML-P · CT-MLOPS-P · Machine Learning and MLOps on Google Cloud

Build and operationalize ML models on Google Cloud.

Google Cloud Professional Machine Learning Engineer

40 hoursCertificate with unique codeMultiple-choice exam

349EUR

Full bundle: course PDF + online exam + certification.

Recertification every 3 years: 99 EUR

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About the course

Learn to develop, train, and operationalize machine learning models on Google Cloud using Vertex AI and modern MLOps practices. Aligned with the Google Cloud Professional Machine Learning Engineer exam.

Focus: ML and MLOps on GCP: Vertex AI, pipelines, deployment, and monitoring.

What you'll learn

Train and evaluate models with Vertex AI

Build automated MLOps pipelines

Deploy and scale models in production

Monitor model performance and drift

Sample questions (free)

A sample from the official exam set — correct answers are revealed only during the actual exam.

CERTALYTH Certified ML & MLOps Professional

About the course

What you'll learn

Sample questions (free)

A product team needs image classification for a proprietary dataset of 10k labeled images. They require good accuracy but have limited ML engineering resources and little desire to write custom training code. Which approach best balances accuracy and low engineering effort?

You need to implement a scalable ETL pipeline that processes streaming click events, performs windowed aggregations, and writes feature tables for model training. Which Google Cloud tool is the most appropriate choice?

A fraud-detection model needs real-time features (e.g., recent transaction count) at prediction time and also needs historical feature values for offline training. What is the best design pattern for feature storage and serving?