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The Databricks Certified Machine Learning Professional certification exam assesses an individual’s ability to design, implement, and manage enterprise-scale machine learning solutions using advanced Databricks platform capabilities. This includes proficiency in building scalable ML pipelines with SparkML, implementing distributed training and hyperparameter tuning, leveraging advanced MLflow features, and utilizing Feature Store concepts for automated feature pipelines. The certification exam evaluates expertise in MLOps practices, including testing strategies, environment management with Databricks Asset Bundles, automated retraining workflows, and monitoring using Lakehouse Monitoring for drift detection. Additionally, test-takers are assessed on their ability to implement deployment strategies, custom model serving, and model rollout management. Individuals who pass this certification exam can be expected to perform advanced machine learning engineering tasks at enterprise scale, implementing production-ready ML systems with comprehensive monitoring, testing, and deployment practices using the full feature set of Databricks.
This exam covers:
• Model Development – 44%
• ML Ops – 44%
• Model Deployment – 12%
