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Test your knowledge with 50+ questions from the Solution and Data Monitoring section of the Databricks Certified Machine Learning Professional certification. Find out if you’re ready to ace the exam — can you compare and contrast label drift and feature drift, identify scenarios in which feature or label drift are likely to occur, explain concept drift and its impact on model efficacy, describe summary statistic monitoring as a simple solution for numeric feature drift, explain how mode, unique values, and missing values serve as simple solutions for categorical feature drift, compare tests as more robust monitoring solutions for numeric feature drift than simple summary statistics, compare tests as more robust monitoring solutions for categorical feature drift than simple summary statistics, compare and contrast Jensen–Shannon divergence and Kolmogorov–Smirnov tests for numerical drift detection, identify a scenario in which a chi-square test would be useful, describe the common workflow for measuring concept drift and feature drift, determine when retraining and deploying an updated model is a probable solution to drift, and test whether the updated model performs better on more recent data? And much more!

This intensive DataAI (formerly named DataX) exam survival guide is built to help you master the core concepts, technical competencies, and analytical thinking skills required to pass the DataAI exam with confidence.

Building a data pipeline is one thing. Engineering an enterprise-grade data platform that is performant, reliable, and secure at scale is another. This is the next level of data engineering.

Build, Connect, and Launch a Complete AI App — From Local Code to Live Cloud!

Code in JavaScript. Develop Non-fungible tokens on the NEAR blockchain!