Databricks Machine Learning Associate deep review — September 28, 2026

Read the full guide and all 48 detailed objectives in the still-linked March 1, 2025 PDF. Four weighted domains and lifecycle snapshots are unchanged. Preserve the live page's delivery metadata and the existing explanation of older PDF wording; no accepted snapshots were rewritten. Vendor sample questions were not reproduced.

Supported learning changes

The AutoML reference now supplies a concrete environment boundary. Hyperparameter guidance separates the legacy exam requirement from current runtime choices. Added feature key/observation-time decisions and clarified that registry alias changes require deliberate loading or serving deployment actions.

The guide includes an original synthetic scikit-learn pipeline, fold-local preprocessing and a four-candidate tuning exercise. Four worked decisions and ten answers cover temporal leakage, precision/recall, feature uniqueness and version rollout. The historical MLOps Gym article contributes an entity/time/label worksheet; its code and current API compatibility were not endorsed.

Execution evidence and limits

Executed the guide's three assertions plus 19 additional checks in an isolated local environment using NumPy 2.5.3 and scikit-learn 1.9.1. Confirmed the held-out extreme value does not change the fitted training median, demonstrated a leaking negative control, verified fold-specific medians and confusion-matrix calculations, and instrumented nine search fits (eight validation fits plus refit). Also checked inverse target transform and unknown-category handling.

No Spark, Hyperopt or Databricks service was executed. All eight workspace labs remain proposed, and human review is pending. Signed-in course contents remain unavailable; public Whizlabs content was unusable and Udemy blocked access. Planning durations remain qualified estimates. Detailed objective hashes, source access results and local package versions are preserved in the operational receipt.