Free GCP ML Engineer Exam Prep

BigQuery ML and Agent Platform AutoML models, Gemini tuning in BigQuery, Google Cloud AI APIs, Model Garden model selection, and Gemini cost, latency, and availability.

Data exploration and preprocessing, Feature Store, PII protection, Workbench and Colab Enterprise notebooks, experiments, lineage, and predictive and gen AI evaluation.

Model type and product choice, interpretability, training data, custom training, Kubeflow on GKE, Tabular Workflows, troubleshooting, tuning, and CPU, GPU, and TPU hardware.

Batch and online inference, Model Garden, Cloud Run, and GKE serving, containers, Model Registry, rollouts, endpoints, autoscaling, and production optimization.

Data and model validation, Agent Platform Pipelines, Managed Service for Apache Airflow, Ray on Agent Platform, consistent preprocessing, retraining policy, and CI/CD/CT.

Model Armor, safety filters, exfiltration controls, bias monitoring, explainability, Model Monitoring, skew and drift, and gen AI monitoring and evaluation.