Show you can work with data on Google Cloud, from ingesting and analyzing it with BigQuery and Looker to managing access, and track your readiness for the Associate Data Practitioner exam.

Fundamental

Prepare and test your skills

Fundamental

Prepare and test your skills

Concept

model

Topic in 4 exam domains

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model · Concept
Model · Concept
Model · Feature · App Engine NDB
MODEL · Concept
model · Feature · AML AI

Also called: AML AI models, BigQuery ML model, data model, engine models, ML models, Model class, ndb.Model, recommendations model

A model is a trained machine learning resource contained and managed within a BigQuery dataset or deployed to an endpoint to process data and serve predictions. On Associate Data Practitioner it comes up as a resource you train, evaluate, and query for predictions using SQL, as well as organize across lifecycle stages.

What you can expect on the exam

Training and evaluating models in BigQuery datasets. Be ready to train a model directly within a BigQuery dataset using SQL and evaluate performance metrics such as accuracy or mean squared error before putting it into production.
Generating predictions and inference. Expect to execute SQL queries against a trained model to generate predictions, batch inference, or time-series forecasts on new datasets.
Model governance and versioning. You may need to manage model metadata, track versioning, and assign mutable aliases to designate lifecycle stages such as staging or production to control promotion.

Where this appears on the exam

4 subdomains in 1 of 4 domains

Section 2
Data Analysis and Presentation
1. 2.2Visualize data and create dashboards in Looker given business requirements
  - Manipulate simple LookML parameters to modify a data model
2. 2.3Define, train, evaluate, and use ML models

How learners score on this topic

Last updated November 2, 2026

Associate Data Practitioner

Show you can work with data on Google Cloud, from ingesting and analyzing it with BigQuery and Looker to managing access, and track your readiness for the Associate Data Practitioner exam.

Fundamental

Prepare and test your skills

Fundamental

Prepare and test your skills

Concept

model

Topic in 4 exam domains

X LinkedIn Facebook Reddit

model · Concept
Model · Concept
Model · Feature · App Engine NDB
MODEL · Concept
model · Feature · AML AI

Also called: AML AI models, BigQuery ML model, data model, engine models, ML models, Model class, ndb.Model, recommendations model

What you can expect on the exam

Training and evaluating models in BigQuery datasets. Be ready to train a model directly within a BigQuery dataset using SQL and evaluate performance metrics such as accuracy or mean squared error before putting it into production.
Generating predictions and inference. Expect to execute SQL queries against a trained model to generate predictions, batch inference, or time-series forecasts on new datasets.
Model governance and versioning. You may need to manage model metadata, track versioning, and assign mutable aliases to designate lifecycle stages such as staging or production to control promotion.

Where this appears on the exam

4 subdomains in 1 of 4 domains

Section 2
Data Analysis and Presentation
1. 2.2Visualize data and create dashboards in Looker given business requirements
  - Manipulate simple LookML parameters to modify a data model
2. 2.3Define, train, evaluate, and use ML models

How learners score on this topic

Last updated November 2, 2026

What you can expect on the exam

Where this appears on the exam

Related topics

How learners score on this topic

What you can expect on the exam

Where this appears on the exam

Related topics

How learners score on this topic