ARTIFICIAL INTELLIGENCE ENGINEER
CERTIFICATION 2026 EXAM SCRIPT TEST
PAPER QUESTIONS AND SOLUTIONS GRADED
A+
◉ Machine Learning.
Answer: AutoML, Vertex AI Workbench and TF align to which stage
of the data-to-AI workflow?
◉ Ingestion and Process.
Answer: Pub/Sub, Dataflow, Dataproc and Cloud Data fusion align to
which stage of the data-to-AI workflow?
◉ Archive storage.
Answer: Which data storage class is best for storing data that needs
to be accessed less than once a year, such as online backups and
disaster recovery?
◉ Database and storage.
Answer: Cloud storage, coud bigtable, cloud sql, cloud spanner and
firestone represent which type of services?
,◉ TPU (Tensor Processing Units).
Answer: Which Google hardware innovation tailors architecture to
meet the computation needs on a domain such as the matrix
multiplication in ML
◉ Volume.
Answer: refers to the amount of data that exists
◉ Velocity.
Answer: refers to how quickly data is generated and how quickly
that data moves
◉ Variety.
Answer: refers to diversity of data types
◉ Veracity.
Answer: refers to the quality and accuracy of data
◉ Value.
Answer: refers to the value that big data can provide and related
directly to what organizations can do with that collected data
◉ Volume.
,Answer: Due to several data types and sources, big data often has
many data dimensions. This can introduce data inconsistencies and
uncertainties. Which type of challenge might this present to data
engineers?
◉ Velocity.
Answer: When you build scalable and reliable pipelines, data often
needs to be processed in near-real time, as soon as it reaches the
system which type of challenge might this present to data engineers.
◉ Pub/Sub.
Answer: Which google cloud product is distributed messaging
service that is designed to ingest messages from multiple device
streams such as gaming events, IoT devices and application streams?
◉ 1. Ingest streaming results,
2. Process data
3. Visualize results.
Answer: Streaming data workflow steps
◉ Dataflow.
Answer: Which google cloud products acts as an execution engine to
process and implement data processing pipelines?
, ◉ Storage and Analytics.
Answer: What two services does BQ provide?
◉ Create ML model inside BQ.
Answer: Data has been loaded into BQ, and the features have been
selected and preprocessed. What should happen next when you use
BQML to develop a machine learning model?
◉ BQ manages the underlying structure.
Answer: BQ is a fully managed data warehouse, what does fully
managed refer to?
◉ Unsupervised learning, cluster analysis.
Answer: You want to use machine learning to group random photos
into similar groups what do you use?
◉ Batch Load.
Answer: Which pattern describes source data that is moved into BQ
table in a single operation?
◉ Supervised learning, logistic regression.
Answer: You want to use ML to identify whether an email is spam.
Which should you use?
CERTIFICATION 2026 EXAM SCRIPT TEST
PAPER QUESTIONS AND SOLUTIONS GRADED
A+
◉ Machine Learning.
Answer: AutoML, Vertex AI Workbench and TF align to which stage
of the data-to-AI workflow?
◉ Ingestion and Process.
Answer: Pub/Sub, Dataflow, Dataproc and Cloud Data fusion align to
which stage of the data-to-AI workflow?
◉ Archive storage.
Answer: Which data storage class is best for storing data that needs
to be accessed less than once a year, such as online backups and
disaster recovery?
◉ Database and storage.
Answer: Cloud storage, coud bigtable, cloud sql, cloud spanner and
firestone represent which type of services?
,◉ TPU (Tensor Processing Units).
Answer: Which Google hardware innovation tailors architecture to
meet the computation needs on a domain such as the matrix
multiplication in ML
◉ Volume.
Answer: refers to the amount of data that exists
◉ Velocity.
Answer: refers to how quickly data is generated and how quickly
that data moves
◉ Variety.
Answer: refers to diversity of data types
◉ Veracity.
Answer: refers to the quality and accuracy of data
◉ Value.
Answer: refers to the value that big data can provide and related
directly to what organizations can do with that collected data
◉ Volume.
,Answer: Due to several data types and sources, big data often has
many data dimensions. This can introduce data inconsistencies and
uncertainties. Which type of challenge might this present to data
engineers?
◉ Velocity.
Answer: When you build scalable and reliable pipelines, data often
needs to be processed in near-real time, as soon as it reaches the
system which type of challenge might this present to data engineers.
◉ Pub/Sub.
Answer: Which google cloud product is distributed messaging
service that is designed to ingest messages from multiple device
streams such as gaming events, IoT devices and application streams?
◉ 1. Ingest streaming results,
2. Process data
3. Visualize results.
Answer: Streaming data workflow steps
◉ Dataflow.
Answer: Which google cloud products acts as an execution engine to
process and implement data processing pipelines?
, ◉ Storage and Analytics.
Answer: What two services does BQ provide?
◉ Create ML model inside BQ.
Answer: Data has been loaded into BQ, and the features have been
selected and preprocessed. What should happen next when you use
BQML to develop a machine learning model?
◉ BQ manages the underlying structure.
Answer: BQ is a fully managed data warehouse, what does fully
managed refer to?
◉ Unsupervised learning, cluster analysis.
Answer: You want to use machine learning to group random photos
into similar groups what do you use?
◉ Batch Load.
Answer: Which pattern describes source data that is moved into BQ
table in a single operation?
◉ Supervised learning, logistic regression.
Answer: You want to use ML to identify whether an email is spam.
Which should you use?
