Google Cloud Certified Generative AI Leader Test
It is a category of artificial intelligence that focuses on Generative AI
creating entirely new content, such as text, images, audio,
or code, based on patterns learned from large datasets.
It is a broad field of computer science that enables Artificial Intelligence (AI)
machines to perform tasks that normally require human
intelligence, such as reasoning, learning, and decision-
making.
It is a subset of artificial intelligence that allows systems to Machine Learning (ML)
learn from data and improve performance over time
without being explicitly programmed.
It is a large, pre-trained machine learning model that can Foundation Model
be adapted to a wide range of tasks with minimal
additional training.
It is a type of foundation model trained on vast amounts of Large Language Model (LLM)
text data to understand, generate, and reason using
natural language.
It is a machine learning model designed to produce new Generative Model
data outputs that resemble the patterns found in its training
data.
It is the collection of data used during the learning phase Training Data
to teach a machine learning model how to recognize
patterns and relationships.
It is the stage where a trained model applies learned Inference
patterns to new input data in order to generate predictions
or responses.
It is the set of internal values learned during training that Model Parameters
determine how a model processes inputs and generates
outputs.
It is data that is organized in a predefined format, such as Structured Data
tables with rows and columns, making it easy to store and
query.
It is data that does not follow a predefined format, such as Unstructured Data
free-form text, images, audio recordings, or video content.
It is data that contains some organizational structure but Semi-Structured Data
does not fit neatly into relational tables, such as JSON or
XML files.
It is a machine learning approach where models are Supervised Learning
trained using labeled datasets that include both inputs and
correct outputs.
It is a learning method where models identify patterns and Unsupervised Learning
relationships in data without relying on labeled examples.
It is a machine learning technique where a model learns by Reinforcement Learning
interacting with an environment and receiving rewards or
penalties.
, Google Cloud Certified Generative AI Leader Test
It is the complete process of developing machine learning Machine Learning Lifecycle
solutions, including data preparation, training, deployment,
and ongoing monitoring.
It is the phase in which a model learns from training data Model Training
by adjusting parameters to minimize errors.
It is the process of making a trained machine learning Model Deployment
model available for real-world use in applications or
services.
It is the continuous practice of tracking a deployed model's Model Monitoring
performance, behavior, and reliability over time.
It is the gradual decline in model performance caused by Model Drift
changes in data patterns or operating conditions.
It is Google Cloud's collection of tools, platforms, and Google Cloud Generative AI
services designed to support enterprise-grade generative
AI solutions.
It is Google's family of multimodal generative AI models Gemini
capable of understanding and generating text, images, and
other data types.
It is a generative AI offering that integrates AI assistance Gemini for Workspace
directly into Google Workspace productivity applications.
It is an enterprise-focused version of Gemini that includes Gemini Enterprise
enhanced security, privacy, and governance controls.
It is Google Cloud's managed platform that enables Vertex AI
organizations to build, deploy, and manage machine
learning models at scale.
It is a Vertex AI feature that provides access to a curated Model Garden
collection of pre-trained, open, and proprietary models.
It is a Google Cloud tool that allows organizations to create Agent Builder
conversational and task-oriented AI agents.
It is a technique that improves AI responses by retrieving Retrieval-Augmented Generation (RAG)
relevant external data at runtime and incorporating it into
model outputs.
It is the practice of ensuring AI-generated responses are Grounding
anchored to trusted and authoritative data sources.
A specialized database designed to store and efficiently Vector Database
search high-dimensional vector representations.
It is a category of artificial intelligence that focuses on Generative AI
creating entirely new content, such as text, images, audio,
or code, based on patterns learned from large datasets.
It is a broad field of computer science that enables Artificial Intelligence (AI)
machines to perform tasks that normally require human
intelligence, such as reasoning, learning, and decision-
making.
It is a subset of artificial intelligence that allows systems to Machine Learning (ML)
learn from data and improve performance over time
without being explicitly programmed.
It is a large, pre-trained machine learning model that can Foundation Model
be adapted to a wide range of tasks with minimal
additional training.
It is a type of foundation model trained on vast amounts of Large Language Model (LLM)
text data to understand, generate, and reason using
natural language.
It is a machine learning model designed to produce new Generative Model
data outputs that resemble the patterns found in its training
data.
It is the collection of data used during the learning phase Training Data
to teach a machine learning model how to recognize
patterns and relationships.
It is the stage where a trained model applies learned Inference
patterns to new input data in order to generate predictions
or responses.
It is the set of internal values learned during training that Model Parameters
determine how a model processes inputs and generates
outputs.
It is data that is organized in a predefined format, such as Structured Data
tables with rows and columns, making it easy to store and
query.
It is data that does not follow a predefined format, such as Unstructured Data
free-form text, images, audio recordings, or video content.
It is data that contains some organizational structure but Semi-Structured Data
does not fit neatly into relational tables, such as JSON or
XML files.
It is a machine learning approach where models are Supervised Learning
trained using labeled datasets that include both inputs and
correct outputs.
It is a learning method where models identify patterns and Unsupervised Learning
relationships in data without relying on labeled examples.
It is a machine learning technique where a model learns by Reinforcement Learning
interacting with an environment and receiving rewards or
penalties.
, Google Cloud Certified Generative AI Leader Test
It is the complete process of developing machine learning Machine Learning Lifecycle
solutions, including data preparation, training, deployment,
and ongoing monitoring.
It is the phase in which a model learns from training data Model Training
by adjusting parameters to minimize errors.
It is the process of making a trained machine learning Model Deployment
model available for real-world use in applications or
services.
It is the continuous practice of tracking a deployed model's Model Monitoring
performance, behavior, and reliability over time.
It is the gradual decline in model performance caused by Model Drift
changes in data patterns or operating conditions.
It is Google Cloud's collection of tools, platforms, and Google Cloud Generative AI
services designed to support enterprise-grade generative
AI solutions.
It is Google's family of multimodal generative AI models Gemini
capable of understanding and generating text, images, and
other data types.
It is a generative AI offering that integrates AI assistance Gemini for Workspace
directly into Google Workspace productivity applications.
It is an enterprise-focused version of Gemini that includes Gemini Enterprise
enhanced security, privacy, and governance controls.
It is Google Cloud's managed platform that enables Vertex AI
organizations to build, deploy, and manage machine
learning models at scale.
It is a Vertex AI feature that provides access to a curated Model Garden
collection of pre-trained, open, and proprietary models.
It is a Google Cloud tool that allows organizations to create Agent Builder
conversational and task-oriented AI agents.
It is a technique that improves AI responses by retrieving Retrieval-Augmented Generation (RAG)
relevant external data at runtime and incorporating it into
model outputs.
It is the practice of ensuring AI-generated responses are Grounding
anchored to trusted and authoritative data sources.
A specialized database designed to store and efficiently Vector Database
search high-dimensional vector representations.
