WGU D685 COMPREHENSIVE FINAL TEST
2026 TESTED QUESTIONS GRADED A+
⫸ narrow AI. Ans: artificial intelligence that is designed and trained
for a specific task or narrow set of tasks
⫸ general AI. Ans: a hypothetical future AI system that would
possess human-level intelligence
⫸ algorithms. Ans: defined methods or processes employed to train
models, generate predictions, and execute tasks using data
⫸ machine learning. Ans: a branch of AI that enables computers to
improve their performance through experience without needing
explicit programming
⫸ AI model. Ans: a computer program designed to make predictions
or decisions based on input data
⫸ supervised learning. Ans: a technique where a model is trained
using data that includes labeled examples, such as images with tagged
objects or text with marked entities
⫸ unsupervised learning. Ans: a type of machine learning where the
model is trained on unlabeled data without explicit guidance or
supervision
,⫸ reinforcement learning. Ans: a type of machine learning wherein
an AI agent learns through interactions with an environment,
garnering rewards or penalties contingent upon its actions
⫸ neural networks. Ans: computational models inspired by the
structure and function of the human brain's neural networks that learn
from data called training to recognize patterns, make predictions, and
perform tasks such as classification, regression, and pattern
recognition
⫸ deep learning. Ans: a powerful subset of machine learning that
uses artificial neural networks to learn from large amounts of data
⫸ generative AI. Ans: AI systems that can create new content
⫸ large language models (LLMs). Ans: a type of machine learning
model that is trained on massive amounts of text data to understand
and generate human-like language
⫸ natural language processing (NLP). Ans: the field of AI
concentrated on enabling computers to understand and engage with
human language, mirroring the intricacies of human communication
⫸ chatbots. Ans: AI programs designed to engage in natural
conversations with people, providing information, answering
questions, and even offering emotional support
, ⫸ computer vision. Ans: a field of artificial intelligence that enables
computers to interpret and analyze visual information from the real
world, such as images and videos
⫸ robotics. Ans: the field of AI that focuses on designing,
constructing, and operating robots
⫸ statistical analysis. Ans: a technique employed in AI that involves
collecting, organizing, examining, and interpreting data to identify
patterns and make predictions
⫸ AI tools. Ans: software programs designed to assist users in
performing AI-related tasks
⫸ Machine learning. Ans: a key component of AI that enables
computers to learn and improve without being explicitly programmed
by humans.
⫸ Algorithms. Ans: specific procedures or methods used to train
models, make predictions, and perform tasks based on data.
⫸ Supervised learning. Ans: a machine learning technique where a
model is trained on labeled data, such as images with identified
objects or text with labeled entities.
2026 TESTED QUESTIONS GRADED A+
⫸ narrow AI. Ans: artificial intelligence that is designed and trained
for a specific task or narrow set of tasks
⫸ general AI. Ans: a hypothetical future AI system that would
possess human-level intelligence
⫸ algorithms. Ans: defined methods or processes employed to train
models, generate predictions, and execute tasks using data
⫸ machine learning. Ans: a branch of AI that enables computers to
improve their performance through experience without needing
explicit programming
⫸ AI model. Ans: a computer program designed to make predictions
or decisions based on input data
⫸ supervised learning. Ans: a technique where a model is trained
using data that includes labeled examples, such as images with tagged
objects or text with marked entities
⫸ unsupervised learning. Ans: a type of machine learning where the
model is trained on unlabeled data without explicit guidance or
supervision
,⫸ reinforcement learning. Ans: a type of machine learning wherein
an AI agent learns through interactions with an environment,
garnering rewards or penalties contingent upon its actions
⫸ neural networks. Ans: computational models inspired by the
structure and function of the human brain's neural networks that learn
from data called training to recognize patterns, make predictions, and
perform tasks such as classification, regression, and pattern
recognition
⫸ deep learning. Ans: a powerful subset of machine learning that
uses artificial neural networks to learn from large amounts of data
⫸ generative AI. Ans: AI systems that can create new content
⫸ large language models (LLMs). Ans: a type of machine learning
model that is trained on massive amounts of text data to understand
and generate human-like language
⫸ natural language processing (NLP). Ans: the field of AI
concentrated on enabling computers to understand and engage with
human language, mirroring the intricacies of human communication
⫸ chatbots. Ans: AI programs designed to engage in natural
conversations with people, providing information, answering
questions, and even offering emotional support
, ⫸ computer vision. Ans: a field of artificial intelligence that enables
computers to interpret and analyze visual information from the real
world, such as images and videos
⫸ robotics. Ans: the field of AI that focuses on designing,
constructing, and operating robots
⫸ statistical analysis. Ans: a technique employed in AI that involves
collecting, organizing, examining, and interpreting data to identify
patterns and make predictions
⫸ AI tools. Ans: software programs designed to assist users in
performing AI-related tasks
⫸ Machine learning. Ans: a key component of AI that enables
computers to learn and improve without being explicitly programmed
by humans.
⫸ Algorithms. Ans: specific procedures or methods used to train
models, make predictions, and perform tasks based on data.
⫸ Supervised learning. Ans: a machine learning technique where a
model is trained on labeled data, such as images with identified
objects or text with labeled entities.
