WGU D685 - Practical Applications of Prompt
Engineering Newest Exam 2026/2027 | All
Questions and Correct Detailed Answers |
Already Graded A | New and Revised
Key capabilities of LLM - ANSWERS-- Understanding and generating human-
like text
-Language translation
-Text summarization
-Question answering
-Content creation
-Conversational interactions (chatbots and virtual assistants)
-Rephrasing and rewriting text in different styles
Natural Language Processing (NLP) - ANSWERS-This field of AI is
concentrated on enabling computers to understand and
engage with human language, mirroring the intricacies of human
communication.
What are three applications of NLP in AI systems? - ANSWERS-Chatbots,
Sentiment Analysis, Language Translation
Chatbots - ANSWERS-AI programs that engage in natural conversations,
providing information and answering questions
Sentiment Analysis - ANSWERS-Determining the emotional tone or opinion
expressed in text (positive, negative, neutral)
, Language Translation - ANSWERS-Converting text or speech from one
language to another (Google Translate, real-time
translation services)
What are some other applications of NLP in AI systems? - ANSWERS-Other
applications include document summarization, text classification, and speech
recognition.
Narrow AI - ANSWERS-(weak AI) Designed for a specific task or a narrow set
of tasks. It excels at its designated purpose but cannot perform tasks outside
its programmed scope.
General AI - ANSWERS-a hypothetical future AI system that would possess
human-level intelligence and could perform any intellectual task that a
human can do.
Examples of Narrow AI - ANSWERS-Playing chess, purchasing suggestions
on an e-commerce site (Netflix/Amazon), self-driving cars, speech
recognition, facial recognition, and image recognition.
Supervised Learning - ANSWERS-A technique where a model is trained
using data that includes labeled examples, such as
images with tagged objects or text with marked sentiments. The model
learns from these labeled examples to make
predictions.
Unsupervised Learning - ANSWERS-A type of machine learning where the
model is trained on unlabeled data without explicit
guidance or supervision. The model finds patterns and relationships in the
data on its own.
Engineering Newest Exam 2026/2027 | All
Questions and Correct Detailed Answers |
Already Graded A | New and Revised
Key capabilities of LLM - ANSWERS-- Understanding and generating human-
like text
-Language translation
-Text summarization
-Question answering
-Content creation
-Conversational interactions (chatbots and virtual assistants)
-Rephrasing and rewriting text in different styles
Natural Language Processing (NLP) - ANSWERS-This field of AI is
concentrated on enabling computers to understand and
engage with human language, mirroring the intricacies of human
communication.
What are three applications of NLP in AI systems? - ANSWERS-Chatbots,
Sentiment Analysis, Language Translation
Chatbots - ANSWERS-AI programs that engage in natural conversations,
providing information and answering questions
Sentiment Analysis - ANSWERS-Determining the emotional tone or opinion
expressed in text (positive, negative, neutral)
, Language Translation - ANSWERS-Converting text or speech from one
language to another (Google Translate, real-time
translation services)
What are some other applications of NLP in AI systems? - ANSWERS-Other
applications include document summarization, text classification, and speech
recognition.
Narrow AI - ANSWERS-(weak AI) Designed for a specific task or a narrow set
of tasks. It excels at its designated purpose but cannot perform tasks outside
its programmed scope.
General AI - ANSWERS-a hypothetical future AI system that would possess
human-level intelligence and could perform any intellectual task that a
human can do.
Examples of Narrow AI - ANSWERS-Playing chess, purchasing suggestions
on an e-commerce site (Netflix/Amazon), self-driving cars, speech
recognition, facial recognition, and image recognition.
Supervised Learning - ANSWERS-A technique where a model is trained
using data that includes labeled examples, such as
images with tagged objects or text with marked sentiments. The model
learns from these labeled examples to make
predictions.
Unsupervised Learning - ANSWERS-A type of machine learning where the
model is trained on unlabeled data without explicit
guidance or supervision. The model finds patterns and relationships in the
data on its own.
