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WGU D685 - PRACTICAL APPLICATIONS OF PROMPT ACTUAL FINAL EXAM 2026/2027 WITH 250 QUESTIONS AND WELL VERIFIED CORRECT ANSWERS | ALREADY GRADED A+ | GUARANTEED SUCCESS | WGU D685 LATEST EXAM

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WGU D685 - PRACTICAL APPLICATIONS OF PROMPT ACTUAL FINAL EXAM 2026/2027 WITH 250 QUESTIONS AND WELL VERIFIED CORRECT ANSWERS | ALREADY GRADED A+ | GUARANTEED SUCCESS | WGU D685 LATEST EXAM a technique where a model is trained using data that includes labeled examples, such as images with tagged objects or text with marked entities supervised learning a type of machine learning where the model is trained on unlabeled data without explicit guidance or supervision unsupervised learning a type of machine learning wherein an AI agent learns through interactions with an environment, garnering rewards or penalties contingent upon its actions reinforcement learning

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WGU D685 - PRACTICAL APPLICATIONS OF
PROMPT ACTUAL FINAL EXAM 2026/2027
WITH 250 QUESTIONS AND WELL-
VERIFIED CORRECT ANSWERS | ALREADY
GRADED A+ | GUARANTEED SUCCESS |
WGU D685 LATEST EXAM




a technique where a model is trained using data that includes labeled examples,
such as images with tagged objects or text with marked entities
supervised learning




a type of machine learning where the model is trained on unlabeled data without
explicit guidance or supervision
unsupervised learning




a type of machine learning wherein an AI agent learns through interactions with an
environment, garnering rewards or penalties contingent upon its actions
reinforcement learning

,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
neural networks




a powerful subset of machine learning that uses artificial neural networks to learn
from large amounts of data
deep learning




AI systems that can create new content
generative AI




a type of machine learning model that is trained on massive amounts of text data to
understand and generate human-like language
large language models (LLMs)




the field of AI concentrated on enabling computers to understand and engage with
human language, mirroring the intricacies of human communication
natural language processing (NLP)

,AI programs designed to engage in natural conversations with people, providing
information, answering questions, and even offering emotional support
chatbots




a field of artificial intelligence that enables computers to interpret and analyze
visual information from the real world, such as images and videos
computer vision




the field of AI that focuses on designing, constructing, and operating robots
robotics




a technique employed in AI that involves collecting, organizing, examining, and
interpreting data to identify patterns and make predictions
statistical analysis




software programs designed to assist users in performing AI-related tasks
AI tools




Match the example prompts with the technique:
"Write a dialogue between two friends planning a trip."
This is an example of Few-Shot Prompting

, data that is organized in a well-defined format and is typically stored in databases
or spreadsheets
structured data


The limitations of AI can be categorized into three main areas:
- fundamental limitations of AI
- practical limitations and challenges
- societal concerns and implications.




Fundamental limitations of AI include:
- dependence on training data
- limited common sense
- lack of emotional sense.




Practical limitations of AI include:
- perpetuating bias
- lack of ethics
- understanding nuances of language and humans.




Societal concerns on AI include:
- data privacy

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Subido en
2 de junio de 2026
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2025/2026
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Examen
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