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NEW QUESTION # 53
If humans are unlabeling the data and the machine is correctly labeling current or future data points, it's
______.
Answer: A
Explanation:
Semi-supervised learning is the correct answer because it combines a small amount of labeled data with a larger amount of unlabeled data. In this scenario, humans are not fully labeling the data, but the machine is still able to correctly label current or future data points by learning patterns from the available data. That matches the concept of semi-supervised learning, where the model uses limited human-provided labels and extends learning to unlabeled examples.
Supervised learning is not the best answer because supervised learning depends on clearly labeled training data supplied by humans. Unsupervised learning is also incorrect because it identifies hidden patterns or clusters without using labels, rather than predicting correct labels for future data points. Reinforcement learning is based on rewards, penalties, actions, and an environment, which is not described here. "Semi- reinforcement learning" is not a standard main category in machine learning.
Therefore, the most accurate answer is **E. Semi-supervised learning**.
NEW QUESTION # 54
Which one of the following is a NOT good attribute of solution architecture?
Answer: D
Explanation:
The correct answer is C. Tightly coupled architecture because a strong solution architecture should promote flexibility, scalability, maintainability, integration readiness, and adaptability. A tightly coupled architecture means system components are highly dependent on one another. This creates problems when teams need to update, scale, replace, test, or modify one part of the system, because changes in one component can easily affect other components. In enterprise AI and software solution design, this increases operational risk, slows innovation, and makes future growth more difficult.
Technology alignment with business requirements is a good attribute because architecture must support business goals and operational needs. Scalability and flexibility are also good attributes because modern solutions must handle growth, changing workloads, and evolving requirements. Risk mitigation is a strong architectural objective because good design reduces security, performance, compliance, and operational risks.
Increased ROI is also a desired outcome when architecture improves efficiency and business value. Therefore, the attribute that is NOT good is C. Tightly coupled architecture .
NEW QUESTION # 55
What type of learning is used when a model is trained with labeled data?
Answer: D
Explanation:
The correct answer is B. Supervised Learning . Supervised learning is the machine learning approach used when a model is trained with labeled data. Labeled data means each training example includes both the input and the correct output or target label. The model studies these examples and learns the relationship between the input features and the expected result. After training, it can make predictions or classifications on new data.
Unsupervised learning is incorrect because it uses unlabeled data and focuses on finding hidden patterns, clusters, or structures without predefined answers. Reinforcement learning is incorrect because it involves an agent learning through actions, rewards, and penalties in an environment. Semi-supervised learning is also not the best answer because it uses a mix of labeled and unlabeled data. Support Vector refers to part of the Support Vector Machine method, not a learning type by itself. Therefore, the correct learning type for labeled data is B. Supervised Learning .
NEW QUESTION # 56
Which of the CORRECT cognitive modeling is used in AI applications?
Answer: E
Explanation:
The correct answer is E. All of the above because deep learning, expert systems, natural language processing, and robotics are all connected with AI applications that support or model intelligent behavior. Cognitive modeling in AI is concerned with building systems that can represent, simulate, or support human-like capabilities such as learning, reasoning, decision-making, perception, language understanding, and action.
Deep learning is used to recognize patterns from large amounts of data and is common in speech recognition, image analysis, recommendation systems, and generative AI. Expert systems use knowledge bases and rules to support decision-making in specialized domains. Natural language processing helps AI systems understand, interpret, generate, and respond to human language. Robotics applies AI to physical systems so machines can sense, plan, move, and perform tasks in real-world environments.
Since all the listed options are valid AI application areas related to intelligent and cognitive capabilities, the correct answer is E. All of the above .
NEW QUESTION # 57
Which of the following is a step for the Value Engineering Framework?
Answer: C
Explanation:
The correct answer is E. All of the above because the Value Engineering Framework focuses on identifying, delivering, and expanding measurable business value from data and AI initiatives. "Define value creation" is a key step because organizations must first clarify the business problem, expected outcomes, success metrics, stakeholders, and value drivers before investing in an AI solution.
"Realize value creation" is also correct because value must be converted from a planned objective into actual operational or financial impact. This may involve deploying the solution, measuring results, improving processes, reducing cost, increasing revenue, improving risk management, or enhancing customer outcomes.
"Scale value creation" is correct because successful AI initiatives should not remain limited to isolated pilots.
Organizations need to scale proven use cases across teams, business units, workflows, and enterprise platforms to maximize return on investment and long-term impact. Since all three options represent steps in value engineering, the best answer is E. All of the above .
NEW QUESTION # 58
......
In the present situation, you will find companies laying off their employees without any notice or prior information. They are just receiving an email and the next moment they have no access to the company network. So to avoid all this, you have to keep yourself updated with the new version of technologies and applications. You have to become one of Certified Artificial Intelligence Consultant (CAIC) certification holders who survived the laying off situation and are still in a great position in their company. You cannot afford to lose it when you need your job the most.
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