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| Section | Objectives |
|---|---|
| Topic 1: Neural Networks and Technical Applications | - Designing, developing, and troubleshooting technical applications on neural networks - Enhancing approaches to problems such as translation, speech recognition, and image classification |
| Topic 2: AI Solutions and Workflows | - AI workflows - Fraud prevention with Cloud AI solutions - Sentiment analysis - Advanced robotics |
| Topic 3: AI Fundamentals and Data Systems | - Developing and deploying data systems related to AI - Fundamentals of Artificial Intelligence and Machine Learning |
| Topic 4: Deployment and Maintenance | - Development, deployment, testing, and maintenance of AI applications |
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NEW QUESTION # 14
Which of the following is NOT a type of machine learning?
Answer: B
Explanation:
The correct answer is D. Restricted Learning because it is not commonly recognized as a standard type of machine learning. The main learning approaches include supervised learning, unsupervised learning, semi- supervised learning, reinforcement learning, and transfer learning. Supervised learning uses labeled datasets to train models for prediction or classification. Unsupervised learning uses unlabeled data to discover patterns, clusters, or hidden structures. Semi-supervised learning combines a small amount of labeled data with a larger amount of unlabeled data. Transfer learning reuses knowledge from a pre-trained model and adapts it to a new related task.
"Restricted Learning" is not a standard machine learning category in this context. Although some specific technical terms may include the word "restricted," such as restricted Boltzmann machines, that does not make
"restricted learning" a recognized general type of machine learning. Therefore, the option that is NOT a type of machine learning is D. Restricted Learning .
NEW QUESTION # 15
Choose the CORRECT benefits a business can get through segmentation.
Answer: E
Explanation:
The correct answer is E. a, b and c only because all three statements describe valid business benefits of segmentation. Segmentation means dividing customers, markets, products, or users into meaningful groups based on shared characteristics, behaviors, needs, value, preferences, or risk profiles. In AI and analytics, segmentation helps organizations understand different customer groups more clearly and make better business decisions.
Statement A is correct because segmentation allows businesses to create targeted marketing communication.
Instead of sending the same message to everyone, companies can design messages that match each segment's interests, needs, and buying behavior. Statement B is also correct because segmentation can support pricing strategies by helping businesses offer the right pricing, discounts, bundles, or value propositions to the right customer groups. Statement C is correct because segmentation improves client service by helping teams understand customer expectations and deliver more relevant support, recommendations, and experiences.
Therefore, all listed benefits are correct, making E the best answer.
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NEW QUESTION # 16
Which one of the following is a NOT good attribute of solution architecture?
Answer: B
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 # 17
A retail company has a large dataset of customer purchases but no predefined labels. The AI system groups customers into segments based on similar buying behavior. This is an example of ______.
Answer: C
Explanation:
Unsupervised learning is the correct answer because the dataset does not contain predefined labels or known target outcomes. The AI system is identifying natural patterns in the data and grouping customers with similar purchasing behavior. This type of task is commonly called clustering, which is one of the most common applications of unsupervised learning. Supervised learning is incorrect because there are no labeled examples telling the model which customer belongs to which segment. Reinforcement learning is incorrect because the system is not learning through rewards or penalties. Transfer learning involves reusing knowledge from one trained model for another related task, which is not described here. Semi-supervised learning would involve both labeled and unlabeled data, but this scenario only mentions unlabeled data. Therefore, the correct answer is B. unsupervised learning .
NEW QUESTION # 18
Which of the following is NOT a pillar of the GenAI Well-Architected Framework?
Answer: A
Explanation:
The correct answer is D. System Architecture Excellence because it is not normally identified as a standard pillar of a GenAI Well-Architected Framework. Well-architected AI and GenAI frameworks commonly focus on structured pillars such as operational excellence, security and privacy, reliability, performance, cost optimization, responsible AI, and governance-related practices. These pillars help organizations design GenAI solutions that are secure, scalable, reliable, maintainable, and aligned with business and ethical expectations.
Operational excellence is a valid pillar because GenAI systems require proper deployment processes, observability, automation, monitoring, incident response, and lifecycle management. Security and privacy are also essential because GenAI applications often process sensitive data, prompts, outputs, embeddings, and model interactions. Reliability is another valid pillar because GenAI solutions must handle failures, latency, model availability, fallback mechanisms, and consistent service delivery.
"System Architecture Excellence" sounds related to solution design, but it is not a recognized pillar name in the listed framework. Therefore, the option that is NOT a pillar is D .
NEW QUESTION # 19
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