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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Machine Learning & Algorithms | 20% | - Types of Machine Learning
- Popular Algorithms
|
| Topic 2: Data Preparation & Engineering | 15% | - Data Collection & Sources - Data Cleaning, Preprocessing & Transformation - Data Quality & Governance - Feature Engineering & Selection |
| Topic 3: AI Fundamentals & Concepts | 15% | - AI Lifecycle and Workflow - Introduction to Artificial Intelligence
|
| Topic 4: AI Technologies & Tools | 15% | - Cloud AI Platforms (AWS, Azure, Google Cloud) - Frameworks: TensorFlow, PyTorch, Scikit-learn - AI Applications: NLP, Computer Vision, Predictive Analytics - Automation & RPA Integration |
| Topic 5: AI in Business & Consulting | 25% | - AI Project Management & Governance - Implementation Planning & Change Management - AI Strategy & Roadmap Development - Cost-Benefit Analysis & ROI Calculation - Identifying AI Use Cases & Opportunities |
| Topic 6: Ethics, Governance & Future Trends | 10% | - Data Privacy, Security & Compliance - Explainable AI & Transparency - AI Ethics, Bias & Fairness - Emerging Trends & Future of AI |
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NEW QUESTION # 34
Which of the following is not a CORRECT common unsupervised learning model/algorithm?
Answer: C
Explanation:
The correct answer is C. K-nearest neighbors KNNs because KNN is commonly used as a supervised learning algorithm, not an unsupervised learning algorithm. In supervised learning, the model uses labeled data to classify or predict outcomes for new data points. KNN works by comparing a new data point with nearby labeled examples and assigning a class or value based on those neighbors.
K-means clustering is a common unsupervised learning algorithm because it groups unlabeled data into clusters based on similarity. Principal Component Analysis PCA is also commonly associated with unsupervised learning because it reduces data dimensions by finding important patterns or directions of variance without requiring labeled outputs.
Since options A and B are valid unsupervised learning techniques, they are not the answer. The option that is not a correct common unsupervised learning model or algorithm is C. K-nearest neighbors KNNs .
NEW QUESTION # 35
Which of the following is the CORRECT stage of the Data and AI Analytics Business Model Maturity Index?
Answer: D
Explanation:
The correct answer is E. All of the above because the Data and AI Analytics Business Model Maturity Index describes how organizations progress in their ability to use data, analytics, and AI for business value creation.
Business Monitoring is a valid stage because organizations first use data to observe performance, track metrics, and understand what is happening in the business. Business Insights is also a correct stage because analytics then helps organizations explain why things are happening and identify patterns, opportunities, and risks.
Business Optimization is another valid stage because mature organizations use analytics and AI to improve processes, decisions, resources, customer experiences, and operational outcomes. Cultural Transformation is also part of maturity because long-term AI and data success requires a shift in mindset, leadership behavior, decision-making culture, and enterprise-wide adoption of data-driven practices.
Since all listed options represent stages or maturity areas in the Data and AI Analytics Business Model Maturity Index, the correct answer is E. All of the above .
NEW QUESTION # 36
Which of the following is a CORRECT statement for DevOps architect?
Answer: B
Explanation:
The correct answer is D. a and b only because statements A and B correctly describe DevOps and the role of a DevOps architect. DevOps is a collaborative approach that connects software development and IT operations so teams can build, test, deploy, monitor, and improve systems more efficiently. It emphasizes automation, communication, continuous delivery, monitoring, reliability, and faster release cycles.
Statement B is also correct because a DevOps architect is responsible for designing and optimizing CI/CD pipelines. These pipelines support continuous integration, automated testing, continuous deployment, infrastructure automation, and reliable software delivery. A DevOps architect may also consider monitoring, security, scalability, performance, and disaster recovery.
Statement C is incorrect because it describes the goal of advanced AI or artificial general intelligence, not DevOps. DevOps does not focus on creating human-like intelligent systems across multiple domains.
Therefore, the best answer is D. a and b only .
NEW QUESTION # 37
An AI agent learns to play a game by taking actions, receiving rewards for good moves, and penalties for poor moves. Over time, it improves its strategy to maximize total reward. This is an example of ______.
Answer: E
Explanation:
Reinforcement learning is the correct answer because the AI agent learns by interacting with an environment and improving its behavior based on rewards and penalties. The goal of reinforcement learning is to learn a policy or strategy that maximizes cumulative reward over time. This differs from supervised learning, where the model learns from labeled input-output examples. It also differs from unsupervised learning, where the model searches for hidden patterns without labels or rewards. Semi-supervised learning is incorrect because the scenario does not involve a mix of labeled and unlabeled data. Regression learning is also incorrect because regression predicts continuous numerical values, while this example focuses on action selection and reward optimization. Therefore, the correct answer is C. reinforcement learning .
NEW QUESTION # 38
Which of the following is a regulatory requirement?
Answer: B
Explanation:
The correct answer is E. a, b and c only because HIPAA, GDPR, and CCPA are all regulatory requirements that organizations may need to follow when collecting, processing, storing, sharing, or protecting data. In AI and data-driven business environments, regulatory compliance is important because AI systems often depend on large volumes of personal, sensitive, customer, health, or behavioral data.
HIPAA is a United States healthcare regulation that protects sensitive patient health information. GDPR is a European Union data protection regulation that governs personal data processing, privacy rights, consent, data minimization, and accountability. CCPA is a California privacy law that gives consumers rights related to personal information, including access, deletion, and opt-out rights. These regulations affect how organizations design AI systems, manage data governance, ensure privacy, reduce risk, and maintain responsible AI practices.
Since all three listed items are valid regulatory requirements, the correct answer is E. a, b and c only .
NEW QUESTION # 39
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