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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI in Business & Consulting | 25% | - Cost-Benefit Analysis & ROI Calculation - AI Strategy & Roadmap Development - AI Project Management & Governance - Implementation Planning & Change Management - Identifying AI Use Cases & Opportunities |
| Topic 2: Data Preparation & Engineering | 15% | - Data Collection & Sources - Data Cleaning, Preprocessing & Transformation - Data Quality & Governance - Feature Engineering & Selection |
| Topic 3: Machine Learning & Algorithms | 20% | - Types of Machine Learning
- Popular Algorithms
|
| Topic 4: Ethics, Governance & Future Trends | 10% | - Emerging Trends & Future of AI - AI Ethics, Bias & Fairness - Data Privacy, Security & Compliance - Explainable AI & Transparency |
| Topic 5: AI Fundamentals & Concepts | 15% | - AI vs Traditional Programming - Introduction to Artificial Intelligence
|
| Topic 6: AI Technologies & Tools | 15% | - Cloud AI Platforms (AWS, Azure, Google Cloud) - Frameworks: TensorFlow, PyTorch, Scikit-learn - Automation & RPA Integration - AI Applications: NLP, Computer Vision, Predictive Analytics |
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NEW QUESTION # 46
Which of the following is a CORRECT statement for the Data and AI Analytics Business Model Maturity Index?
Answer: B
Explanation:
The correct answer is D. a and b only because the Data and AI Analytics Business Model Maturity Index is mainly used to guide and assess how effectively an organization uses data, analytics, and AI to improve business and operational models. Option A is correct because a maturity index provides a roadmap that helps organizations understand where they are currently and what capabilities they need to develop next. This supports better use of analytics, data-driven decision-making, and AI-enabled transformation.
Option B is also correct because a maturity index works as a benchmark. Organizations can compare their current maturity level against defined stages, measure progress, identify gaps, and evaluate improvement in analytics capabilities over time.
Option C is not the best statement because "focus on ROI and team" is too narrow and incomplete. ROI and team capability may be considered in analytics planning, but they do not fully define the purpose of the maturity index. Therefore, the best answer is D. a and b only .
NEW QUESTION # 47
Which of the following is a CORRECT statement for DevOps architect?
Answer: A
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 # 48
Supervised learning is a type of machine learning where the algorithm learns from a ______.
Answer: E
Explanation:
The correct answer is A. labeled dataset . Supervised learning is a machine learning method in which an algorithm is trained using data that already contains the correct output labels or target values. Each training example includes input features and a known answer, allowing the model to learn the relationship between the inputs and the expected output. Once trained, the model can use that learned relationship to classify or predict outcomes for new data.
An unlabeled dataset is used in unsupervised learning, where the model identifies hidden patterns, clusters, or relationships without predefined labels. An "explained dataset" is not a standard machine learning category.
Option D is incorrect because supervised learning does not learn from both labeled and unlabeled datasets as its primary definition. Option E is also incorrect because "explained dataset" is not the correct term.
Therefore, supervised learning learns from a labeled dataset , making A the correct answer.
NEW QUESTION # 49
Which of the CORRECT cognitive modeling is used in AI applications?
Answer: C
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 # 50
Which type of AI mimics the human brain by building networks of artificial neurons?
Answer: E
Explanation:
The correct answer is C. Neural Networks . Neural networks are AI and machine learning models inspired by the structure and function of the human brain. They are built using interconnected artificial neurons, also called nodes, which process input data, apply weights and activation functions, and pass information through layers to produc e an output. This structure allows neural networks to learn complex patterns from data.
Fuzzy logic is incorrect because it deals with reasoning under uncertainty using degrees of truth rather than artificial neurons. Genetic algorithms are optimization methods inspired by natural selection and evolution, not the brain's neuron-based structure. Expert systems use rules and knowledge bases to make decisions, but they do not mimic the brain through networks of artificial neurons. Since the question specifically asks about AI that mimics the human brain by building artificial neuron networks, the correct answer is C. Neural Networks .
NEW QUESTION # 51
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