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| Section | Weight | Objectives |
|---|---|---|
| AI Fundamentals & Concepts | 15% | - Introduction to Artificial Intelligence
- AI vs Traditional Programming |
| Ethics, Governance & Future Trends | 10% | - Emerging Trends & Future of AI - Explainable AI & Transparency - Data Privacy, Security & Compliance - AI Ethics, Bias & Fairness |
| Machine Learning & Algorithms | 20% | - Types of Machine Learning
- Popular Algorithms
|
| Data Preparation & Engineering | 15% | - Data Quality & Governance - Data Cleaning, Preprocessing & Transformation - Data Collection & Sources - Feature Engineering & Selection |
| AI Technologies & Tools | 15% | - Frameworks: TensorFlow, PyTorch, Scikit-learn - AI Applications: NLP, Computer Vision, Predictive Analytics - Automation & RPA Integration - Cloud AI Platforms (AWS, Azure, Google Cloud) |
| AI in Business & Consulting | 25% | - AI Project Management & Governance - Cost-Benefit Analysis & ROI Calculation - AI Strategy & Roadmap Development - Implementation Planning & Change Management - Identifying AI Use Cases & Opportunities |
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NEW QUESTION # 66
Choose the CORRECT example of a business goal?
Answer: A
Explanation:
A business goal is a measurable outcome that an organization wants to achieve through strategy, operations, technology, or transformation initiatives. In artificial intelligence and business analytics contexts, common business goals include reducing operating costs, minimizing risks, improving customer or product outcomes, and increasing revenue. Cost reduction for operational processes is a valid business goal because AI can automate tasks, optimize resources, and reduce inefficiencies. Mitigation of business or operational risks is also a valid goal because AI can support fraud detection, compliance monitoring, anomaly detection, and predictive risk analysis. Product or service revenue improvement is another valid goal because AI can help personalize offerings, improve pricing, identify market opportunities, and increase customer value.
Since all three listed choices represent legitimate business goals that can guide AI initiatives and business transformation, the most complete and correct option is E. All of the above .
NEW QUESTION # 67
Which of the following is CORRECT for Support Vector Machine SVM?
Answer: C
Explanation:
The correct answer is D. a and b only . Support Vector Machine, or SVM, is a supervised machine learning algorithm widely used for classification problems. It works by finding the best separating boundary, called a hyperplane, between different classes in the dataset. The goal is to maximize the margin between the closest data points of each class, known as support vectors, so the model can classify new data more effectively.
Statement B is also correct because SVM can use kernel methods to transform data into higher-dimensional spaces. This helps make complex or non-linearly separable data easier to separate. For example, when data cannot be clearly grouped in a two-dimensional view, a kernel function can map it into a higher-dimensional feature space where a better separating hyperplane may be found.
Statement C is incorrect because SVM does allow dimensional transformation through kernel techniques.
Therefore, the correct choice is D. a and b only .
NEW QUESTION # 68
What is the main advantage of using deep learning over traditional machine learning?
Answer: D
NEW QUESTION # 69
Which of the following statement is CORRECT for RNN?
Answer: B
Explanation:
The correct answer is E. a, b and c only because all three statements correctly describe Recurrent Neural Networks and their limitation. RNNs are neural network models designed for sequential data such as text, speech, time-series data, and ordered events. They process information step by step and use previous hidden states to influence later outputs.
Statement A is correct because a major drawback of traditional RNNs is their difficulty in remembering information over many time steps. This happens mainly because of vanishing gradient problems during training. Statement B is also correct because standard RNNs generally struggle with long-term dependencies, meaning they may fail to retain important information from earlier parts of a sequence. Statement C is correct because Long Short-Term Memory networks are a specialized extension of RNNs designed to handle long- term memory more effectively using gates that control what information is stored, forgotten, and passed forward.
Therefore, the best answer is E. a, b and c only .
NEW QUESTION # 70
Which of the following is a CORRECT statement for the Data and AI Analytics Business Model Maturity Index?
Answer: A
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 # 71
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