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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Research and Analysis | 15% | - Data collection, preparation and preprocessing - Data quality, bias and validation - Data visualization and insight generation |
| Topic 2: Prompt Engineering | 15% | - Prompt design principles and best practices - Advanced prompting techniques - Defensive prompting and error mitigation |
| Topic 3: Agentic AI | 15% | - Human-in-the-loop strategies - Model Context Protocol (MCP) framework - Agentic AI vs Generative AI use cases - Agent design principles and capabilities |
| Topic 4: AI for Code and Workflow Optimization | 15% | - Automation and workflow enhancement - Integration of AI tools in development processes - AI-assisted code generation and improvement |
| Topic 5: AI Ethics and Security | 20% | - Responsible AI principles - AI-specific threats, risks and misinformation - Data privacy and security in AI systems - Compliance and governance frameworks |
| Topic 6: Generative AI Models | 20% | - Model selection and evaluation in AI hubs - Context windows, token limits and response management - Generative AI model families and use cases - Model hosting options and trade-offs |
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NEW QUESTION # 12
Which metric is commonly used to evaluate classification models?
Answer: C
Explanation:
Accuracy measures how many predictions were correct out of total predictions.
NEW QUESTION # 13
A team uses AI to scaffold a new microservice. What does this process involve?
Answer: D
Explanation:
Scaffolding uses AI to generate the initial project structure, boilerplate files, configuration, and basic code layout so the team can start development faster.
NEW QUESTION # 14
A company discloses to its users that their support tickets are being summarized by an AI model.
Which responsible AI principle does this action support?
Answer: D
Explanation:
Transparency means clearly informing users when AI is being used, what it is doing, and how it may affect their data or experience.
NEW QUESTION # 15
When using AI to draft a technical proposal, what is the benefit of a format-agnostic strategy?
Answer: D
Explanation:
A format-agnostic strategy keeps the content independent of a specific final layout, making it easier to reuse or adapt the same proposal material for different formats such as email, slides, documents, or reports.
NEW QUESTION # 16
Which design principle helps prevent an autonomous agent from looping infinitely and wasting tokens?
Answer: A
Explanation:
Implementing constraints, such as maximum iteration limits, stop conditions, and execution boundaries, helps prevent an autonomous agent from repeatedly running actions without reaching a valid endpoint.
NEW QUESTION # 17
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