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| Section | Weight | Objectives |
|---|---|---|
| AI for Code and Workflow Optimization | 15% | - Integration of AI tools in development processes - Automation and workflow enhancement - AI-assisted code generation and improvement |
| Prompt Engineering | 15% | - Prompt design principles and best practices - Advanced prompting techniques - Defensive prompting and error mitigation |
| Generative AI Models | 20% | - Model hosting options and trade-offs - Model selection and evaluation in AI hubs - Generative AI model families and use cases - Context windows, token limits and response management |
| Data Research and Analysis | 15% | - Data quality, bias and validation - Data collection, preparation and preprocessing - Data visualization and insight generation |
| Agentic AI | 15% | - Agentic AI vs Generative AI use cases - Model Context Protocol (MCP) framework - Human-in-the-loop strategies - Agent design principles and capabilities |
| AI Ethics and Security | 20% | - AI-specific threats, risks and misinformation - Compliance and governance frameworks - Responsible AI principles - Data privacy and security in AI systems |
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NEW QUESTION # 16
Which AI-driven activity involves a developer providing runtime error logs to a model to receive an explanation of the root cause and a suggested fix?
Answer: D
Explanation:
AI-assisted debugging uses error logs, stack traces, and runtime context to help identify the root cause of a failure and suggest a corrective fix.
NEW QUESTION # 17
Which AI-assisted task standardizes inconsistent date formats (e.g., MM/DD/YY and DD-MM- YYYY)?
Answer: B
Explanation:
Data transformation converts inconsistent data into a consistent format, such as standardizing multiple date formats into one required representation.
NEW QUESTION # 18
Which activity occurs when a developer uses AI to generate a complete Python class for a new API client based on a high-level description?
Answer: D
Explanation:
Code scaffolding uses AI to generate the initial structure and boilerplate for a new component, such as a complete Python class for an API client based on a high-level description.
NEW QUESTION # 19
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 # 20
What happens when the input provided to an LLM exceeds its context window limit?
Answer: D
Explanation:
When input exceeds the context window, the model cannot process all provided text at once, so earlier content may be truncated or pushed out of the active context.
NEW QUESTION # 21
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