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Cisco 810-110 Exam Syllabus Topics:

Section	Weight	Objectives
Agentic AI Systems		- Agent architecture 1. Multi-step reasoning workflows 2. Autonomous agents and orchestration
AI for Data Research and Analysis		- Data exploration and transformation 1. Insight generation and validation 2. AI-assisted data cleaning
Ethics and Security	15%	- Data privacy and governance 1. Secure AI data handling - AI security threats 1. AI-specific attack surfaces 2. Misinformation and hallucinations - Responsible AI principles 1. Bias mitigation 2. Fairness, transparency, accountability
Prompt Engineering	15%	- Prompting techniques 1. Chained and iterative prompting 2. Few-shot prompting - Prompt design principles 1. Roles, instructions, constraints - Security and robustness 1. Prompt injection risks 2. Mitigation and defensive prompting
Generative AI Models	20%	- Context and retrieval systems 1. RAG, embeddings, vector databases 2. Context windows and token limits - Model fundamentals and use cases 1. Use cases: summarization, code generation, content creation 2. LLMs and diffusion models overview - Model hosting and architecture 1. Latency, cost, privacy considerations 2. Cloud vs local deployment trade-offs
AI for Code and Workflow Optimization		- Automation workflows 1. Workflow orchestration concepts 2. API integration basics - AI-assisted software development 1. Code generation and debugging 2. SDLC integration

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Cisco AI Technical Practitioner Sample Questions (Q18-Q23):

NEW QUESTION # 18
Why is defining a persona considered a best practice for technical prompt engineering?

A. It guides the tone and vocabulary.
B. It reduces the total token usage.
C. It provides a pattern to emulate.
D. It provides instructions for desired action.

Answer: A

Explanation:
Defining a persona guides the AI to respond with the appropriate role-based tone, vocabulary, level of technical depth, and communication style for the intended audience.

NEW QUESTION # 19
How does context window management help control the cost of a long-running AI conversation?

A. by automatically switching to a lower-cost model as the conversation history grows
B. by increasing the context window size to reduce the total number of API calls
C. by capping the cumulative number of input tokens sent with each new prompt
D. by switching to an algorithm that reduces the character-to-token ratio

Answer: C

Explanation:
Context window management controls cost by limiting how much prior conversation history is included with each new request, reducing the number of input tokens processed and billed.

NEW QUESTION # 20
What is the main advantage of cloud-based AI services?

A. Scalability and flexible compute resources
B. Unlimited free hardware
C. Elimination of cybersecurity risks
D. No need for networking

Answer: A

Explanation:
Cloud AI platforms provide scalable infrastructure and elastic computing power for AI workloads.

NEW QUESTION # 21
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?

A. performing code scaffolding
B. executing legacy code refactoring
C. implementing predictive function logic
D. providing inline co-pilot assistance

Answer: A

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 # 22
Which AI-assisted task standardizes inconsistent date formats (e.g., MM/DD/YY and DD-MM- YYYY)?

A. data transformation
B. data visualization
C. thematic summarization
D. data correlation

Answer: A

Explanation:
Data transformation converts inconsistent data into a consistent format, such as standardizing multiple date formats into one required representation.

NEW QUESTION # 23
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