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Cisco 810-110 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Prompt Engineering	15%	- Prompt design principles 1. Roles, instructions, constraints - Security and robustness 1. Prompt injection risks 2. Mitigation and defensive prompting - Prompting techniques 1. Few-shot prompting 2. Chained and iterative prompting
Topic 2: AI for Code and Workflow Optimization		- AI-assisted software development 1. Code generation and debugging 2. SDLC integration - Automation workflows 1. API integration basics 2. Workflow orchestration concepts
Topic 3: Ethics and Security	15%	- AI security threats 1. AI-specific attack surfaces 2. Misinformation and hallucinations - Data privacy and governance 1. Secure AI data handling - Responsible AI principles 1. Bias mitigation 2. Fairness, transparency, accountability
Topic 4: Generative AI Models	20%	- Model hosting and architecture 1. Latency, cost, privacy considerations 2. Cloud vs local deployment trade-offs - Context and retrieval systems 1. RAG, embeddings, vector databases 2. Context windows and token limits - Model fundamentals and use cases 1. LLMs and diffusion models overview 2. Use cases: summarization, code generation, content creation
Topic 5: AI for Data Research and Analysis		- Data exploration and transformation 1. Insight generation and validation 2. AI-assisted data cleaning
Topic 6: Agentic AI Systems		- Agent architecture 1. Multi-step reasoning workflows 2. Autonomous agents and orchestration

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Cisco AI Technical Practitioner Sample Questions (Q51-Q56):

NEW QUESTION # 51
Which threat involves an attacker intentionally contaminating the training set of a model to influence its future behavior?

A. algorithmic bias
B. gradient inversion
C. data poisoning
D. direct prompt injection

Answer: C

Explanation:
Data poisoning occurs when an attacker deliberately manipulates or contaminates training data so the model learns harmful, biased, or attacker-controlled behavior.

NEW QUESTION # 52
In an AI-powered automation workflow, what is the function of an approval gate?

A. to apply human judgement before high-impact actions are executed
B. to ensure the internal logic of AI remains closed for modification
C. to automatically block deployments if system health alerts are active
D. to trigger automated completion notifications to project stakeholders

Answer: A

Explanation:
An approval gate adds human review before an automated workflow performs a high-impact action, helping ensure that AI-driven decisions are checked for correctness, risk, and business impact before execution.

NEW QUESTION # 53
How does a coordinator agent function in a multi-agent AI framework?

A. It replaces the need for multiple agents by handling tasks within a single reasoning loop.
B. It orchestrates task delegation across specialized agents and aggregates the outputs.
C. It serves as the external data source that each agent queries for grounding information.
D. It fine-tunes each agent's model weights to optimize performance on assigned tasks.

Answer: B

Explanation:
A coordinator agent manages the overall workflow by assigning tasks to specialized agents, coordinating their interactions, and combining their outputs into a final result.

NEW QUESTION # 54
A practitioner is estimating the operational cost of integrating a cloud-hosted LLM API into an application. How does tokenization influence the cost of using this API?

A. Tokenization has no impact because pricing is based on a flat-rate subscription.
B. The number of tokens determines the per-request cost.
C. Tokenization increases cost by requiring additional GPU run time.
D. Costs are determined by the number of API calls.

Answer: B

Explanation:
Cloud-hosted LLM APIs commonly charge based on the number of input and output tokens processed, so tokenization directly affects the per-request cost.

NEW QUESTION # 55
When using AI to draft a technical proposal, what is the benefit of a format-agnostic strategy?

A. It allows for easy repurposing.
B. It maintains contextual alignment.
C. It ensures the most creative text.
D. It minimizes token consumption.

Answer: A

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 # 56
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