Cisco 810 - 110 Certification Study Guide | Exam Prep & Practice Questions Exam Preparation Tips and Recommended Study Resources www.NWExam.com The Cisco AI Technical Practitioner 810 - 1 10 Certification Study Guide is designed to help professionals prepare effectively for the AITECH exam. This guide covers core AI concepts, generative AI fundamentals, data preparation, prompt engineering, security, ethics, and real - world Cisco AI use case s. It provides a structured overview of exam objectives, key topics, and practice - style questions aligned with the latest Cisco exam blueprint. Ideal for IT professionals and beginners in AI, this study guide supports skill development and exam readiness f or earning the globally recognized Cisco AI Technical Practitioner certification. PDF 810-110 AI Technical Practitioner Sample Questions 1 Cisco AI Technical Practitioner 810-110 Certification Study Guide Cisco 810-110 Certification Exam Details Cisco 810-110 certifications are globally accepted and add significant value to any IT professional. The certification gives you a profound understanding of all the workings of the network models and the devices that are utilized with it. NWExam.com is proud to provide you with the best Cisco Exam Guides. The Cisco 810-110 Exam is challenging, and thorough preparation is essential for success. This cert guide is designed to help you prepare for the AI Technical Practitioner certification exam. It contains a detailed list of the topics covered on the Professional exam. These guidelines for the AITECH will help guide you through the study process for your certification. To obtain Cisco AI Technical Practitioner certification, you are required to pass the AITECH 810-110 exam. This exam is created keeping in mind the input of professionals PDF 810-110 AI Technical Practitioner Sample Questions 2 in the industry and reveals how Cisco products are used in organizations across the world. 810-110 Cisco AI Technical Practitioner Exam Summary ● Exam Name: Cisco AI Technical Practitioner ● Exam Code: 810-110 ● Exam Price: $150 USD ● Duration: 60 minutes ● Number of Questions: 40-60 ● Passing Score: Variable (750-850 / 1000 Approx.) ● Exam Registration: PEARSON VUE ● Recommended Practice: Cisco AI Technical Practitioner Practice Test ● Recommended Training: Cisco AI Technical Practitioner | AITECH Topics covered in the Cisco AI Technical Practitioner 810-110 Exam Section Weight Objectives Generative AI Models 20% - Describe major generative AI model families (e.g., LLMs, diffusion models) and common use cases (text summarization, content creation, code generation) - Compare model hosting options (cloud - hosted vs locally hosted) and their trade - offs (cost, latency, privacy, scalability) - Explain role of context windows, token limits and response management - Understand model selection in AI model hubs and repositories for appropriate use - cases (e.g., reasoning, multimodality) - Describe Retrieval Augmented Generatio n (RAG) and role of embeddings and vector databases Prompt Engineering 15% - Understand prompt engineering principles and patterns (roles, instructions, constraints) - Explain prompting techniques (iterative/sequential, chained, few - shot) and structures for text, image and audio generation - Describe prompt injection attack types - Explain defensive prompting and mitigation strategies for AI - generated errors (e.g., hal lucinations) Ethics and Security 15% - Explain responsible AI principles (fairness, transparency, accountability, bias mitigation, safety) PDF 810-110 AI Technical Practitioner Sample Questions 3 Section Weight Objectives - Describe approaches to protect corporate data privacy and security in AI systems - Explain AI - specific secur ity threats and risks, including misinformation - Explain AI governance considerations (policy, risk management, compliance) Data Research and Analysis 10% - Explain AI’s role in exploratory data analysis (EDA) - Describe automated data preparation tasks (quality checks, formatting, transformation, cleaning) - Explain the ethical and privacy considerations in AI - assisted data analysis, including controls to prevent data exposure - Describe techniques for AI - assis ted research, ideation, and content drafting Development and Workflow Automation 20% - Describe AI's role across the software development lifecycle (requirements, prototyping, implementation, testing, deployment) - Describe the AI capabilities for c ode generation and rapid prototyping - Explain AI workflow design and monitoring principles - Describe how token usage and context - window management affect prototyping cost, latency, and output quality - Explain how AI improves code quality (debugging assi stance, error handling, documentation) Agentic AI 20% - Differentiate Agentic AI from Generative AI use cases - Explain AI agent design principles, autonomous capabilities, and orchestration - Describe Model Context Protocol (MCP) framework primitives in context of agentic AI - Explain human - in - the - loop (HITL) strategies - Describe data transformation and mapping within AI Agents AI Technical Practitioner 810-110 Practice Exam Questions. Grab an understanding from these Cisco 810-110 sample questions and answers and improve your 810-110 exam preparation towards attaining a Cisco AI Technical Practitioner Certification. Answering these sample questions will make you familiar with the types of questions you can expect on the actual exam. Doing practice with AI Technical Practitioner AITECH questions and answers before the exam as much as possible is the key to passing the Cisco 810-110 certification exam. PDF 810-110 AI Technical Practitioner Sample Questions 4 810-110 Cisco AI Technical Practitioner Sample Questions:- 01. Which use case is best suited for diffusion models rather than LLMs? a) Sentiment analysis b) Image synthesis from noise c) Chat-based question answering d) Code refactoring Answer: b 02. During automated data preparation, an AI system flags missing values and inconsistent formats across multiple data sources. This step occurs before analysis or modeling begins. Which task category is the AI primarily performing? a) Feature engineering b) Data quality checking and cleaning c) Model evaluation d) Prompt optimization Answer: b 03. Few-shot prompting is often recommended when working with specialized or domain-specific tasks. This technique relies on providing examples to guide the model’s behavior. Why do examples improve model performance in these scenarios? a) They demonstrate desired patterns and structure b) They retrain the model dynamically c) They increase the model’s context window d) They reduce token consumption Answer: a 04. What is the primary role of a context window in generative AI systems? a) Enforcing ethical constraints b) Controlling model accuracy c) Defining maximum memory for a single interaction d) Limiting training data size Answer: c 05. When designing prompts for image and audio generation, practitioners often adjust structure differently than for text-only tasks. This is because multimodal outputs require clearer intent signaling. What is the main reason for this difference? a) Multimodal models ignore constraints PDF 810-110 AI Technical Practitioner Sample Questions 5 b) Token limits do not apply to images or audio c) Few-shot prompting is unsupported d) Non-text outputs require precise guidance on format and attributes Answer: d 06. Security teams often restrict training or prompting AI models with sensitive customer data. This reduces risk but may limit usefulness. What is the primary trade-off being managed? a) Performance versus privacy b) Speed versus accuracy c) Automation versus scalability d) Cost versus latency Answer: a 07. Bias in AI systems can lead to unfair or harmful outcomes, particularly when models are used in decision-support roles. Organizations must address this risk proactively. Which action most directly helps mitigate bias? a) Increasing inference speed b) Auditing training and input data for representation gaps c) Expanding context window size d) Disabling model logging Answer: b 08. Why is explainability particularly important when AI systems support human decision-making? Decision-makers must trust and understand recommendations before acting on them. a) It increases model speed b) It enables informed oversight and challenge c) It reduces infrastructure cost d) It eliminates bias entirely Answer: b 09. Misinformation generated by AI systems poses reputational and operational risks. This risk increases when outputs are shared without verification. Which mitigation strategy best addresses this concern? a) Human-in-the-loop validation b) Autonomous deployment without review c) Larger context windows d) Reduced logging PDF 810-110 AI Technical Practitioner Sample Questions 6 Answer: a 10. An AI practitioner is assessing threats unique to AI systems rather than traditional IT systems. They want to focus on risks introduced by generative capabilities. Which threat is AI-specific? a) Network congestion b) Hardware failure c) Distributed denial-of-service d) Prompt injection Answer: d Not every IT certification is intended for professionals, but Cisco certification is a great deal. After achieving this Cisco 810-110, you can grab an opportunity to be an IT professional with unique capability and can help the industry or get a good job. Many individuals do the Cisco certifications just for the interest, and that payback as a profession because of the worth of this course.