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Cisco 300-735 Exam Prep Course (Premium File)
AI-Powered Automating Cisco Security Solutions (SAUTO) Exam - Pass on Your First Try

Last updated on Apr 06, 2026

300-735 Practice Exam
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300-735 Package
Premium File (PDF): 110 Questions
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AI Teaching Assistant: Included
Duration & Delievery: Self Paced
Last Updated: 06-Apr-2026
Free Updates: 60 Days
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All Automating Cisco Security Solutions (SAUTO) certification learning material, study guide, training courses are created by a team of Cisco training experts. The Study Guide and .EXM training software files contain relevant Automating Cisco Security Solutions (SAUTO) content, labs, practice questions and explanation. This 300-735 exam guide and training courses is based on the latest exam outlines available!

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Automating Cisco Security Solutions (SAUTO) Study package designed to help you confidently pass your exam.

The 300-735 Exam Prep Features:

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Preparing and Passing the Cisco® 300-735 Exam

Are you aspiring to enhance your networking skills and pursue a career in network automation? The Cisco® 300-735 Automating Cisco Security Solutions (SAUTO) exam is an excellent opportunity to validate your knowledge and expertise in this field. In this article, we will provide you with the most accurate and up-to-date information about the exam, along with actionable tips to help you prepare effectively and increase your chances of success.

About the Cisco® 300-735 Exam

The Cisco® 300-735 SAUTO exam is part of the Cisco Certified DevNet Specialist - Security Automation and Programmability certification track. This exam is designed to evaluate your skills in implementing automated security solutions using Cisco security products, APIs, and platforms.

Here are some key details about the exam:

  • Exam Name: Automating Cisco Security Solutions (SAUTO)
  • Exam Code: 300-735 SAUTO
  • Exam Duration: 90 minutes
  • Exam Format: Multiple choice (single and multiple answers), drag-and-drop, simulation, and testlet
  • Exam Cost: The exam cost may vary depending on your location. It is recommended to visit the official Cisco® website for the most accurate pricing information.

Exam Objectives

To effectively prepare for the Cisco® 300-735 exam, it is crucial to have a clear understanding of the exam objectives. The following topics are covered in the exam:

  1. Utilize APIs and automation protocols
  2. Implement automation for Cisco Security platforms
  3. Implement event-driven workflows
  4. Implement automation for security policies and procedures
  5. Implement automation for mitigation techniques

Preparing for the Exam

Proper preparation is key to passing the Cisco® 300-735 exam. Here are some actionable tips to help you get ready:

  1. Review the Official Exam Blueprint: Start by thoroughly reviewing the official exam blueprint provided by Cisco®. This document outlines the exam objectives and the topics you need to focus on during your preparation.
  2. Study Official Documentation: Cisco® provides comprehensive documentation and guides for their security products and APIs. Familiarize yourself with these resources, including configuration guides, API reference documentation, and developer guides.
  3. Hands-on Experience: Gain practical experience by setting up a lab environment to work with Cisco security products and automation tools. Practice implementing various security solutions and automating security tasks.
  4. Training Courses: Consider enrolling in official Cisco® training courses or online learning platforms that offer courses specifically designed for the exam. These courses provide structured learning and cover the necessary topics in depth.
  5. Practice with Sample Questions: Use practice exams and sample questions to assess your knowledge and identify areas that require further study. Cisco® offers official practice exams that simulate the exam environment.
  6. Join Study Groups and Communities: Engage with fellow students and professionals studying for the same exam. Participating in study groups and online communities can provide valuable insights, resources, and support.

Exam Day Tips

To perform your best on the day of the exam, consider the following tips:

  1. Review Exam Policies: Familiarize yourself with the exam policies and procedures outlined by Cisco®. Understand the rules regarding the use of external materials, breaks, and time management.
  2. Arrive Early: Plan to arrive at the exam center well ahead of your scheduled exam time. This allows you to settle in, relax, and minimize any last-minute stress.
  3. Read Questions Carefully: Take your time to read and understand each question before selecting an answer. Pay attention to keywords and any specific requirements mentioned in the question.
  4. Manage Your Time: The Cisco® 300-735 exam has a time limit, so manage your time wisely. If you encounter a difficult question, flag it for review and move on. Come back to it later if you have time remaining.
  5. Stay Calm and Focused: Maintain a calm and focused mindset throughout the exam. Avoid unnecessary stress and trust in your preparation. Take short breaks if needed to regain concentration.
  6. Review Your Answers: If time permits, review your answers before submitting the exam. Check for any mistakes or inaccuracies that you may have made during the initial attempt.

By following these tips and dedicating ample time to studying and hands-on practice, you can increase your chances of passing the Cisco® 300-735 SAUTO exam and obtaining the Cisco Certified DevNet Specialist - Security Automation and Programmability certification. Best of luck on your exam!

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VirtuLearn AI

Question 25:

  • Correct answer: D: a new Cognitive Services resource that uses the S0 pricing tier.

  • Why: To enable OCR and text analytics in a Cognitive Search enrichment pipeline, you must attach a Cognitive Services resource to the skillset. For cost efficiency on a large document set, choose the base standard tier (S0) rather than higher tiers or a free tier, which may limit enrichments. The OCR capability comes from the Cognitive Services (Computer Vision/Read) and the S0 tier provides a balance of capability and cost.

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Question 20:

  • Correct answer: D and E.

  • Why: Provisioning a QnA Maker service creates:
- Azure App Service to host the QnA Maker web API (your App Service Plan AP1 will host the App Service resource). - Azure Cognitive Search to enable fast search over the knowledge base.
  • Why not the others:
- Language Understanding, Azure SQL Database, and Azure Storage are not automatically created by QnA Maker provisioning.
  • Quick note: After provisioning, check RG1 to verify the new App Service and Cognitive Search resources.

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what if different between speech recognizer and speach synthesizer

  • Speech Recognizer (Speech-to-Text): Converts audio input (live mic or audio file) into text. Output is transcripts with timestamps, confidence scores, and optional punctuation. Use cases: meeting transcripts, voice commands, real-time captions.

  • Speech Synthesizer (Text-to-Speech): Converts text (or SSML) into audio output. Output is audio data (wav/mp3 or streaming). Use cases: voice prompts, IVR responses, accessibility narrations. You can choose voices, languages, and adjust prosody (rate, pitch, volume).

  • Key differences:
- Input: Recognizer takes audio; Synthesizer takes text/SSML. - Output: Recognizer ? text; Synthesizer ? audio. - Features: Recognizer provides transcripts and timing; Synthesizer provides customizable voices (neural, SSML), multiple languages. - Typical scenarios: Transcription vs. generating spoken content.
  • Quick example: Use Speech Recognizer to transcribe a meeting; use Speech Synthesizer to read a script aloud in a chosen voice.

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Question 17:

  • Correct answer: A Anomaly Detector.

  • Why: Anomaly Detector is designed to identify unusual values in time-series data. Your scenario has 100 machines × 50 sensors, generating minute-by-minute data, totaling 5,000 time-series. Anomaly Detector can process each time-series (or batches of series) to flag deviations that may indicate potential failures, which is exactly what you need for predictive maintenance.

  • Why not the others:
- Cognitive Search is for indexing and querying content, not for detecting anomalies in time-series data. - Form Recognizer extracts data from forms, not time-series sensor data. - Custom Vision analyzes images, not numeric sensor streams.
  • Practical note: with 5,000 time series, you’d typically run anomaly detection per series (potentially in parallel) and aggregate results to identify which machines/sensors warrant attention.

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Question 12:

  • Correct answers: A, B, F.

  • Why:
- A. The index size will increase. Enabling CMK encryption adds encryption metadata and key management data, which increases index size. - B. Query times will increase. Encryption/decryption overhead and key retrieval can slow queries. - F. Azure Key Vault is required. CMK means you store/manage keys in Key Vault; it’s a billable, required service for CMK.
  • Why the other options are incorrect:
- C (self-signed X.509 certificate required) is not a requirement for CMK. - D (index size will decrease) and E (query times will decrease) contradict the expected impact of CMK.

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VirtuLearn AI

GIF also we are using ?

  • No, GIF is not supported for Form Recognizer input. The allowed formats are JPG, PNG, PDF (text or scanned), or TIFF.
  • If you have GIFs, convert them to one of the supported formats (e.g., convert to JPG/PNG or PDF) before training or uploading.
  • Also ensure each file is under 50 MB and, when possible, use text-embedded PDFs to reduce errors.

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Question 11:

  • Correct answers: A, C, F.

  • Why:
- Form Recognizer accepts documents in these formats: JPG, PNG, PDF (text or scanned), or TIFF. (TIFF is sometimes used in archival/scanned docs.) - Text-embedded PDFs are preferred because they minimize character extraction and location errors. - Training data must be under 50 MB per file.
  • So A, C, and F are the three files that meet these input requirements; the other options (B, D, E) likely fail one of the criteria (wrong format or too large). If you want, describe the formats of A, C, and F to confirm they meet all three criteria.

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Question 10:
The correct answer is B: A new query key was generated.
Explanation:

  • The REST call to:
POST .../regenerateKey?api-version=2017-04-18 with body {"keyName": "Key2"} regenerates the specified account key.
  • Since you specified Key2, only the secondary key is regenerated; the primary key (Key1) remains unchanged.
  • This operation updates the Cognitive Services account keys within Azure, not anything in Azure Key Vault.
  • “Query key” refers to the key used to authorize API requests to the service (subscription key), so regenerating Key2 yields a new value for that key.

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Why pull first, its create is first is it
Yes. The sequence is correct because you need a base image first.

  • Step 1: Pull the base container image (Anomaly Detector) to have a starting point.
  • Step 2: Create a Dockerfile to capture the exact changes you want (reproducible build).
  • Step 3: Build and push the customized image to Azure Container Registry (ACR).
  • Step 4: Distribute a docker run script to deploy the container on devices.

Why not start with the Dockerfile? You need the base image to reference in the FROM line, and you can only push a built image to ACR, not an unbuilt modification.

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Question 5:

  • In Azure Resource Manager (ARM) REST APIs, creating or updating a resource is done with a PUT request to the resource’s exact URL (idempotent operation). This means you can repeatedly call the same PUT and it will create the resource if it doesn’t exist or update it if it does.
  • POST is used to create resources under a collection (without a predefined name), which would generate a new resource id each time and is not suitable when you need a single, known resource name and a single endpoint/key to consolidate billing and access.
  • For Question 5, you’re creating a new resource at a specific path (with a known resource name) to provide a single key/endpoint for multiple services. Therefore, PUT is the correct method.

If you’d like, I can outline the exact REST call structure (URL, headers, and body) for creating the Cognitive Services/related resource using PUT.

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