Last updated on Jun 09, 2026
All GMAT Section 3: Verbal Ability certification learning material, study guide, training courses are created by a team of GMAT training experts. The Study Guide and .EXM training software files contain relevant GMAT Section 3: Verbal Ability content, labs, practice questions and explanation. This GMAT SECTION 3: VERBAL ABILITY exam guide and training courses is based on the latest exam outlines available!
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The GMAT (Graduate Management Admission Test) is a standardized exam designed to assess the skills required for success in business and management programs. The Verbal Ability section of the GMAT evaluates a student's proficiency in understanding and analyzing written English. It consists of questions that test reading comprehension, critical reasoning, and sentence correction abilities. To excel in this section, it is essential to have a strong command of the English language and effective strategies for tackling the various question types.
The GMAT Verbal Ability section comprises three question types:
Effective preparation is crucial for success in the GMAT Verbal Ability section. Here are some actionable tips to help you prepare and perform your best:
By following these tips and committing to consistent and focused preparation, you can increase your chances of performing well in the GMAT Verbal Ability section. Remember to stay disciplined, manage your time effectively during the exam, and maintain a positive mindset. Good luck!
Question 61: Correct answer: Azure Cognitive Services. Why: A single multi-service Azure Cognitive Services resource provides one endpoint and one credential that can be used to access multiple APIs (e.g., Decision and Language, plus others like Content Moderator). This meets the requirement of using a single endpoint/credential. Why not the others: If you created separate resources for each API (e.g., separate Language, Speech, Content Moderator resources), you’d have multiple endpoints and keys, violating the “single endpoint and credential” requirement. All listed services are part of Cognitive Services, so they share a single Cognitive Services resource.
Question 61:
Azure Cognitive Services
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Question 28:Answer: C — Computer Vision image analysis Explanation: To generate image tags in multiple languages with minimal development, use the Image Analysis endpoint of the Computer Vision service. Call the API (Analyze Image) with visualFeatures=Tags and specify the language parameter (e.g., language=en, language=fr, language=es). The response returns tags with names localized to the requested language. This approach requires no custom model training, unlike Custom Vision image classification, which would require building and tagging a dataset. Other options: - Content Moderator is for content safety/moderation, not tagging. - Image Moderation endpoints focus on inappropriate content. - Custom Translator translates text, not image tags. In short, use the Image Analysis endpoint to get language-localized tags with minimal effort.
Question 28:Answer: C — Computer Vision image analysis Explanation:
Image Analysis
visualFeatures=Tags
language
language=en
language=fr
language=es
tags
Question 61: Correct answer: A. Run the Bot Framework Emulator. Why: The Bot Framework Emulator lets you test and validate a locally running bot before connecting to any channels. It lets you simulate conversations, inspect requests/responses, view state, and debug dialog flows in real time. Why the other options are not correct for pre-connection validation: - Bot Framework Composer is a design/authoring tool, not a local validation tool for a running bot. - Registering the bot with Azure Bot Service is for cloud deployment, not for initial local validation. - Windows Terminal is just a shell; it doesn’t provide bot testing capabilities. Quick steps (before connecting to channels): - Install and run the bot locally (e.g., dotnet run or npm start). - Start the Bot Framework Emulator and connect to your bot’s local endpoint (typically http://localhost:3978/api/messages with any app credentials as needed). - Validate conversations, dialogs, and state to ensure correct behavior prior to deployment.
dotnet run
npm start
http://localhost:3978/api/messages
Question 10:Correct answer: B. A new query key was generated. Explanation: The REST call uses POST to .../regenerateKey with body {"keyName": "Key2"}. This regenerates only the specified key (Key2) for the given Cognitive Services account. The value of Key2 changes to a new secret; Key1 remains unchanged. It does not rotate both keys, nor does it involve Azure Key Vault. After regenerating, update your client applications to use the new Key2 value to continue authenticating.
Question 10:Correct answer: B. A new query key was generated. Explanation:
.../regenerateKey
{"keyName": "Key2"}
Question 57:In question 57, after a new feature release users experience latency at login. The first action should be to rollback the recent release to the previous stable version. Why: Rolling back quickly restores service and user experience, minimizing impact (blast radius) while you investigate the root cause. It buys time to diagnose whether the regression was introduced by the new release. Why not the other options as the first step: Review Stackdriver monitoring is important for diagnosis, but it doesn’t immediately restore service to normal. Do it after rollback or in parallel to triage. Upsize the VMs may help temporarily but does not address the underlying issue and isn’t a guaranteed fix. Deploy a new release could reintroduce the problem or delay stabilization. Best practice tip: use feature flags or canary deployments so you can rollback a feature with minimal impact, and have a defined rollback playbook for fast incident response.
Question 57:In question 57, after a new feature release users experience latency at login. The first action should be to rollback the recent release to the previous stable version. Why:
Hi, when I click on Practice online it sends me to the free test is this right? is there a Mac OS of Xengine Thanks Mark
Question 2: Correct option: C — the models are PA-3260, PA-5410, PA-850, and PA-460. Why: ARE requires PAN-OS 11.0+ and hardware that supports the feature. ARE is available on the PA-3200 Series, PA-5400 Series, PA-800 Series, and PA-400 Series. That includes: - PA-3260 (PA-3200 family) - PA-5410 (PA-5400 family) - PA-850 and PA-460 (PA-800/PA-400 families) What to do in practice: - Ensure PAN-OS 11.0+ is running. - Apply the ARE license. - Enable ARE on the relevant logical router to use advanced routing features (e.g., enhanced BGP/OSPF). Why other choices are incorrect: those models fall outside the ARE-supported families or are VM/CN-Series not listed for ARE in this context.
Question 2:
Question 2: Correct answer: Set-MsolCompanySettings Why: - Self-service sign-up (SSS) is a tenant-wide setting in Azure AD/MSOL. To prevent external users from creating new accounts in your contoso.com tenant via SSS, you modify the MSOL company settings. - The cmdlet to configure these tenant-wide settings is Set-MsolCompanySettings. - The other options operate on federation settings or domain-level configurations (e.g., Set-MsolDomainFederationSettings, Update-MsolfederatedDomain, Set-MsolDomain) and do not control self-service sign-up behavior.
Set-MsolCompanySettings
Set-MsolDomainFederationSettings
Update-MsolfederatedDomain
Set-MsolDomain
Question 0:You’re right to question it, but in this exam context the correct option is A: create_resource("res1", "ComputerVision", "F0", "westus"). Why: The task is to generate captions of images, which uses the Computer Vision resource, not Custom Vision. The requirement specifies a free Azure resource, so you should use the free tier F0 in the West US region. The other options either use the wrong service (CustomVision.Prediction) or a paid tier (S0). If you’ve seen F0 not available for Computer Vision in your actual Azure portal, that’s a portal/region nuance, but for the exam scenario the expected choice is A.
Question 0:You’re right to question it, but in this exam context the correct option is A: create_resource("res1", "ComputerVision", "F0", "westus"). Why:
create_resource("res1", "ComputerVision", "F0", "westus")