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PMI PMI-200 Exam Prep Course (Premium File)
AI-Powered Project Management Professional (PMP)® Exam - Pass on Your First Try

Last updated on May 28, 2026

PMI-200 Practice Exam
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PMI-200 Package
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Last Updated: 28-May-2026
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All Project Management Professional (PMP)® certification learning material, study guide, training courses are created by a team of PMI training experts. The Study Guide and .EXM training software files contain relevant Project Management Professional (PMP)® content, labs, practice questions and explanation. This PMI-200 exam guide and training courses is based on the latest exam outlines available!

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Project Management Professional (PMP)® Study package designed to help you confidently pass your exam.

The PMI-200 Exam Prep Features:

  • Contains the most relevant and up to date PMI-200 study material covering all exam topics on the latest PMI-200 certification.
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How to Prepare and Pass the PMI PMI-200 Exam

Welcome to this comprehensive guide on preparing and passing the PMI PMI-200 exam! In this article, we will provide you with all the necessary information about the PMI-200 exam, including its details, requirements, and actionable tips to help you succeed. Let's dive in!

About the PMI-200 Exam

The PMI-200 exam, also known as the Project Management Institute's PMI-200 Exam, is a certification exam specifically designed for individuals aspiring to become certified project management professionals. This exam focuses on testing the candidates' knowledge and skills in the field of project management and assesses their ability to apply project management principles and practices effectively.

Exam Details

  • Exam Code: PMI-200
  • Exam Name: PMI Agile Certified Practitioner (PMI-ACP)
  • Exam Duration: 3 hours
  • Number of Questions: 120 multiple-choice questions
  • Passing Score: The passing score for the PMI-200 exam is not explicitly defined by PMI. Instead, it is determined by a psychometric analysis process.
  • Exam Fee: The exam fee varies depending on your PMI membership status. As of the latest update, the fee for PMI members is $435, while non-members need to pay $495. It's recommended to visit the official PMI website for the most up-to-date information on exam fees.

Exam Prerequisites

To be eligible for the PMI-200 exam, candidates must fulfill certain prerequisites set by PMI. Here are the prerequisites:

  • Educational Background: Candidates must have a secondary degree (high school diploma, associate's degree, or global equivalent) or higher education.
  • Project Management Experience: Candidates must have at least 2,000 hours of general project management experience, along with 1,500 hours of experience working on agile project teams or using agile methodologies.
  • Agile Project Management Training: Candidates must have completed at least 21 hours of agile project management training, which should cover topics related to agile practices, tools, and methodologies.

Preparing for the PMI-200 Exam

Preparing for the PMI-200 exam requires a systematic and focused approach. Here are some actionable tips to help you effectively prepare for the exam:

1. Understand the Exam Content Outline:

Start by familiarizing yourself with the exam content outline provided by PMI. The outline highlights the domains, tasks, and knowledge areas covered in the exam. Understanding the content outline will give you a clear roadmap of what to expect and where to focus your studies.

2. Study the PMI Agile Practice Guide:

The PMI Agile Practice Guide is a valuable resource for preparing for the PMI-200 exam. It provides a comprehensive overview of agile principles, methodologies, and tools. Study this guide thoroughly to enhance your understanding of agile project management practices.

3. Utilize Recommended Study Materials:

PMI recommends using specific study materials to prepare for the PMI-200 exam. These materials include books, practice exams, and online courses. Explore the PMI website to access the recommended study resources and choose the ones that align with your learning preferences.

4. Join Study Groups or Forums:

Engaging with fellow exam aspirants through study groups or online forums can be highly beneficial. It allows you to discuss concepts, share study resources, and gain insights from others' experiences. Consider joining PMI forums or local study groups to enhance your learning process.

5. Take Practice Exams:

Practice exams are an excellent way to assess your knowledge and familiarize yourself with the exam format. PMI provides sample questions and practice exams that simulate the actual exam environment. Make sure to time yourself and review the explanations for both correct and incorrect answers.

6. Create a Study Schedule:

Develop a study schedule that suits your routine and allows you to allocate dedicated time for exam preparation. Breaking down your study material into smaller sections and setting milestones will help you stay organized and track your progress effectively.

7. Review and Revise:

Regularly review the topics you've studied to reinforce your understanding. Identify areas where you need improvement and revisit those topics. Focus on clarifying your concepts and ensure you can apply them to real-life project management scenarios.

8. Stay Calm and Confident:

On the day of the exam, remember to stay calm and confident. Proper rest, a healthy breakfast, and positive self-talk can help alleviate exam anxiety. Trust in your preparation and believe in your abilities to perform well.

Conclusion

The PMI PMI-200 exam is a significant step towards becoming a certified project management professional. By understanding the exam details, fulfilling the prerequisites, and following the actionable tips provided in this article, you can be well-prepared to tackle the exam with confidence. Remember to utilize the official PMI resources and stay updated with the latest information from the PMI website. Best of luck in your journey towards achieving the PMI Agile Certified Practitioner (PMI-ACP) certification!

Disclaimer: This article provides general information about the PMI PMI-200 exam based on the knowledge available up to September 2021. It's recommended to visit the official PMI website for the most accurate and up-to-date information regarding the exam.

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Question 33:

  • Correct concept: The Weather.Historic entity corresponds to the text "by month" in the utterance.

  • Why: The sample export shows the entity spans characters 23 to 31, and the substring in that span is "by month." In LU/LUIS, an entity's value is the exact text matched in the utterance; startIndex/endIndex (or startPos/endPos in older versions) indicate where that text appears.

  • Key takeaway: Weather.Historic is the phrase "by month" extracted from the user input, not the numeric value or a separate label. The positions illustrate where the entity text is located within the utterance.

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Question 61:

  • Correct answer: Run the Bot Framework Emulator.

  • Why: When you start a bot locally, the Emulator is the standard tool to validate and debug your bot without publishing it. It lets you connect to your local endpoint (e.g., http://localhost:3978/api/messages), send test messages, inspect requests/responses, and verify dialogs and state.

  • What to expect: You can test conversation flows, activities, and debugging traces, ensuring the bot behaves as intended before connecting to any Azure channels.

  • Why the other options aren’t correct for this step:
- Bot Framework Composer is for designing and managing bot flows, not the primary local validation step before connecting to the bot. - Register the bot with Azure Bot Service is for deployment to Azure channels, not for initial local validation. - Run Windows Terminal is just a command shell and does not validate bot functionality.

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VirtuLearn AI

Question 51:

  • Correct answer: Waterfall and Prompt dialogs (options C and D).

Explanation:
  • WaterfallDialog provides a simple, linear sequence of steps to collect multiple inputs. You can branch the flow based on the item type and decide which steps to execute next.
  • Prompt dialogs (e.g., TextPrompt, NumberPrompt) handle asking for input and basic validation, reducing custom parsing code.
  • Using a waterfall flow with prompts lets you minimize development effort: you define the sequence once and use prompts to gather the required details for each item type, rather than building complex adaptive logic.

Singapore, Singapore

VirtuLearn AI

Question 35:

  • Correct answer: Waterfall (option C), i.e., use a WaterfallDialog.
  • Why: A product setup process is a linear, guided flow. A WaterfallDialog runs a fixed sequence of steps (prompts, validations, and results) in order, which is ideal for collecting setup details step-by-step and finalizing the configuration.
  • How it works:
- Define a list of steps (e.g., gather product type, collect settings, confirm, complete). - Each step can prompt the user, validate input, store results, and proceed to the next step. - End after the final step.
  • Why not the others:
- ComponentDialog: groups multiple dialogs but isn’t inherently linear. - AdaptiveDialog: more flexible/dynamic; used for complex, context-aware flows. - “Action” isn’t a standard dialog type for this purpose.
In short, for a straightforward, guided setup flow, a WaterfallDialog is the most appropriate choice.

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Question 34:
Correct answers: Adaptive Card (D) and Dialog (E).
Explanation:

  • Adaptive Card: Lets you render rich content, including multiple options each with an image. You can include images for every option and actions (like Submit) to capture the user’s choice.
  • Dialog: Provides the flow control to show the card, wait for the user to pick an option, and then branch to the appropriate next steps. It manages multi-turn interactions and state.

Why the other options don’t fit:
  • an entity: Used for extracting data from user input, not for presenting options with images.
  • an Azure function: Backend code, not for UI presentation.
  • an utterance: A user input phrase, not for building the option list.

So, to present a list with images and handle selections in Bot Framework Composer, use an Adaptive Card to display the options and a Dialog to manage the interaction.

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Question 76:

  • Correct answer: Spatial Analysis in Azure AI Vision

  • Why this is correct:
- You need to verify the user is alone in the camera frame. Spatial Analysis in Azure AI Vision can analyze a video stream to detect and count people in a scene and understand their spatial relationships. This directly supports determining whether more than one person is present, which matches the “user alone” requirement. - It minimizes development effort because it provides built-in scene understanding for video, unlike other options that would require additional training or separate services.
  • Why not the others:
- Speech-to-text in Azure AI Speech focuses on transcribing audio, not detecting other people in the video. - Object detection in Azure AI Custom Vision would require labeling and training a model to detect people, which adds work. - Object detection in Azure AI Vision (non-spatial) can detect objects but isn’t as targeted for counting people and analyzing their spatial arrangement as the dedicated Spatial Analysis feature.
  • Quick implementation note:
- Use the video pipeline’s spatial analysis capability to count people per frame over time; trigger a warning or block access if the count exceeds 1.

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Question 72:
Question 72 asks which Python package to add to App1 to use an Azure AI service model (Model1) that identifies text intent.

  • Correct answer: azure-ai-language-conversations (Option B)

Why:
  • The task uses the Language Service’s Conversation Analysis feature to identify intent from text. The appropriate Python SDK to call a deployed Conversation model is the azure-ai-language-conversations package.
  • Other options are for different capabilities:
- azure-cognitiveservices-language-textanalytics is the older Text Analytics API (sentiment, key phrases, etc.), not for custom intent models. - azure-mgmt-cognitiveservices is for resource management, not calling models. - azure-cognitiveservices-speech is for Speech services (speech-to-text, etc.), not text intent.
Practical note (conceptual):
  • Install: pip install azure-ai-language-conversations
  • Use the ConversationAnalysisClient to call your deployed model (

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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.

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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.

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