Become an Azure AI Expert: Free Exam Questions and Answers
Table of Contents
- Introduction
- AI 102 Real Exam Questions
- Getting the PDF of the Video
- Building a Chatbot
- Developing a Sales System
- Containerized Deployment
- Custom Form Recognizer Model
- Responsible AI Principles
- Container Hosting Options
- App and Service Configuration
- Cognitive Services Integration
- Monitoring and Anomaly Detection
- Analyzing Images and Text
- Azure Cognitive Search
- AI Solution for Staff Compliance
- Application Insights and Metrics
- Image Analysis and Color Detection
- Confidential Document Processing
- Azure Private Link Setup
- Query Volume and Throttling
- OCR for Extracting Text
- Sentiment Analysis and Responsible AI
- Hosting Cognitive Services Model
- Azure Container Instances
- Custom Language Understanding Model
- Indexing and Querying Data
- Monitoring Anomalies in Sensor Data
- Detecting People in Video
- Language Understanding Contributors
- Receipt Analysis with Form Recognizer
- Optical Character Recognition (OCR)
- Sentiment Analysis for Bonus Calculation
AI 102 Real Exam Questions
In this section, we will cover the AI 102 real exam questions. These questions are important for your AI 102 certification exam. Make sure to watch the entire video to answer these questions correctly.
Question 1: Building a Chatbot
Question 2: Receipt Information Extraction
Question 3: Responsible AI Principles
Question 4: Containerized Deployment on Local Devices
Question 5: Custom Form Recognizer Training
Question 6: Equitable Results Monitoring
Question 7: Throttling of Query Requests
Question 8: Detecting People in Video Feed
Question 9: Container Deployment Steps
Question 10: Language Understanding Contributors
Question 11: Receipt Data Extraction with Form Recognizer
Question 12: Enrichment Pipeline Configuration
Question 13: Image Analysis API Usage
Question 14: Personal Protective Equipment Compliance
Question 15: Index Configuration for Azure Cognitive Search
Question 16: Sensor Data Anomaly Detection Monitoring
Question 17: Vision Impaired Output from Image Analysis
Question 18: Detecting Background Color in Image
Question 19: Sentiment Analysis for Staff Bonuses
Question 20: Applying Responsible AI Principles
Question 21: Azure Cognitive Search Traffic Routing
Question 22: Multi-Volume Anomaly Detection
Question 23: Azure Cognitive Services Usage
Question 24: Azure Cognitive Search Secure Access
Question 25: Anomaly Detection in Entire Data Set
Question 26: Secure Access to Cognitive Search
Question 27: Reducing Throttling of Query Requests
Question 28: Migrating to Higher Tier for Query Volume
Question 29: AI Solution App Deployment
Question 30: Extracting Text from Handwritten Images
Question 31: Dominant Background Color Detection
Article
Introduction
Hello everyone and welcome to S IQ! In this article, we will cover the most important and repeating questions from the AI 102 certification exam. This article will help You prepare for the exam and enhance your knowledge in the field of AI. We will also provide you with information on how to access the PDF version of the video containing these questions. So, let's get started!
AI 102 Real Exam Questions
The AI 102 certification exam consists of 40 important questions that cover various topics related to AI. These questions are designed to test your knowledge and understanding of AI concepts, principles, and technologies. To successfully pass the exam, it is essential to thoroughly study and comprehend these questions. In the following sections, we will discuss each question in Detail, providing solutions and explanations.
Getting the PDF of the Video
If you are interested in getting the PDF version of the video containing the 40 most important questions of the AI 102 exam, follow these simple steps:
- Subscribe to our Channel and like the video to Show your support.
- Comment down the correct answer to the two questions asked at the end of the video.
By following these steps, you will receive the PDF containing the questions. Make sure to watch the complete video to correctly answer the questions and increase your chances of receiving the PDF.
Building a Chatbot
Question 1: You need to build a chatbot that meets specific requirements. The options provided include Q&A Maker, Language Understanding, and Dispatch. Based on the requirements, the correct option is Language Understanding, Text Analytics, and Q&A Maker. Language Understanding (LU) allows users to Interact with your application and IoT devices using natural language. Q&A Maker is a cloud-based natural language processing service that creates a conversational layer over your data. Text Analytics provides insights into unstructured text using sentiment analysis.
Developing a Sales System
Question 2: Your company wants to reduce the time it takes for employees to log receipts in expense reports. The solution must minimize development effort. The correct option is Form Recognizer, which identifies and extracts text, key-value pairs, tables, and structures from documents. It provides structured data and supports OCR, reducing manual intervention.
Containerized Deployment
Question 4: You plan to use containerized versions of the Anomaly Detector API on local devices and on-premises data centers. To meet the specified requirements, you should perform the following actions in sequence: pull the anomaly detector container image, Create a custom Docker file, build the image, and push it to an Azure container registry. This ensures that billing information is not stored in command line histories and access to container images is controlled using Azure role-based access control.
Custom Form Recognizer Model
Question 5: You are developing a sales system that will process video and text from a public-facing Website. You need to monitor the system to ensure equitable results for all users, regardless of their location or background. The responsible AI principles that provide guidance for meeting these monitoring requirements are fairness and reliability/safety.
Responsible AI Principles
Question 6: You are developing a monitoring system for staff compliance with personal protective equipment requirements. The responsible AI principle that ensures equitable results for all employees, regardless of their actions, is fairness.
Question 7: You plan to enable server-side encryption and use customer-managed keys stored in Azure for your Azure Cognitive Search instance. The three implications of this plan change that meet the monitoring requirements are fairness, reliability and safety.
Container Hosting Options
Question 8: You plan to perform predictive maintenance using IoT sensor data. Anomal Detector is the appropriate service to identify unusual values in each time series and help predict machinery failures.
Question 9: You are developing an internet-based training solution that detects remote learners' presence and Attention. For the learner's video feed, you should use the Face API to verify their presence. For the learner's facial expression in the video feed, you should use the Face API to verify their attention. These options ensure accuracy and minimize development effort.
App and Service Configuration
Question 10: You plan to provision a Q&A Maker service in a new resource group. When you provision the Q&A Maker service, Azure Cognitive Search and Azure App Service resources are automatically created in the same resource group. This simplifies the provisioning process and ensures that all necessary resources are available for the Q&A Maker service.
Question 11: You are building a language model using a Language Understanding service. To add more contributors, you should use the access control page for authoring the resources in the Azure portal. This allows you to manage access and permissions for contributors working on the language model.
Cognitive Services Integration
Question 12: You have receipts accessible from a URL and need to extract data from them using Form Recognizer and the SDK. The correct client and method to use are the FormRecognizerClient and the StartRecognizeReceiptsFromUri method. This ensures that a pre-built model is used for extracting information from the receipts.
Monitoring and Anomaly Detection
Question 17: You have an Azure Cognitive Search solution and a collection of blog posts with a category field. To index the posts and meet the search result requirements, you should configure the category field with the attributes "retrievable, filterable, and sortable". This ensures that the category field is included in the search result list and allows users to search for words in the category field and perform drill-down filtering based on category.
Question 18: You have an Azure Cognitive Search solution that indexes purchase orders using Form Recognizer. To analyze the extracted information using PowerBI, you should add an object projection to the indexer. This allows the extracted information to be included in the search result and can be used for analysis in PowerBI.
Analyzing Images and Text
Question 19: You have an app that analyzes images using the Computer Vision API. To detect the presence of people in a video feed, you should use the Special Analysis feature. This feature provides Spatial analysis capabilities to detect whether people are present in the video.
Question 20: You are building an AI solution that uses sentiment analysis results to calculate bonuses for customer service staff. To meet the responsible AI principle, you should add a human review and approval step before making decisions that affect the staff's financial situation. This ensures that human judgement is considered in decisions impacting the staff's financial well-being.
Deployment and Configuration
Question 21: You have an Azure subscription that contains a Language Understanding service resource and a virtual network. To ensure that only resources in the virtual network can access the Language Understanding service, you should configure the virtual network settings for the Language Understanding resource. This restricts network access and enhances security.
Question 22: You are developing a monitoring system that analyzes engine sensor data. To perform atypical value detection across multiple correlated sensors and identify the root cause of process stops, you should use multivariate anomaly detection. This AI service provides advanced anomaly detection capabilities for analyzing sensor data.
Optical Character Recognition (OCR)
Question 30: You are building an app that will use Azure Computer Vision to extract text from scanned images of handwritten text. The correct computer vision feature to use is Optical Character Recognition (OCR). This feature enables extraction of text from images, including handwritten text.
Sentiment Analysis and Responsible AI
Question 31: You are building an app that will use sentiment analysis results from a service to calculate bonuses for customer service staff. To ensure compliance with the Microsoft responsible AI principle, you should add a human review and approval step before making decisions that affect the staff's financial situation. This provides an additional layer of oversight and accountability in decision-making.
Highlights
- The AI 102 real exam questions cover a diverse range of topics related to AI.
- Understanding responsible AI principles is crucial for meeting compliance requirements.
- Containerization provides flexibility and scalability for deployment.
- Form Recognizer is a powerful tool for extracting information from documents.
- Azure Cognitive Search enables efficient indexing and querying of data.
- Server-side encryption and customer-managed keys enhance data security.
- Optical Character Recognition (OCR) is vital for extracting text from images.
- Sentiment analysis can be used to drive decision-making processes.
- Continuous monitoring and anomaly detection ensure system reliability.
- Integration of AI services requires proper configuration and access control.
FAQs
Q: How can I access the PDF version of the video with the AI 102 real exam questions?
A: To access the PDF version, subscribe to our channel, like the video, and comment the correct answers to the questions asked at the end of the video.
Q: Is it necessary to consider responsible AI principles in AI development?
A: Yes, responsible AI principles ensure fair, reliable, and safe usage of AI technologies, promoting ethics and accountability.
Q: What is the recommended approach for deploying AI models?
A: Containerization using Azure Container Instances provides a lightweight, scalable, and cost-effective solution for hosting AI models.
Q: How can Azure Cognitive Search enhance data indexing and querying?
A: Azure Cognitive Search allows efficient indexing and querying of structured and unstructured data, providing powerful search capabilities to applications.
Q: Why is sentiment analysis important in decision-making processes?
A: Sentiment analysis provides insights into customer opinions and emotions, allowing businesses to make data-driven decisions based on customer feedback.
Q: How can monitoring and anomaly detection enhance system reliability?
A: Continuous monitoring and anomaly detection help detect and mitigate issues and anomalies in real-time, ensuring the system operates smoothly and efficiently.
Q: What are some key considerations for securing AI services?
A: Proper access control, network security, and encryption of data are essential for securing AI services and protecting sensitive information.
Q: How does Optical Character Recognition (OCR) facilitate the extraction of text from images?
A: OCR technology enables the recognition and extraction of text from images, including handwritten text, making it essential for various applications such as document analysis and data extraction.
Q: Why is it important to consider responsible AI principles in decision-making processes?
A: Responsible AI principles promote fairness, accountability, and transparency, ensuring that AI systems treat all individuals fairly and make reliable and safe decisions.
Q: Why is continuous monitoring and anomaly detection important for AI solutions?
A: Continuous monitoring and anomaly detection enable identification of abnormal patterns or behaviors, ensuring the reliability and optimal performance of AI solutions.
Conclusion
In this article, we covered the AI 102 real exam questions and provided detailed explanations for each question. We discussed topics such as building chatbots, responsible AI principles, containerized deployment, form recognizer, and much more. Additionally, we highlighted the importance of understanding responsible AI principles and integrating AI services securely. We also included a list of frequently asked questions to address common queries related to AI. By thoroughly understanding these questions and concepts, you will be well-prepared for the AI 102 certification exam. Good luck!