Microsoft AI-900 Azure AI Fundamentals Certification Practice Exam is a comprehensive and reliable tool designed to help individuals prepare for the AI-900 certification exam. This practice exam offers a range of benefits, including the opportunity to assess one's knowledge and skills in the field of Azure AI fundamentals.
With this practice exam, individuals can gain a deeper understanding of key concepts and principles related to Azure AI, including machine learning, cognitive services, and natural language processing. The exam also provides detailed feedback and explanations for each question, allowing individuals to identify areas where they may need to focus their study efforts.
In addition, the Microsoft AI-900 Azure AI Fundamentals Certification Practice Exam is designed to simulate the actual certification exam, providing individuals with a realistic testing experience. This can help to reduce anxiety and increase confidence when it comes time to take the actual exam.
AI-900 : Microsoft Azure AI Fundamentals Exam details :
Exam Name: Microsoft Certified - Azure AI Fundamentals
Exam Code: AI-900
Exam Price: $99 (USD)
Number of Questions: Maximum of 40-60 questions,
Type of Questions: Multiple Choice Questions (single and multiple response), drag and drops and performance-based,
Length of Test: 60 Minutes. The exam is available in English and Japanese languages.
Passing Score: 700 / 1000
Languages : English, Japanese, Korean, and Simplified Chinese
Schedule Exam : Pearson VUE
AI-900 : Microsoft Azure AI Fundamentals Certification Exams skill questions:
Skill Measurement Exam Topics:-
Describe Artificial Intelligence workloads and considerations (20–25%)
Describe fundamental principles of machine learning on Azure (25–30%)
Describe features of computer vision workloads on Azure (15–20%)
Describe features of Natural Language Processing (NLP) workloads on Azure (25–30%)
##) Describe Artificial Intelligence workloads and considerations (20–25%)
Identify features of common AI workloads
Identify features of anomaly detection workloads
Identify computer vision workloads
Identify natural language processing workloads
Identify knowledge mining workloads
Identify guiding principles for responsible AI
Describe considerations for fairness in an AI solution
Describe considerations for reliability and safety in an AI solution
Describe considerations for privacy and security in an AI solution
Describe considerations for inclusiveness in an AI solution
Describe considerations for transparency in an AI solution
Describe considerations for accountability in an AI solution
##) Describe fundamental principles of machine learning on Azure (25–30%)
Identify common machine learning types
Identify regression machine learning scenarios
Identify classification machine learning scenarios
Identify clustering machine learning scenarios
Describe core machine learning concepts
Identify features and labels in a dataset for machine learning
Describe how training and validation datasets are used in machine learning
Describe capabilities of visual tools in Azure Machine Learning Studio
Automated machine learning
Azure Machine Learning designer
##) Describe features of computer vision workloads on Azure (15–20%)
Identify common types of computer vision solution
Identify features of image classification solutions
Identify features of object detection solutions
Identify features of optical character recognition solutions
Identify features of facial detection and facial analysis solutions
Identify Azure tools and services for computer vision tasks
Identify capabilities of the Computer Vision service
Identify capabilities of the Custom Vision service
Identify capabilities of the Face service
Identify capabilities of the Form Recognizer service
##) Describe features of Natural Language Processing (NLP) workloads on Azure (25–30%)
Identify features of common NLP Workload Scenarios
Identify features and uses for key phrase extraction
Identify features and uses for entity recognition
Identify features and uses for sentiment analysis
Identify features and uses for language modeling
Identify features and uses for speech recognition and synthesis
Identify features and uses for translation
Identify Azure tools and services for NLP workloads
Identify capabilities of the Language service
Identify capabilities of the Speech service
Identify capabilities of the Translator service
Identify considerations for conversational AI solutions on Azure
Identify features and uses for bots
Identify capabilities of Power Virtual Agents and the Azure Bot service
Overall, the Microsoft AI-900 Azure AI Fundamentals Certification Practice Exam is an invaluable resource for anyone looking to earn their AI-900 certification. With its comprehensive coverage, detailed feedback, and realistic testing experience, this practice exam is an essential tool for success in the field of Azure AI.
Microsoft AI-900 Azure AI Fundamentals Certification Practice Exam is a comprehensive and reliable tool designed to help individuals prepare for the AI-900 certification exam. This practice exam offers a range of benefits, including the opportunity to assess one's knowledge and skills in the field of Azure AI fundamentals.
With this practice exam, individuals can gain a deeper understanding of key concepts and principles related to Azure AI, including machine learning, cognitive services, and natural language processing. The exam also provides detailed feedback and explanations for each question, allowing individuals to identify areas where they may need to focus their study efforts.
In addition, the Microsoft AI-900 Azure AI Fundamentals Certification Practice Exam is designed to simulate the actual certification exam, providing individuals with a realistic testing experience. This can help to reduce anxiety and increase confidence when it comes time to take the actual exam.
AI-900 : Microsoft Azure AI Fundamentals Exam details :
Exam Name: Microsoft Certified - Azure AI Fundamentals
Exam Code: AI-900
Exam Price: $99 (USD)
Number of Questions: Maximum of 40-60 questions,
Type of Questions: Multiple Choice Questions (single and multiple response), drag and drops and performance-based,
Length of Test: 60 Minutes. The exam is available in English and Japanese languages.
Passing Score: 700 / 1000
Languages : English, Japanese, Korean, and Simplified Chinese
Schedule Exam : Pearson VUE
AI-900 : Microsoft Azure AI Fundamentals Certification Exams skill questions:
Skill Measurement Exam Topics:-
Describe Artificial Intelligence workloads and considerations (20–25%)
Describe fundamental principles of machine learning on Azure (25–30%)
Describe features of computer vision workloads on Azure (15–20%)
Describe features of Natural Language Processing (NLP) workloads on Azure (25–30%)
##) Describe Artificial Intelligence workloads and considerations (20–25%)
Identify features of common AI workloads
Identify features of anomaly detection workloads
Identify computer vision workloads
Identify natural language processing workloads
Identify knowledge mining workloads
Identify guiding principles for responsible AI
Describe considerations for fairness in an AI solution
Describe considerations for reliability and safety in an AI solution
Describe considerations for privacy and security in an AI solution
Describe considerations for inclusiveness in an AI solution
Describe considerations for transparency in an AI solution
Describe considerations for accountability in an AI solution
##) Describe fundamental principles of machine learning on Azure (25–30%)
Identify common machine learning types
Identify regression machine learning scenarios
Identify classification machine learning scenarios
Identify clustering machine learning scenarios
Describe core machine learning concepts
Identify features and labels in a dataset for machine learning
Describe how training and validation datasets are used in machine learning
Describe capabilities of visual tools in Azure Machine Learning Studio
Automated machine learning
Azure Machine Learning designer
##) Describe features of computer vision workloads on Azure (15–20%)
Identify common types of computer vision solution
Identify features of image classification solutions
Identify features of object detection solutions
Identify features of optical character recognition solutions
Identify features of facial detection and facial analysis solutions
Identify Azure tools and services for computer vision tasks
Identify capabilities of the Computer Vision service
Identify capabilities of the Custom Vision service
Identify capabilities of the Face service
Identify capabilities of the Form Recognizer service
##) Describe features of Natural Language Processing (NLP) workloads on Azure (25–30%)
Identify features of common NLP Workload Scenarios
Identify features and uses for key phrase extraction
Identify features and uses for entity recognition
Identify features and uses for sentiment analysis
Identify features and uses for language modeling
Identify features and uses for speech recognition and synthesis
Identify features and uses for translation
Identify Azure tools and services for NLP workloads
Identify capabilities of the Language service
Identify capabilities of the Speech service
Identify capabilities of the Translator service
Identify considerations for conversational AI solutions on Azure
Identify features and uses for bots
Identify capabilities of Power Virtual Agents and the Azure Bot service
Overall, the Microsoft AI-900 Azure AI Fundamentals Certification Practice Exam is an invaluable resource for anyone looking to earn their AI-900 certification. With its comprehensive coverage, detailed feedback, and realistic testing experience, this practice exam is an essential tool for success in the field of Azure AI.
Microsoft AI-900 Azure AI Fundamentals Certification Practice Exam is a highly beneficial product for individuals seeking to enhance their knowledge and skills in the field of artificial intelligence. This practice exam is designed to provide a comprehensive understanding of the fundamental concepts and principles of Azure AI, enabling individuals to prepare for the AI-900 certification exam with confidence.
The practice exam offers a range of benefits, including the opportunity to assess one's knowledge and identify areas for improvement. It provides a realistic simulation of the actual certification exam, allowing individuals to familiarize themselves with the format and structure of the test. Additionally, the practice exam offers detailed explanations and feedback on each question, enabling individuals to learn from their mistakes and improve their performance.
The Microsoft AI-900 Azure AI Fundamentals Certification Practice Exam is an excellent resource for individuals seeking to enhance their career prospects in the field of artificial intelligence. It is a valuable tool for professionals seeking to demonstrate their expertise in Azure AI, and for organizations seeking to validate the skills of their employees. With its comprehensive coverage of the fundamental concepts and principles of Azure AI, this practice exam is an essential resource for anyone seeking to excel in the field of artificial intelligence.
AI-900 : Microsoft Azure AI Fundamentals Exam details :
Exam Name: Microsoft Certified - Azure AI Fundamentals
Exam Code: AI-900
Exam Price: $99 (USD)
Number of Questions: Maximum of 40-60 questions,
Type of Questions: Multiple Choice Questions (single and multiple response), drag and drops and performance-based,
Length of Test: 60 Minutes. The exam is available in English and Japanese languages.
Passing Score: 700 / 1000
Languages : English, Japanese, Korean, and Simplified Chinese
Schedule Exam : Pearson VUE
AI-900 : Microsoft Azure AI Fundamentals Certification Exams skill questions:
Skill Measurement Exam Topics:-
Describe Artificial Intelligence workloads and considerations (20–25%)
Describe fundamental principles of machine learning on Azure (25–30%)
Describe features of computer vision workloads on Azure (15–20%)
Describe features of Natural Language Processing (NLP) workloads on Azure (25–30%)
##) Describe Artificial Intelligence workloads and considerations (20–25%)
Identify features of common AI workloads
Identify features of anomaly detection workloads
Identify computer vision workloads
Identify natural language processing workloads
Identify knowledge mining workloads
Identify guiding principles for responsible AI
Describe considerations for fairness in an AI solution
Describe considerations for reliability and safety in an AI solution
Describe considerations for privacy and security in an AI solution
Describe considerations for inclusiveness in an AI solution
Describe considerations for transparency in an AI solution
Describe considerations for accountability in an AI solution
##) Describe fundamental principles of machine learning on Azure (25–30%)
Identify common machine learning types
Identify regression machine learning scenarios
Identify classification machine learning scenarios
Identify clustering machine learning scenarios
Describe core machine learning concepts
Identify features and labels in a dataset for machine learning
Describe how training and validation datasets are used in machine learning
Describe capabilities of visual tools in Azure Machine Learning Studio
Automated machine learning
Azure Machine Learning designer
##) Describe features of computer vision workloads on Azure (15–20%)
Identify common types of computer vision solution
Identify features of image classification solutions
Identify features of object detection solutions
Identify features of optical character recognition solutions
Identify features of facial detection and facial analysis solutions
Identify Azure tools and services for computer vision tasks
Identify capabilities of the Computer Vision service
Identify capabilities of the Custom Vision service
Identify capabilities of the Face service
Identify capabilities of the Form Recognizer service
##) Describe features of Natural Language Processing (NLP) workloads on Azure (25–30%)
Identify features of common NLP Workload Scenarios
Identify features and uses for key phrase extraction
Identify features and uses for entity recognition
Identify features and uses for sentiment analysis
Identify features and uses for language modeling
Identify features and uses for speech recognition and synthesis
Identify features and uses for translation
Identify Azure tools and services for NLP workloads
Identify capabilities of the Language service
Identify capabilities of the Speech service
Identify capabilities of the Translator service
Identify considerations for conversational AI solutions on Azure
Identify features and uses for bots
Identify capabilities of Power Virtual Agents and the Azure Bot service
Overall, the Microsoft AI-900 Azure AI Fundamentals Certification Practice Exam is an essential resource for anyone seeking to obtain the Microsoft AI-900 Azure AI Fundamentals certification. It provides a comprehensive and rigorous assessment of the candidate's knowledge and skills in the field of AI, enabling them to demonstrate their expertise and enhance their career prospects in this rapidly growing field.
Microsoft AI-900 Azure AI Fundamentals Certification Practice Exam is a highly beneficial product for individuals seeking to enhance their knowledge and skills in the field of artificial intelligence. This practice exam is designed to provide a comprehensive understanding of the fundamental concepts and principles of Azure AI, enabling individuals to prepare for the AI-900 certification exam with confidence.
The practice exam offers a range of benefits, including the opportunity to assess one's knowledge and identify areas for improvement. It provides a realistic simulation of the actual certification exam, allowing individuals to familiarize themselves with the format and structure of the test. Additionally, the practice exam offers detailed explanations and feedback on each question, enabling individuals to learn from their mistakes and improve their performance.
The Microsoft AI-900 Azure AI Fundamentals Certification Practice Exam is an excellent resource for individuals seeking to enhance their career prospects in the field of artificial intelligence. It is a valuable tool for professionals seeking to demonstrate their expertise in Azure AI, and for organizations seeking to validate the skills of their employees. With its comprehensive coverage of the fundamental concepts and principles of Azure AI, this practice exam is an essential resource for anyone seeking to excel in the field of artificial intelligence.
AI-900 : Microsoft Azure AI Fundamentals Exam details :
Exam Name: Microsoft Certified - Azure AI Fundamentals
Exam Code: AI-900
Exam Price: $99 (USD)
Number of Questions: Maximum of 40-60 questions,
Type of Questions: Multiple Choice Questions (single and multiple response), drag and drops and performance-based,
Length of Test: 60 Minutes. The exam is available in English and Japanese languages.
Passing Score: 700 / 1000
Languages : English, Japanese, Korean, and Simplified Chinese
Schedule Exam : Pearson VUE
AI-900 : Microsoft Azure AI Fundamentals Certification Exams skill questions:
Skill Measurement Exam Topics:-
Describe Artificial Intelligence workloads and considerations (20–25%)
Describe fundamental principles of machine learning on Azure (25–30%)
Describe features of computer vision workloads on Azure (15–20%)
Describe features of Natural Language Processing (NLP) workloads on Azure (25–30%)
##) Describe Artificial Intelligence workloads and considerations (20–25%)
Identify features of common AI workloads
Identify features of anomaly detection workloads
Identify computer vision workloads
Identify natural language processing workloads
Identify knowledge mining workloads
Identify guiding principles for responsible AI
Describe considerations for fairness in an AI solution
Describe considerations for reliability and safety in an AI solution
Describe considerations for privacy and security in an AI solution
Describe considerations for inclusiveness in an AI solution
Describe considerations for transparency in an AI solution
Describe considerations for accountability in an AI solution
##) Describe fundamental principles of machine learning on Azure (25–30%)
Identify common machine learning types
Identify regression machine learning scenarios
Identify classification machine learning scenarios
Identify clustering machine learning scenarios
Describe core machine learning concepts
Identify features and labels in a dataset for machine learning
Describe how training and validation datasets are used in machine learning
Describe capabilities of visual tools in Azure Machine Learning Studio
Automated machine learning
Azure Machine Learning designer
##) Describe features of computer vision workloads on Azure (15–20%)
Identify common types of computer vision solution
Identify features of image classification solutions
Identify features of object detection solutions
Identify features of optical character recognition solutions
Identify features of facial detection and facial analysis solutions
Identify Azure tools and services for computer vision tasks
Identify capabilities of the Computer Vision service
Identify capabilities of the Custom Vision service
Identify capabilities of the Face service
Identify capabilities of the Form Recognizer service
##) Describe features of Natural Language Processing (NLP) workloads on Azure (25–30%)
Identify features of common NLP Workload Scenarios
Identify features and uses for key phrase extraction
Identify features and uses for entity recognition
Identify features and uses for sentiment analysis
Identify features and uses for language modeling
Identify features and uses for speech recognition and synthesis
Identify features and uses for translation
Identify Azure tools and services for NLP workloads
Identify capabilities of the Language service
Identify capabilities of the Speech service
Identify capabilities of the Translator service
Identify considerations for conversational AI solutions on Azure
Identify features and uses for bots
Identify capabilities of Power Virtual Agents and the Azure Bot service
Overall, the Microsoft AI-900 Azure AI Fundamentals Certification Practice Exam is an essential resource for anyone seeking to obtain the Microsoft AI-900 Azure AI Fundamentals certification. It provides a comprehensive and rigorous assessment of the candidate's knowledge and skills in the field of AI, enabling them to demonstrate their expertise and enhance their career prospects in this rapidly growing field.
Welcome to the Premier Course in Generative AI! This exhaustive course is designed to help you master leading-edge tools like ChatGPT, Midjourney, BARD, GPT-4, DALLE-2, Stable Diffusion, and GEN-1. You'll gain proficiency in using these tools to generate text, image, audio, and video content effortlessly.
This course is structured to provide hands-on learning experiences, enabling you to gain a practical understanding of each technology discussed. You will acquire skills in prompt engineering techniques and learn how to optimize results in text-to-text and text-to-image generation. Additionally, this course allows you to harness AI tools such as ChatGPT, DALLE-2, Stable Diffusion, Whisper, Synthesia, MAKE-A-VIDEO, and IMAGEN to streamline your content creation process, maximizing efficiency.
Beyond the technical components of Generative AI, this premier course also enlightens you on the newest advancements and ideas in this domain. It covers topics like GANs, GAI, LMMs, Transformers, Stable Diffusion, and AI-driven content generation, offering a comprehensive understanding of the field and keeping you informed about the latest developments.
Whether you are a beginner or an experienced professional, this course caters to all, providing the insights and skills necessary for success in the field. It’s a gateway to revolutionizing your content creation approach. So, enroll now and become a connoisseur in Generative AI!
In essence, this premier course in Generative AI provides an all-encompassing and practical approach to learning the newest innovations in Generative AI. Focusing on pioneering technologies and methodologies, you'll be equipped to create content easily and stay ahead in your field. Don’t delay, enroll now and elevate your capabilities!
Course Content
In Section 1, delve into AI Text Generation. Start with a comprehensive "ChatGPT Walkthrough" covering GPT-3, 3.5, and GPT-4, with insights on project integration. Next, evaluate "GPT 3.5 vs. GPT 4" through an in-depth comparison highlighting accuracy, speed, and performance metrics. Additionally, explore "Bard vs. GPT-4," comparing Google Bard and GPT-4 in terms of capabilities, usability, and overall performance. Gain valuable insights into the world of text generation.
In Section 2, we explore AI Image Generation with a no-code approach. "Midjourney Mastery" offers a comprehensive guide for crafting visually striking AI art, no coding skills are needed. Dive deeper into creative control with advanced techniques like infinite zooming and prompt shortening. Elevate your AI-generated images effortlessly.
In Section 3, explore "AI Video Generation" starting with "Gen-1 Basics and Video-to-Video Generation," a foundational module on Gen-1 technology for video generation. Learn about the methods and algorithms behind it. Then, discover "Text to Video Generation Technique by Using Gen-2," where Gen-2 technology is leveraged to transform text data into lifelike videos.
In Section 4, get an "Introduction to AI Audio Generation," offering an overview of AI audio technologies. Dive into "Speech to Text: Whisper AI by Runway" for a practical guide on converting speech into text using Whisper AI by Runway.
Section 5 introduces the "Concept of Stable Diffusion." Begin by setting up "Stable Diffusion Locally into Your System" with detailed instructions. Then, familiarize yourself with the "Walkthrough of Stable Diffusion UI" to navigate the user interface effectively.
In Section 6, grasp the "Basics of Generative AI" with an in-depth exploration of its history and applications across various fields. Investigate the "Market Overview & Use Cases" to understand the current landscape and diverse applications of generative AI.
Section 7 delves into "The Future of Generative AI" by discussing the socio-economic impact of AI, particularly its effects on employment and future job opportunities.
Finally, in Section 8, go "Beyond the Course" with a relaxed session exploring some of the most interesting and fun AI tools available today.
Welcome to the Premier Course in Generative AI! This exhaustive course is designed to help you master leading-edge tools like ChatGPT, Midjourney, BARD, GPT-4, DALLE-2, Stable Diffusion, and GEN-1. You'll gain proficiency in using these tools to generate text, image, audio, and video content effortlessly.
This course is structured to provide hands-on learning experiences, enabling you to gain a practical understanding of each technology discussed. You will acquire skills in prompt engineering techniques and learn how to optimize results in text-to-text and text-to-image generation. Additionally, this course allows you to harness AI tools such as ChatGPT, DALLE-2, Stable Diffusion, Whisper, Synthesia, MAKE-A-VIDEO, and IMAGEN to streamline your content creation process, maximizing efficiency.
Beyond the technical components of Generative AI, this premier course also enlightens you on the newest advancements and ideas in this domain. It covers topics like GANs, GAI, LMMs, Transformers, Stable Diffusion, and AI-driven content generation, offering a comprehensive understanding of the field and keeping you informed about the latest developments.
Whether you are a beginner or an experienced professional, this course caters to all, providing the insights and skills necessary for success in the field. It’s a gateway to revolutionizing your content creation approach. So, enroll now and become a connoisseur in Generative AI!
In essence, this premier course in Generative AI provides an all-encompassing and practical approach to learning the newest innovations in Generative AI. Focusing on pioneering technologies and methodologies, you'll be equipped to create content easily and stay ahead in your field. Don’t delay, enroll now and elevate your capabilities!
Course Content
In Section 1, delve into AI Text Generation. Start with a comprehensive "ChatGPT Walkthrough" covering GPT-3, 3.5, and GPT-4, with insights on project integration. Next, evaluate "GPT 3.5 vs. GPT 4" through an in-depth comparison highlighting accuracy, speed, and performance metrics. Additionally, explore "Bard vs. GPT-4," comparing Google Bard and GPT-4 in terms of capabilities, usability, and overall performance. Gain valuable insights into the world of text generation.
In Section 2, we explore AI Image Generation with a no-code approach. "Midjourney Mastery" offers a comprehensive guide for crafting visually striking AI art, no coding skills are needed. Dive deeper into creative control with advanced techniques like infinite zooming and prompt shortening. Elevate your AI-generated images effortlessly.
In Section 3, explore "AI Video Generation" starting with "Gen-1 Basics and Video-to-Video Generation," a foundational module on Gen-1 technology for video generation. Learn about the methods and algorithms behind it. Then, discover "Text to Video Generation Technique by Using Gen-2," where Gen-2 technology is leveraged to transform text data into lifelike videos.
In Section 4, get an "Introduction to AI Audio Generation," offering an overview of AI audio technologies. Dive into "Speech to Text: Whisper AI by Runway" for a practical guide on converting speech into text using Whisper AI by Runway.
Section 5 introduces the "Concept of Stable Diffusion." Begin by setting up "Stable Diffusion Locally into Your System" with detailed instructions. Then, familiarize yourself with the "Walkthrough of Stable Diffusion UI" to navigate the user interface effectively.
In Section 6, grasp the "Basics of Generative AI" with an in-depth exploration of its history and applications across various fields. Investigate the "Market Overview & Use Cases" to understand the current landscape and diverse applications of generative AI.
Section 7 delves into "The Future of Generative AI" by discussing the socio-economic impact of AI, particularly its effects on employment and future job opportunities.
Finally, in Section 8, go "Beyond the Course" with a relaxed session exploring some of the most interesting and fun AI tools available today.
AI-102 Microsoft Azure AI Solution Certification Practice Exam is a comprehensive and reliable tool designed to help individuals prepare for the Microsoft Azure AI Solution Certification exam. This practice exam offers a range of benefits to users, including the opportunity to assess their knowledge and skills in the field of AI, gain confidence in their abilities, and identify areas for improvement.
With a focus on practical application and real-world scenarios, the AI-102 practice exam provides users with a realistic and challenging experience that closely mirrors the actual certification exam. This allows individuals to become familiar with the exam format, question types, and time constraints, enabling them to perform at their best on exam day.
In addition to its practical benefits, the AI-102 practice exam is also an excellent resource for individuals seeking to enhance their professional credentials and advance their careers in the field of AI. By earning the Microsoft Azure AI Solution Certification, individuals can demonstrate their expertise and proficiency in designing and implementing AI solutions using Microsoft Azure technologies, opening up new opportunities for career growth and advancement.
Microsoft Azure AI Solution Exam Summary:
Exam Name : Microsoft Azure AI Solution
Exam Code : AI-102
Exam Price : 165 (USD)
Number of Questions: Maximum of 40-60 questions,
Type of Questions: Multiple Choice Questions (single and multiple response), drag and drops and performance-based,
Length of Test: 130 Minutes. The exam is available in English and Japanese languages.
Passing Score: 700 / 1000
Languages : English at launch. Japanese
Schedule Exam : Pearson VUE
Microsoft AI-102 Exam Syllabus Topics:
Plan and manage an Azure AI solution (25–30%)
Select the appropriate Azure AI service
Select the appropriate service for a vision solution
Select the appropriate service for a language analysis solution
Select the appropriate service for a decision support solution
Select the appropriate service for a speech solution
Select the appropriate Applied AI services
Plan and configure security for Azure AI services
Manage account keys
Manage authentication for a resource
Secure services by using Azure Virtual Networks
Plan for a solution that meets Responsible AI principles
Create and manage an Azure AI service
Create an Azure AI resource
Configure diagnostic logging
Manage costs for Azure AI services
Monitor an Azure AI resource
Deploy Azure AI services
Determine a default endpoint for a service
Create a resource by using the Azure portal
Integrate Azure AI services into a continuous integration/continuous deployment (CI/CD) pipeline
Plan a container deployment
Implement prebuilt containers in a connected environment
Create solutions to detect anomalies and improve content
Create a solution that uses Anomaly Detector, part of Cognitive Services
Create a solution that uses Azure Content Moderator, part of Cognitive Services
Create a solution that uses Personalizer, part of Cognitive Services
Create a solution that uses Azure Metrics Advisor, part of Azure Applied AI Services
Create a solution that uses Azure Immersive Reader, part of Azure Applied AI Services
Implement image and video processing solutions (15–20%)
Analyze images
Select appropriate visual features to meet image processing requirements
Create an image processing request to include appropriate image analysis features
Interpret image processing responses
Extract text from images
Extract text from images or PDFs by using the Computer Vision service
Convert handwritten text by using the Computer Vision service
Extract information using prebuilt models in Azure Form Recognizer
Build and optimize a custom model for Azure Form Recognizer
Implement image classification and object detection by using the Custom Vision service, part of Azure Cognitive Services
Choose between image classification and object detection models
Specify model configuration options, including category, version, and compact
Label images
Train custom image models, including classifiers and detectors
Manage training iterations
Evaluate model metrics
Publish a trained iteration of a model
Export a model to run on a specific target
Implement a Custom Vision model as a Docker container
Interpret model responses
Process videos
Process a video by using Azure Video Indexer
Extract insights from a video or live stream by using Azure Video Indexer
Implement content moderation by using Azure Video Indexer
Integrate a custom language model into Azure Video Indexer
Implement natural language processing solutions (25–30%)
Analyze text
Retrieve and process key phrases
Retrieve and process entities
Retrieve and process sentiment
Detect the language used in text
Detect personally identifiable information (PII)
Process speech
Implement and customize text-to-speech
Implement and customize speech-to-text
Improve text-to-speech by using SSML and Custom Neural Voice
Improve speech-to-text by using phrase lists and Custom Speech
Implement intent recognition
Implement keyword recognition
Translate language
Translate text and documents by using the Translator service
Implement custom translation, including training, improving, and publishing a custom model
Translate speech-to-speech by using the Speech service
Translate speech-to-text by using the Speech service
Translate to multiple languages simultaneously
Build and manage a language understanding model
Create intents and add utterances
Create entities
Train evaluate, deploy, and test a language understanding model
Optimize a Language Understanding (LUIS) model
Integrate multiple language service models by using Orchestrator
Import and export language understanding models
Create a question answering solution
Create a question answering project
Add question-and-answer pairs manually
Import sources
Train and test a knowledge base
Publish a knowledge base
Create a multi-turn conversation
Add alternate phrasing
Add chit-chat to a knowledge base
Export a knowledge base
Create a multi-language question answering solution
Create a multi-domain question answering solution
Use metadata for question-and-answer pairs
Implement knowledge mining solutions (5–10%)
Implement a Cognitive Search solution
Provision a Cognitive Search resource
Create data sources
Define an index
Create and run an indexer
Query an index, including syntax, sorting, filtering, and wildcards
Manage knowledge store projections, including file, object, and table projections
Apply AI enrichment skills to an indexer pipeline
Attach a Cognitive Services account to a skillset
Select and include built-in skills for documents
Implement custom skills and include them in a skillset
Implement incremental enrichment
Implement conversational AI solutions (15–20%)
Design and implement conversation flow
Design conversational logic for a bot
Choose appropriate activity handlers, dialogs or topics, triggers, and state handling for a bot
Build a conversational bot
Create a bot from a template
Create a bot from scratch
Implement activity handlers, dialogs or topics, and triggers
Implement channel-specific logic
Implement Adaptive Cards
Implement multi-language support in a bot
Implement multi-step conversations
Manage state for a bot
Integrate Cognitive Services into a bot, including question answering, language understanding,
and Speech service
Test, publish, and maintain a conversational bot
Test a bot using the Bot Framework Emulator or the Power Virtual Agents web app
Test a bot in a channel-specific environment
Troubleshoot a conversational bot
Deploy bot logic
Overall, the AI-102 Microsoft Azure AI Solution Certification Practice Exam is an essential tool for anyone seeking to achieve certification in this rapidly growing field. With its comprehensive coverage, practical focus, and numerous benefits, this practice exam is an invaluable resource for individuals looking to take their AI skills and knowledge to the next level.
AI-102 Microsoft Azure AI Solution Certification Practice Exam is a comprehensive and reliable tool designed to help individuals prepare for the Microsoft Azure AI Solution Certification exam. This practice exam offers a range of benefits to users, including the opportunity to assess their knowledge and skills in the field of AI, gain confidence in their abilities, and identify areas for improvement.
With a focus on practical application and real-world scenarios, the AI-102 practice exam provides users with a realistic and challenging experience that closely mirrors the actual certification exam. This allows individuals to become familiar with the exam format, question types, and time constraints, enabling them to perform at their best on exam day.
In addition to its practical benefits, the AI-102 practice exam is also an excellent resource for individuals seeking to enhance their professional credentials and advance their careers in the field of AI. By earning the Microsoft Azure AI Solution Certification, individuals can demonstrate their expertise and proficiency in designing and implementing AI solutions using Microsoft Azure technologies, opening up new opportunities for career growth and advancement.
Microsoft Azure AI Solution Exam Summary:
Exam Name : Microsoft Azure AI Solution
Exam Code : AI-102
Exam Price : 165 (USD)
Number of Questions: Maximum of 40-60 questions,
Type of Questions: Multiple Choice Questions (single and multiple response), drag and drops and performance-based,
Length of Test: 130 Minutes. The exam is available in English and Japanese languages.
Passing Score: 700 / 1000
Languages : English at launch. Japanese
Schedule Exam : Pearson VUE
Microsoft AI-102 Exam Syllabus Topics:
Plan and manage an Azure AI solution (25–30%)
Select the appropriate Azure AI service
Select the appropriate service for a vision solution
Select the appropriate service for a language analysis solution
Select the appropriate service for a decision support solution
Select the appropriate service for a speech solution
Select the appropriate Applied AI services
Plan and configure security for Azure AI services
Manage account keys
Manage authentication for a resource
Secure services by using Azure Virtual Networks
Plan for a solution that meets Responsible AI principles
Create and manage an Azure AI service
Create an Azure AI resource
Configure diagnostic logging
Manage costs for Azure AI services
Monitor an Azure AI resource
Deploy Azure AI services
Determine a default endpoint for a service
Create a resource by using the Azure portal
Integrate Azure AI services into a continuous integration/continuous deployment (CI/CD) pipeline
Plan a container deployment
Implement prebuilt containers in a connected environment
Create solutions to detect anomalies and improve content
Create a solution that uses Anomaly Detector, part of Cognitive Services
Create a solution that uses Azure Content Moderator, part of Cognitive Services
Create a solution that uses Personalizer, part of Cognitive Services
Create a solution that uses Azure Metrics Advisor, part of Azure Applied AI Services
Create a solution that uses Azure Immersive Reader, part of Azure Applied AI Services
Implement image and video processing solutions (15–20%)
Analyze images
Select appropriate visual features to meet image processing requirements
Create an image processing request to include appropriate image analysis features
Interpret image processing responses
Extract text from images
Extract text from images or PDFs by using the Computer Vision service
Convert handwritten text by using the Computer Vision service
Extract information using prebuilt models in Azure Form Recognizer
Build and optimize a custom model for Azure Form Recognizer
Implement image classification and object detection by using the Custom Vision service, part of Azure Cognitive Services
Choose between image classification and object detection models
Specify model configuration options, including category, version, and compact
Label images
Train custom image models, including classifiers and detectors
Manage training iterations
Evaluate model metrics
Publish a trained iteration of a model
Export a model to run on a specific target
Implement a Custom Vision model as a Docker container
Interpret model responses
Process videos
Process a video by using Azure Video Indexer
Extract insights from a video or live stream by using Azure Video Indexer
Implement content moderation by using Azure Video Indexer
Integrate a custom language model into Azure Video Indexer
Implement natural language processing solutions (25–30%)
Analyze text
Retrieve and process key phrases
Retrieve and process entities
Retrieve and process sentiment
Detect the language used in text
Detect personally identifiable information (PII)
Process speech
Implement and customize text-to-speech
Implement and customize speech-to-text
Improve text-to-speech by using SSML and Custom Neural Voice
Improve speech-to-text by using phrase lists and Custom Speech
Implement intent recognition
Implement keyword recognition
Translate language
Translate text and documents by using the Translator service
Implement custom translation, including training, improving, and publishing a custom model
Translate speech-to-speech by using the Speech service
Translate speech-to-text by using the Speech service
Translate to multiple languages simultaneously
Build and manage a language understanding model
Create intents and add utterances
Create entities
Train evaluate, deploy, and test a language understanding model
Optimize a Language Understanding (LUIS) model
Integrate multiple language service models by using Orchestrator
Import and export language understanding models
Create a question answering solution
Create a question answering project
Add question-and-answer pairs manually
Import sources
Train and test a knowledge base
Publish a knowledge base
Create a multi-turn conversation
Add alternate phrasing
Add chit-chat to a knowledge base
Export a knowledge base
Create a multi-language question answering solution
Create a multi-domain question answering solution
Use metadata for question-and-answer pairs
Implement knowledge mining solutions (5–10%)
Implement a Cognitive Search solution
Provision a Cognitive Search resource
Create data sources
Define an index
Create and run an indexer
Query an index, including syntax, sorting, filtering, and wildcards
Manage knowledge store projections, including file, object, and table projections
Apply AI enrichment skills to an indexer pipeline
Attach a Cognitive Services account to a skillset
Select and include built-in skills for documents
Implement custom skills and include them in a skillset
Implement incremental enrichment
Implement conversational AI solutions (15–20%)
Design and implement conversation flow
Design conversational logic for a bot
Choose appropriate activity handlers, dialogs or topics, triggers, and state handling for a bot
Build a conversational bot
Create a bot from a template
Create a bot from scratch
Implement activity handlers, dialogs or topics, and triggers
Implement channel-specific logic
Implement Adaptive Cards
Implement multi-language support in a bot
Implement multi-step conversations
Manage state for a bot
Integrate Cognitive Services into a bot, including question answering, language understanding,
and Speech service
Test, publish, and maintain a conversational bot
Test a bot using the Bot Framework Emulator or the Power Virtual Agents web app
Test a bot in a channel-specific environment
Troubleshoot a conversational bot
Deploy bot logic
Overall, the AI-102 Microsoft Azure AI Solution Certification Practice Exam is an essential tool for anyone seeking to achieve certification in this rapidly growing field. With its comprehensive coverage, practical focus, and numerous benefits, this practice exam is an invaluable resource for individuals looking to take their AI skills and knowledge to the next level.
Last Update: Oct 2023
Hi talent!
Welcome to this CISM - ISACA, Trends Focused, Practice Test course ! This course is prepared for the best of your value and the best of your interest!
This practice test covers will a large number of CISM - ISACA, Mock Exam Questions that simulate the real-live-exam for you to learn the topics in-depth. The practice tests are crafted from topics across the critical domains for the CISM - ISACA certificate. You will not only go through a journey to acquire knowledge through practicing with the the Trends Focused questions for the CISM - ISACA exam, you will learn all the exam skills by experiencing all different MC question formats I have especially crafted for you.
**The questions included in this course have been thoroughly analyzed with the latest trends in the CISM - ISACA exam**
Major Domains
Domain 1. Information Security Governance
Domain 2. Information Security Risk Management
Domain 3. Information Security Program
Domain 4. Incident Management
Major Domains | Weightings (Percentage)
Domain 1 – Information Security Governance (17%)
Domain 2 – Information Security Risk Management (20%)
Domain 3 – Information Security Program (33%)
Domain 4 – Incident Management (30%)
Total | 100%
**This practice test has been made with reference to the official guidelines and the exam weight in each domain**
What is the CISM difference?
Data breaches, ransomware attacks and other constantly evolving security threats are top-of-mind for today’s IT professionals. With a Certified Information Security Manager (CISM ) certification, you’ll learn how to assess risks, implement effective governance and proactively respond to incidents.
Beside doing the practice test, I would suggest you to do as much simulation test / question as you could to get your self well prepared for the exam. More practice test will be released soon. Stay tuned and Good Luck.
CISM Examination Information
4 hours (240 minutes), 150 multiple choice questions
Are you Ready to get CISM ?
One more thing, Walter's career tips:
If you are pursuing your career paths in External / Internal Auditor, Tech. Risk, Cybersecurity, you should consider taking following Certifications to equip yourself and demonstrate your competency to your employers.
ISACA | ISC2 | CSA | IAPP | IIA | ACAMS |
CISA | CISSP | CCSK | CIPT | CIA | CAMS |
CISM | CCSP | | CIPP |
CRISC | SSCP | | CIPM |
CGEIT | CGRC | | CDPO |
CDPSE | CSSLP |
CCAK | CISSP-ISSAP |
COBIT | CISSP-ISSMP |
| CISSP-ISSEP |
Last Update: Oct 2023
Hi talent!
Welcome to this CISM - ISACA, Trends Focused, Practice Test course ! This course is prepared for the best of your value and the best of your interest!
This practice test covers will a large number of CISM - ISACA, Mock Exam Questions that simulate the real-live-exam for you to learn the topics in-depth. The practice tests are crafted from topics across the critical domains for the CISM - ISACA certificate. You will not only go through a journey to acquire knowledge through practicing with the the Trends Focused questions for the CISM - ISACA exam, you will learn all the exam skills by experiencing all different MC question formats I have especially crafted for you.
**The questions included in this course have been thoroughly analyzed with the latest trends in the CISM - ISACA exam**
Major Domains
Domain 1. Information Security Governance
Domain 2. Information Security Risk Management
Domain 3. Information Security Program
Domain 4. Incident Management
Major Domains | Weightings (Percentage)
Domain 1 – Information Security Governance (17%)
Domain 2 – Information Security Risk Management (20%)
Domain 3 – Information Security Program (33%)
Domain 4 – Incident Management (30%)
Total | 100%
**This practice test has been made with reference to the official guidelines and the exam weight in each domain**
What is the CISM difference?
Data breaches, ransomware attacks and other constantly evolving security threats are top-of-mind for today’s IT professionals. With a Certified Information Security Manager (CISM ) certification, you’ll learn how to assess risks, implement effective governance and proactively respond to incidents.
Beside doing the practice test, I would suggest you to do as much simulation test / question as you could to get your self well prepared for the exam. More practice test will be released soon. Stay tuned and Good Luck.
CISM Examination Information
4 hours (240 minutes), 150 multiple choice questions
Are you Ready to get CISM ?
One more thing, Walter's career tips:
If you are pursuing your career paths in External / Internal Auditor, Tech. Risk, Cybersecurity, you should consider taking following Certifications to equip yourself and demonstrate your competency to your employers.
ISACA | ISC2 | CSA | IAPP | IIA | ACAMS |
CISA | CISSP | CCSK | CIPT | CIA | CAMS |
CISM | CCSP | | CIPP |
CRISC | SSCP | | CIPM |
CGEIT | CGRC | | CDPO |
CDPSE | CSSLP |
CCAK | CISSP-ISSAP |
COBIT | CISSP-ISSMP |
| CISSP-ISSEP |