The Exam AI-102 is part of the Microsoft Certified: Azure AI Solution Associate certification. This exam measures the candidate’s ability to design and implement AI solutions that use Microsoft Azure services. It covers a range of topics including natural language processing, computer vision, and conversational AI, as well as the ability to use Azure AI services like Cognitive Services, Azure Bot Service, and Azure Machine Learning. The exam is intended for professionals who have intermediate-level knowledge of programming and Azure services, and who want to demonstrate their ability to design and implement AI solutions on Azure.
Earning the Microsoft Certified: Azure AI Solution Associate certification demonstrates your expertise in designing and implementing AI solutions using Microsoft Azure services. This certification can help you stand out in a competitive job market and increase your earning potential. It also shows that you are committed to continuing your education and staying up-to-date on the latest AI technologies.
However, this blog will provide an overview of the AI-102 exam and the benefits of earning the Microsoft Certified: Azure AI Solution Associate certification. It will offer exam preparation tips, including how to develop a study plan, utilize Microsoft learning resources, and gain practical experience. Additionally, it will offer strategies for success on exam day, such as managing your time effectively, understanding the questions, and utilizing exam features. Finally, it will conclude with a recap of the exam and certification benefits, as well as additional resources for exam preparation.
Exam AI-102 Exam Glossary
Here are some key terms and concepts that you may encounter in the Microsoft Azure AI Solution Exam AI-102:
- Artificial Intelligence (AI): The simulation of human intelligence processes by computer systems, such as learning, reasoning, and self-correction.
- Machine Learning (ML): The ability of a computer system to learn from data and improve its performance over time without being explicitly programmed.
- Deep Learning: A subset of machine learning that uses deep neural networks to model complex patterns in data.
- Neural Network: A type of machine learning model that is inspired by the structure and function of the human brain.
- Data Science: An interdisciplinary field that involves the use of statistical and computational methods to extract insights from data.
- Natural Language Processing (NLP): A branch of AI that focuses on the interaction between computers and human language.
- Computer Vision: A field of AI that focuses on enabling computers to interpret and understand visual information from the world around them.
- Cognitive Services: A set of pre-built AI services provided by Microsoft Azure, including speech recognition, language understanding, and image recognition.
- Azure Machine Learning: A cloud-based service provided by Microsoft Azure for building, training, and deploying machine learning models.
- Learn Azure Cognitive Search: A cloud-based search service provided by Microsoft Azure that uses AI to enable intelligent search experiences.
- Azure Databricks: A cloud-based big data and machine learning platform provided by Microsoft Azure that integrates with other Azure services.
- Learn Azure Stream Analytics: A cloud-based service provided by Microsoft Azure for processing and analyzing real-time streaming data.
- Azure Synapse Analytics: A cloud-based service provided by Microsoft Azure that integrates big data and data warehousing capabilities.
- Azure Data Factory: A cloud-based service provided by Microsoft Azure for orchestrating data movement and transformation workflows.
Microsoft Azure AI Solution Exam AI-102 Study Guide
Here are some official resources for preparing for the Microsoft Azure AI Solution exam:
- Exam page: The official Microsoft page for the Azure AI Solution exam provides an overview of the exam, including its format, objectives, and skills measured. You can access it here: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-100
- Study materials: Microsoft provides a range of study materials to help you prepare for the exam, including online courses, practice exams, and learning paths. You can access them here: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-100
- Microsoft Learn: Microsoft Learn is an online learning platform that offers free, interactive courses on a range of topics, including Azure AI. You can access the Azure AI courses here: https://docs.microsoft.com/en-us/learn/browse/?products=azure-ai&roles=data-scientist&levels=beginner
- Azure AI documentation: Microsoft also provides detailed documentation on Azure AI, which can be helpful in preparing for the exam. You can access it here: https://docs.microsoft.com/en-us/azure/ai/
- Microsoft Azure AI community: Joining the Azure AI community is a great way to connect with other professionals, share knowledge, and get support. You can join the community here: https://techcommunity.microsoft.com/t5/azure-ai/bd-p/AzureAI
- Exam practice test: Microsoft also provides an official practice test that can help you prepare for the exam. You can access it here: https://www.microsoft.com/en-us/learning/exam-AI-100.aspx#practice-tab
Microsoft Azure AI Solution Exam AI-102 Tips and Tricks
Here are some tips and tricks for the Microsoft Azure AI Solution Exam AI-102:
- Understand the exam objectives: The first step in preparing for any exam is to understand the exam objectives. Review the skills measured section on the exam page and ensure that you are familiar with all the topics.
- Familiarize yourself with Azure AI services: The exam covers various Azure AI services, including Azure Cognitive Services, Azure Bot Service, and Azure Machine Learning. Familiarize yourself with these services and understand their capabilities.
- Practice with real-world scenarios: The exam will test your ability to apply your knowledge to real-world scenarios. So, practice with hands-on experience and work on projects to gain practical experience.
- Learn how to integrate Azure AI services: The exam will also test your ability to integrate Azure AI services with other Azure services, such as Azure Functions, Azure Logic Apps, and Azure App Service. So, learn how to integrate Azure AI services with other Azure services.
- Study Azure AI best practices: Learn about best practices for designing, deploying, and monitoring Azure AI solutions. Familiarize yourself with the best practices related to data preparation, model training, and deployment.
- Use Microsoft official resources: Microsoft provides a range of study materials, practice exams, and learning paths to help you prepare for the exam. Utilize these resources to gain a deeper understanding of the topics covered on the exam.
- Manage your time during the exam: The exam is timed, so make sure you manage your time effectively. Don’t spend too much time on a single question and move on if you get stuck.
- Read the questions carefully: Make sure to read the questions carefully and understand what is being asked before answering. Don’t rush through the questions, take your time to understand them.
Exam AI-102: Course Outline
In order to pass the exam, one should understand the course domains. Each region in this course outline comes with several subtopics, which makes it all the more significant. Devote sufficient time to each and every domain and have complete clarity about the exam concepts.
1. Plan and Manage an Azure AI Solution (15-20%)
Select the appropriate Azure AI service
- select the appropriate service for a computer vision solution
- Select the appropriate service for a natural language processing solution
- select the appropriate Service for a decision support solution (Microsoft Documentation: Choose an Azure compute service)
- select the appropriate service for a speech solution (Microsoft Documentation: What is the Speech service?)
- Select the appropriate service for a generative AI solution
- Select the appropriate service for a document intelligence solution
- Select the appropriate service for a knowledge mining solution
Plan, create and deploy an Azure AI service
- Plan for a solution that meets Responsible AI principles
- Create an Azure AI resource
- Determine a default endpoint for a service
- Integrate Azure AI services into a continuous integration and continuous delivery (CI/CD) pipeline
- Plan and implement a container deployment
Manage, monitor and secure an Azure AI service
- Configure diagnostic logging
- Monitor an Azure AI resource
- Manage costs for Azure AI services
- Manage account keys
- Protect account keys by using Azure Key Vault
- Manage authentication for an Azure AI Service resource
- Manage private communications
2. Implement decision support solutions (10–15%)
Create decision support solutions for data monitoring and anomaly detection
- Implement a univariate anomaly detection solution with Azure AI Anomaly Detector
- Implement a multivariate anomaly detection solution Azure AI Anomaly Detector
- Implement a data monitoring solution with Azure AI Metrics Advisor
Create decision support solutions for content delivery
- Implement a text moderation solution with Azure AI Content Safety
- Implement an image moderation solution with Azure AI Content Safety
- Implement a content personalization solution with Azure AI Personalizer
3. Implement computer vision solutions (15–20%)
Analyze images
- Select visual features to meet image processing requirements
- Detect objects in images and generate image tags
- Include image analysis features in an image processing request
- Interpret image processing responses
- Extract text from images using Azure AI Vision
- Convert handwritten text using Azure AI Vision
Implement custom computer vision models by using Azure AI Vision
- Choose between image classification and object detection models
- Label images
- Train a custom image model, including image classification and object detection
- Evaluate custom vision model metrics
- Publish a custom vision model
- Consume a custom vision model
Analyze videos
- Use Azure AI Video Indexer to extract insights from a video or live stream
- Use Azure AI Vision Spatial Analysis to detect presence and movement of people in video
4. Implement Natural Language Processing Solutions (30-35%)
Analyze text by using Azure AI Language
- Extract key phrases
- Extract entities
- Determine sentiment of text
- detect the language used in the text (Microsoft Documentation: Detect language with Text Analytics)
- Detect personally identifiable information (PII) in text
Process speech by using Azure AI Speech
- implement text-to-speech (Microsoft Documentation: text-to-speech, Custom Voice)
- implement speech-to-text (Microsoft Documentation: speech-to-text)
- Improve text-to-speech by using Speech Synthesis Markup Language (SSML)
- improve Custom Speech solutions
- Implement intent recognition (Microsoft Documentation: Recognize intents with the Speech service and LUIS)
- Implement keyword recognition
Translate language
- translate text and documents by using the Azure AI Translator service (Microsoft Documentation: Create a translation app with WPF)
- Implement custom translation, including training, improving, and publishing a custom model
- translating speech-to-speech by using the Azure AI Speech service (Microsoft Documentation: speech translation)
- translate speech-to-text by using the Azure AI Speech service (Microsoft Documentation: speech-to-text)
- Translate to multiple languages simultaneously
Implement and manage a language understanding model by using Azure AI Language
- create intents and add utterances (Microsoft Documentation: Intents)
- Create entities
- Train evaluate, deploy, and test a language understanding model (Microsoft Documentation: deploy a model, Train your conversational language understanding model)
- Optimize a Language Understanding model (Microsoft Documentation: What is Language Understanding (LUIS)?)
- Consume a language model from a client application
- Backup and recover language understanding models
Create a question answering solution by using Azure AI Language
- Create a question answering project (Microsoft Documentation: Create, test, and deploy a custom question answering project)
- Add question-and-answer pairs manually
- Import sources
- train and test a knowledge base (Microsoft Documentation: Test your knowledge base in QnA Maker, Create, train, and publish your QnA Maker knowledge base)
- publish a knowledge base (Microsoft Documentation: Publish the knowledge base)
- create a multi-turn conversation (Microsoft Documentation: create multiple turns of a conversation)
- add alternate phrasing (Microsoft Documentation: Add additional alternatively-phrased questions, Add alternate questions)
- add chit-chat to a knowledge base (Microsoft Documentation: Add Chit-chat to a knowledge base)
- export a knowledge base (Microsoft Documentation: Migrate a knowledge base using export-import)
- Create a multi-language question answering solution
5. Implement knowledge mining and document intelligence solutions (10–15%)
Implement a Azure Cognitive Search Solution
- Provision a Cognitive Search resource
- create data sources (Microsoft Documentation: Create Data Source)
- Create an index (Microsoft Documentation: Creating search indexes in Azure Cognitive Search)
- Define a skillset
- Implement custom skills and include them in a skillset
- create and run an indexer (Microsoft Documentation: Creating indexers in Azure Cognitive Search)
- Query an index, including syntax, sorting, filtering, and wildcards (Microsoft Documentation: Simple query syntax in Azure Cognitive Search, Lucene query syntax in Azure Cognitive Search, Querying in Azure Cognitive Search)
- Manage knowledge store projections, including file, object, and table projections
Implement an Azure AI Document Intelligence solution
- Provision a Document Intelligence resource
- Use prebuilt models to extract data from documents
- Implement a custom document intelligence model
- Train, test, and publish a custom document intelligence model
- Create a composed document intelligence model
- Implement a document intelligence model as a custom Azure Cognitive Search skill
6. Implement generative AI solutions (10–15%)
Use Azure OpenAI Service to generate content
- Provision an Azure OpenAI Service resource
- Select and deploy an Azure OpenAI model
- Submit prompts to generate natural language
- Submit prompts to generate code
- Use the DALL-E model to generate images
- Use Azure OpenAI APIs to submit prompts and receive responses
Optimize generative AI
- Configure parameters to control generative behavior
- Apply prompt engineering techniques to improve responses
- Use your own data with an Azure OpenAI model
- Fine-tune an Azure OpenAI model
Preparatory Resources: Exam AI-102
It is time to acknowledge some learning resources for becoming the Microsoft Certified: Azure AI Engineer Associate. Let us begin:
Develop a study plan
Create a study plan that covers all the topics and skills measured in the exam. Divide your study plan into manageable sections and set realistic goals for each section.
Gain practical experience
Experience working with Azure services and AI technologies can be invaluable when preparing for the exam. Try to gain practical experience by working on real-world projects or experimenting with Azure services and tools.
Microsoft Learning Platform
Microsoft gives AI-102 learning paths, the candidate should visit the official website of Microsoft. The candidate can find every possible information on the official site. The candidate will find many Microsoft Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution learning paths and documentation for this. Finding relatable content on the Microsoft website is quite an easy task. Also, you can find the study guide for Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution on the official website of Microsoft.
Refer to the following mentioned learning paths-
Provision and manage Azure Cognitive Services
Process and translate the text with Azure Cognitive Services
Process and Translate Speech with Azure Cognitive Speech Services
Create a Language Understanding solution
Microsoft Documentation
Microsoft Documentations are an important learning resource while preparing for Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution. The candidate will find documentation on every topic relating to the particular exam. This step is very valuable in preparing for becoming a Microsoft Identity and Access Administrator.
- Publish the current iteration
- Upload and index your videos
- Live stream analysis with Video Indexer
- How to use Named Entity Recognition in Text Analytics
- Create a translation app with WPF
- Deploy an app in the LUIS portal
Refer to the upper mentioned course outline for all Microsoft Documentations!
Instructor-Led Training
Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution training program that Microsoft provides itself is available on their website. The instructor-led training is an essential resource in order to prepare for an exam like AI-102. The candidate can find the instructor-led training on the page of the particular exam on the Microsoft website. There are various Microsoft AI-102 training courses available prior to one exam. The following is the training program offered by Microsoft.
Testprep Online Tutorial
We at Testperptraining offer an online tutorial for every exam and certification. These online tutorials will help you to learn and understand all the information regarding the exam. This will be a very beneficial step. CLICK HERE for Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution Online Tutorial.
Join a Study Group
For becoming the Microsoft Certified: Azure AI Engineer Associate, the candidate needs to get and share knowledge. So, we are suggesting you join some studies where you can discuss the concepts with the people who have the same goal. This will lead the candidate throughout their preparation.
Evaluate yourself with Practice Test
The most important step is to try your hands on the practice test. The Microsoft AI-102 Practice tests are the one which ensures the candidate about their preparation. There are many practice tests available on the internet nowadays, the candidate can choose whichever they want. The practice test is very beneficial in preparing the Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution. So, Start Preparing Now!
Final Tips For The Exam
Final tips for exam success
Here are some final tips to help you succeed on the AI-102 exam:
- Manage your time effectively: Time management is crucial when taking any certification exam. Use your time wisely, read the questions carefully, and don’t spend too much time on any one question.
- Read and understand the questions: Take the time to read and understand each question before answering it. Look for keywords and phrases that can help you identify the correct answer.
- Utilize exam features: The exam may have features like marking questions for review or highlighting important information. Use these features to your advantage to ensure you answer every question to the best of your ability.
- Stay calm and focused: Don’t panic if you encounter difficult questions or struggle with a particular section of the exam. Take deep breaths, stay calm, and remain focused on the task at hand.
