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AI-102: Develop AI solutions in Azure
Minimum cohort size: 10 learners
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Course
AI-102: Develop AI solutions in Azure
This course is designed to teach software developers how to create AI solutions that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework to build computer vision, language analysis, knowledge mining, intelligent search and conversational AI solutions on Azure.
Benefit from instructor-led preparation for the AI-102 certification exam with tips, tricks, guidance, and mentored support.
Online Live Classes
Intermediate Level
Mentor Support
This course will prepare you for the AI-102 Microsoft Azure AI Engineer certification exam. Entry for the exam is not included, however you will gain the skills and knowledge you need to pass successfully.
This course is a culmination of the Azure AI Engineer Associate program. You will learn to plan and manage an Azure Cognitive Services solution. Plus you will implement Computer Vision solutions, natural language processing solutions, knowledge mining solutions, and conversational AI solutions.
Overall, this course will prepare you for taking the AI-102 Designing and Implementing a Microsoft Azure AI Solution certification exam. Entry for the exam is not included. In addition, you will get a more detailed overview of the Microsoft certification process. Plus, you will get tips and tricks, testing strategies, useful resources, and information on how to sign up for the AI-102 proctored exam.
This course comprises 37 purposely designed modules that take you on a carefully defined learning journey.
It is an instructor-led course which runs to a fixed schedule, with set start and finish dates. It is driven forward by your instructor and features live sessions that are aired at a set time. You will, however, have time to complete certain activities at your own pace outside of the live sessions.
The materials for each module are accessible from the start of the course and will remain available for the duration of your enrollment. Methods of learning and assessment will include reading material, hands-on labs, and online exams questions.
As part of our mentoring service you will have access to valuable guidance and support throughout the course. We provide a dedicated discussion space where you can ask questions, chat with your peers, and resolve issues.
Once you have successfully completed the course, you will earn your Certificate of Completion.
You will be able to:
- Plan and manage an Azure AI solution
- Implement content moderation solutions
- Implement computer vision solutions
- Implement natural language processing solutions
- Implement knowledge mining and document intelligence solutions
- Implement generative AI solutions
- IT professionals seeking to build on their expertise in designing and implementing AI solutions running on Microsoft Azure.
- Individuals looking to prepare for Microsoft AI-102 certification exam.
- Knowledge of Microsoft Azure and ability to navigate the Azure portal
- Knowledge of either C# or Python
- Familiarity with JSON and REST programming semantics
This course will help you to prepare for the AI-102: Designing and Implementing a Microsoft Azure AI Solution exam.
It is ideal for learners who are just beginning to build, manage, and deploy AI solutions.
- You will become familiar with the responsibilities for this role, which include the stages from requirements definition and design to development, deployment, maintenance, performance tuning, and monitoring.
- You will build your knowledge of core Azure services, Azure workloads and mostly AI technologies.
- You will gain experience using PowerShell, Azure CLI, Azure portal, Azure Cognitive Services, speech-enabled applications and face recognition system
When you take this course, you will also get information and guidance on the Microsoft certification process, knowledge checks and practice questions, and useful tips on how to pass the exam. This certification then lays the foundation for the following certifications: Microsoft Certified Azure Solutions Architect Expert, Microsoft Certified Azure DevOps Engineer Expert, Microsoft Certified Azure Security Engineer Associate and Microsoft AI Engineer Associate.
Course Outline
Introduction
Grading Scheme
Pre-Requisite
Exam and Certification Details
About this module
What is AI?
Azure AI services
Azure AI Foundry
Developer tools and SDKs
Responsible AI
Knowledge Check
About this module
Explore the model catalog
Deploy a model to an endpoint
Optimize model performance
Knowledge Check
About this module
What is the Azure AI Foundry SDK?
Work with project connections
Create a chat client
Knowledge Check
About this module
Understand the development lifecycle of a large language model (LLM) app
Understand core components and explore flow types
Explore connections and runtimes
Explore variants and monitoring options
Knowledge Check
About this module
Understand how to ground your language model
Make your data searchable
Create a RAG-based client application
Implement RAG in a prompt flow
Knowledge Check
About this module
Understand when to fine-tune a language model
Prepare your data to fine-tune a chat completion model
Explore fine-tuning language models in Azure AI Foundry portal
Knowledge Check
About this module
Plan a responsible generative AI solution
Map potential harms
Measure potential harms
Mitigate potential harms
Manage a responsible generative AI solution
Knowledge Check
About this module
Assess the model performance
Manually evaluate the performance of a model
Automated evaluations
Knowledge Check
About this module
What are AI agents?
Options for agent development
Azure AI Foundry Agent Service
Knowledge Check
About this module
What is an AI agent
How to use Azure AI Foundry Agent Service
Develop agents with the Azure AI Foundry Agent Service
Knowledge Check
About this module
Why use custom tools
Options for implementing custom tools
How to integrate custom tools
Knowledge Check
About this module
Understand connected agents
Design a multi-agent solution with connected agents
Knowledge Check
About this module
Understand MCP tool discovery
Integrate agent tools using an MCP server and client
Use Azure AI agents with MCP servers
Knowledge Check
About this module
Understand Semantic Kernel AI agents
Create an Azure AI agent with Semantic Kernel
Add plugins to Azure AI agent
Knowledge Check
About this module
Understand the Semantic Kernel Agent Framework
Create an agent group chat
Design an agent selection strategy
Define a chat termination strategy
Knowledge Check
About this module
Provision an Azure AI Language resource
Detect language
Extract key phrases
Analyze sentiment
Extract entities
Extract linked entities
Knowledge Check
About this module
Understand question answering
Compare question answering to Azure AI Language understanding
Create a knowledge base
Implement multi-turn conversation
Test and publish a knowledge base
Use a knowledge base
Improve question answering performance
Knowledge Check
About this module
Understand prebuilt capabilities of the Azure AI Language service
Understand resources for building a conversational language understanding model
Define intents, utterances, and entities
Use patterns to differentiate similar utterances
Use pre-built entity components
Train, test, publish, and review a conversational language understanding model
Knowledge Check
About this module
Understand types of classification projects
Understand how to build text classification projects
Knowledge Check
About this module
Understand custom named entity recognition
Label your data
Train and evaluate your model
Knowledge Check
About this module
Provision an Azure AI Translator resource
Understand language detection, translation, and transliteration
Specify translation options
Define custom translations
Knowledge Check
About this module
Provision an Azure resource for speech
Use the Azure AI Speech to text API
Use the text to speech API
Configure audio format and voices
Use Speech Synthesis Markup Language
Knowledge Check
About this module
Provision an Azure resource for speech translation
Translate speech to text
Synthesize translations
Knowledge Check
About this module
Deploy a multimodal model
Develop an audio-based chat app
Knowledge Check
About this module
Provision an Azure AI Vision resource
Analyze an image
Knowledge Check
About this module
Explore Azure AI Vision options for reading text
Read text with Azure AI Vision Image Analysis
Knowledge Check
About this module
Plan a face detection, analysis, or recognition solution
Detect and analyze faces
Verify and identify faces
Responsible AI considerations for face-based solutions
Knowledge Check
About this module
Azure AI Custom Vision
Train an image classification model
Create an image classification client application
Knowledge Check
About this module
Use Azure AI Custom Vision for object detection
Train an object detector
Develop an object detection client application
Knowledge Check
About this module
Understand Azure Video Indexer capabilities
Extract custom insights
Use Video Analyzer widgets and APIs
Knowledge Check
About this module
Deploy a multimodal model
Develop a vision-based chat app
Knowledge Check
About this module
What are image-generation models?
Explore image-generation models in Azure AI Foundry portal
Create a client application that uses an image generation model
Knowledge Check
About this module
What is Azure AI Content Understanding?
Create a Content Understanding analyzer
Use the Content Understanding REST API
Knowledge Check
About this module
Prepare to use the AI Content Understanding REST API
Create a Content Understanding analyzer
Analyze content
Knowledge Check
About this module
Understand prebuilt models
Use the General Document, Read, and Layout models
Use financial, ID, and tax models
Knowledge Check
About this module
What is Azure Document Intelligence?
Get started with Azure Document Intelligence
Train custom models
Use Azure Document Intelligence models
Use the Azure Document Intelligence Studio
Knowledge Check
About this module
What is Azure AI Search?
Extract data with an indexer
Enrich extracted data with AI skills
Search an index
Persist extracted information in a knowledge store
Knowledge Check
Instructions
Choose and deploy a language model
Create a generative AI chat app
Create a generative AI app that uses your own data
Apply content filters to prevent the output of harmful content
Evaluate generative AI model performance
Explore AI Agent development
Develop an AI agent
Use a custom function in an AI agent
Develop an Azure AI agent with the Semantic Kernel SDK
Develop a multi-agent solution
Analyze text
Create a question answering solution
Custom text classification
Recognize and synthesize speech
Develop an audio-enabled chat app
Analyze images
Read text in images
Detect and analyze faces
Classify images
Develop a vision-enabled chat app
Generate images with AI
Extract information from multimodal content
Develop a Content Understanding client application
Analyze forms with prebuilt Azure AI Document Intelligence models Analyze forms with custom Azure AI Document Intelligence models
Analyze forms with custom Azure AI Document Intelligence models
Create a knowledge mining solution
Practice Set 1
Practice Set 2
AI-102 Project
Download your certificate
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FAQs
Learners must be fluent in C#, Python, or JavaScript. You should be able to use REST-based APIs and SDKs to build computer vision, natural language processing, knowledge mining, and conversational AI solutions on Azure.
You should be conversant with the Azure AI portfolio components and the data storage options accessible and must be aware of and capable of employing ethical AI principles.
Learners can become certified in AI-102: Designing and Implementing a Microsoft Azure AI Solution by following these steps:
Step 1: Complete recommended training for AI-102 with a Microsoft authorized training partner. SKillUp Online is a Microsoft authorized training partner.
Step 2: After completing the training, visit Microsoft's official website. Register for the Microsoft exam, and schedule it with Pearson VUE.
Step 3: Take the exam, pass it, and get certified!
You can enroll onto training with us; we are a Microsoft authorized training partner. During the course, you will build up detailed knowledge of all the topics as per the Microsoft Official Curriculum (MOC) through training from certified trainers. You will also get practical experience through Microsoft official hands-on labs. Plus, we will provide practice exams to enable you to check on your certification preparation, and you will complete a capstone project.
AI-102: Designing and Implementing a Microsoft Azure AI Solution is a certification exam offered by Microsoft/Pearson VUE. To pass, a score of 700 is required. You'll know if you passed or failed the exam within a few minutes after finishing it. You will also receive a printed report with your exam score and feedback on your performance in the skill areas assessed. This report will give you a number score for overall exam performance as well as a bar chart displaying performance on each skill area assessed and instructions on how to interpret your results and next steps.
PLEASE NOTE: Exam entry is not included with this course. However, your instructor will take your through what will happen during the Microsoft certification process. And they will also give you help and guidance on how to enter and pass the exam.
Type of certificate
Certificate of completion
About this course
37 Modules
14 Skills
Includes
Discussion space
26 Labs
37 Knowledge checks
02 Practice exam
01 Project
Create
Azure AI Services
Question Answering Solution
Language understanding model
Custom Skill for Azure AI Search
Exercises to explore
Azure AI Vision
Read Text in Images
Analyze Text
Recognize and synthesize speech
Integrate Azure OpenAI into your app
Azure OpenAI
Extract Data from Forms
You’ll learn with these experts
Microsoft
This course is led by experienced Microsoft Certified Trainers (MCTs).
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