Microsoft Certified Azure AI Engineer Associate: AI 102
Design and Implement a Microsoft Azure AI Solution
- Microsoft Certified: Azure AI Engineer Associate - AI 102 aligned training
- Get access to practice tests to ace the AI-102 exam
- Build AI Apps with Azure Services like Azure AI Search and Azure OpenAI
- Gain expertise in core AI areas like computer vision, NLP, and speech services
- Explore Microsoft Azure for building and deploying intelligent applications
Start Date
23rd June 2025
Course Duration
360 Hrs
Course Overview
The Azure AI certification course prepares you for Microsoft’s Azure AI Engineer Associate exam AI-102. It covers Azure services like language, speech and translation, OpenAI, prompt engineering, responsible generative AI, and more. It also helps you master topics like Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework.
Key Features
- Microsoft Certified: Azure AI Engineer Associate - AI-102 aligned training
- Access to official Microsoft handbooks aligned to the examination
- Practice tests to prepare you for the AI 102 examination
- Training sessions conducted by Microsoft-certified trainers
- Official course completion badge/certificate hosted on the Microsoft Learn portal
- Practice labs and projects with Azure labs
Skills Covered
- Azure AI Solution Design & Deployment
- Generative AI with Azure OpenAI & AI Foundry
- Computer Vision (image/video analysis)
- Natural Language Processing (NLP)
- Knowledge Mining & Document Intelligence
- Prompt Engineering & Model Optimization
- Agentic AI Workflows using Semantic Kernel
- Responsible AI Governance & Moderation
Next cohort starts on 23rd June
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Training Options
Associate
Foundation Track
- Master Python basics to OOP
- Learn HTML, CSS, and scripting
- Build logic with core Java skills
Batch starting from:
23rd June
₹20,000 ₹25,000
Enroll Now
Professional
Career Accelerator Track
(Everything in Associate+)
- Create responsive sites with Bootstrap & JS
- Develop backend with Spring Boot & JSP
- Learn basics of AI and machine learning
Batch starting from:
23rd June
₹25,000 ₹30,000
Enroll Now
Course Curriculum
Eligibility
- Bachelor’s degree in Engineering/IT or equivalent
- Basic programming knowledge (Python/C#/JavaScript)
- Familiarity with cloud platforms is beneficial
- No prior AI experience required—but helpful
Course Content
- Select the appropriate Azure AI services
- Select the appropriate service for a generative AI solution
- Select the appropriate service for a computer vision solution
- Select the appropriate service for a speech solution
- Select the appropriate service for an information extraction 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
- Choose the appropriate AI models for your solution
- Deploy AI models using the appropriate deployment options
- Install and utilize the appropriate SDKs and APIs
- 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
- Monitor an Azure AI resource
- Manage costs for Azure AI services
- Manage and protect account keys
- Manage authentication for an Azure AI Service resource
- Implement AI solutions responsibly
- Implement content moderation solutions
- Configure responsible AI insights, including content safety
- Implement responsible AI, including content filters and blocklists
- Prevent harmful behavior, including prompt shields and harm detection
- Design a responsible AI governance framework
- Build generative AI solutions with Azure AI Foundry
- Plan and prepare for a generative AI solution
- Deploy a hub, project, and necessary resources with Azure AI Foundry
- Deploy the appropriate generative AI model for your use case
- Implement a prompt flow solution
- Implement a RAG pattern by grounding a model in your data
- Evaluate models and flows
- Integrate your project into an application with Azure AI Foundry SDK
- Utilize prompt templates in your generative AI solution
- Use Azure OpenAI Service to generate content
- Provision an Azure OpenAI Service resource
- Select and deploy an Azure OpenAI model
- Submit prompts to generate code and natural language responses
- Use the DALL-E model to generate images
- Integrate Azure OpenAI into your own application
- Use large multimodal models in Azure OpenAI
- Implement an Azure OpenAI Assistant
- Optimize and operationalize a generative AI solution
- Configure parameters to control generative behavior
- Configure model monitoring and diagnostic settings, including performance and resource consumption
- Optimize and manage resources for deployment, including scalability and foundational model updates
- Enable tracing and collect feedback
- Implement model reflection
- Deploy containers for use on local and edge devices
- Implement orchestration of multiple generative AI models
- Apply prompt engineering techniques to improve responses
- Fine-tune an generative model
- Create custom agents
- Understand the role and use cases of an agent
- Configure the necessary resources to build an agent
- Create an agent with the Azure AI Agent Service
- Implement complex agents with Semantic Kernel and Autogen
- Implement complex workflows including orchestration for a multi-agent solution, multiple users, and autonomous capabilities
- Test, optimize and deploy an agent
- 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 vision models
- 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
- Build a custom vision model code first
- 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
- Analyze and translate text
- Extract key phrases and entities
- Determine sentiment of text
- Detect the language used in text
- Detect personally identifiable information (PII) in text
- Translate text and documents by using the Azure AI Translator service
- Process and translate speech
- Integrate generative AI speaking capabilities in an application
- Implement text-to-speech and speech-to-text using Azure AI Speech
- Improve text-to-speech by using Speech Synthesis Markup Language (SSML)
- Implement custom speech solutions with Azure AI Speech
- Implement intent and keyword recognition with Azure AI Speech
- Translate speech-to-speech and speech-to-text by using the Azure AI Speech service
- Implement custom language models
- Create intents, entities, and add utterances
- Train, evaluate, deploy, and test a language understanding model
- Optimize, backup, and recover language understanding model
- Consume a language model from a client application
- Create a custom question answering project
- Add question-and-answer pairs and import sources for question answering
- Train, test, and publish a knowledge base
- Create a multi-turn conversation
- Add alternate phrasing and chit-chat to a knowledge base
- Export a knowledge base
- Create a multi-language question answering solution
- Implement custom translation, including training, improving, and publishing a custom model
- Implement an Azure AI Search solution
- Provision an Azure AI Search resource, create an index, and define a skillset
- Implement custom skills and include them in a skillset
- Create and run an indexer
- Query an index, including syntax, sorting, filtering, and wildcards
- Manage Knowledge Store projections, including file, object, and table projections
- Implement semantic and vector store solutions
- 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
- Extract information with Azure AI Content Understanding
- Create an OCR pipeline to extract text from images and documents
- Summarize, classify, and detect attributes of documents
- Extract entities, tables, and images from documents
- Process and ingest documents, images, videos, and audio with Azure AI Content Understanding
Course Certificate
Salary Scale
Maximum
30 LPA
Average
15 LPA
Minimum
6 LPA
Job Role
- Azure AI Engineer
- Cognitive Services Developer
- Bot Developer
- AI/ML Solution Architect
- AI Consultant
- AI Product Manager
Tools & Technologies
Why Join this Program
Develop skills for real career growth
Cutting-edge curriculum designed in guidance with industry and academia to develop job-ready skills
Learn from experts active in their field, not out-of-touch trainers
Leading practitioners who bring current best practices and case studies to sessions that fit into your work schedule.
Learn by working on real-world problems
Capstone projects involving real world data sets with virtual labs for hands-on learning
Structured guidance ensuring learning never stops
24×7 Learning support from mentors and a community of like-minded peers to resolve any conceptual doubts
Azure AI Certification FAQs
No, the course starts with foundational concepts and gradually progresses to advanced Azure AI implementations.
Yes, the course includes lab-based learning with real Azure tools and SDKs.
Yes, if you have some coding experience and a basic understanding of cloud or APIs, this course is a great way to transition into the AI field.
Yes, the curriculum includes building with Azure OpenAI, prompt engineering, and deploying generative models like GPT and DALL-E.
Absolutely. It’s ideal for professionals aiming to pivot into AI roles or upskill within Azure’s AI stack.