# KodeKloud: Beta Courses AI-102: Microsoft Certified Azure AI Engineer Associate

## AI-102: Microsoft Certified Azure AI Engineer Associate

### Introduction

- [Course Introduction](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Introduction/Course-Introduction/page.md): Introductory course preparing learners for Microsoft Azure AI Engineer Associate certification, teaching Azure AI services, hands-on labs, governance, and exam-focused guidance.
- [Certification Details](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Introduction/Certification-Details/page.md): Concise guide to AI-102 Azure AI Engineer certification, exam domains, required skills, and course resources with labs, mock exams, and study guidance to prepare for the test

### Introduction to AI and Azure AI Services

- [Module Introduction](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Introduction-to-AI-and-Azure-AI-Services/Module-Introduction/page.md): Overview of AI fundamentals, distinctions between AI, machine learning, and data science, and how Azure AI services and tools support building, deploying, and monitoring intelligent solutions.
- [What Is Artificial Intelligence](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Introduction-to-AI-and-Azure-AI-Services/What-Is-Artificial-Intelligence/page.md): Overview of artificial intelligence concepts, applications, developer skills, and responsible governance for building and deploying AI-powered systems.
- [Responsible AI Considerations](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Introduction-to-AI-and-Azure-AI-Services/Responsible-AI-Considerations/page.md): Guidelines for designing, deploying, and governing AI systems to ensure fairness, safety, privacy, inclusiveness, transparency, and accountability throughout the lifecycle.
- [Azure Machine Learning](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Introduction-to-AI-and-Azure-AI-Services/Azure-Machine-Learning/page.md): Overview of Azure Machine Learning, Microsoft's cloud service for building, training, deploying, and managing machine learning models with MLOps, experiment tracking, and scalable compute.
- [Azure AI Services](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Introduction-to-AI-and-Azure-AI-Services/Azure-AI-Services/page.md): Overview of Azure AI Services and how to integrate language, speech, vision, and generative AI capabilities into applications with minimal code and managed APIs
- [Azure AI Search](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Introduction-to-AI-and-Azure-AI-Services/Azure-AI-Search/page.md): Overview of Azure AI Search, an AI-powered service that enriches, indexes, and semantically ranks documents using OCR, NLP, embeddings, and knowledge mining for improved enterprise search

### Get Started with Azure AI Services

- [Module Introduction](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Get-Started-with-Azure-AI-Services/Module-Introduction/page.md): Intro to Azure AI Services showing how to call prebuilt language, speech, vision, and generative models via REST APIs and SDKs and integrate them into cloud applications.
- [Deploying Azure AI Services](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Get-Started-with-Azure-AI-Services/Deploying-Azure-AI-Services/page.md): Guide for provisioning and configuring Azure AI Services, selecting resource types, managing endpoints and keys, planning deployments, and connecting applications via REST APIs or language SDKs
- [Working with Azure AI Services](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Get-Started-with-Azure-AI-Services/Working-with-Azure-AI-Services/page.md): Guide to creating Azure AI Language services and performing sentiment analysis using Python SDK and REST API, comparing approaches and covering endpoints, keys, security, and best practices.

### Using Azure AI Services for Enterprise Applications

- [Module Introduction](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Using-Azure-AI-Services-for-Enterprise-Applications/Module-Introduction/page.md): Guide to operating Azure AI services in production by securing access, monitoring performance and costs, and deploying containerized models for reliable, scalable enterprise and edge environments.
- [Securing Azure AI Services](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Using-Azure-AI-Services-for-Enterprise-Applications/Securing-Azure-AI-Services/page.md): Guide on securing Azure AI services by using key rotation, Azure Key Vault, and Managed Identity to prevent credential leakage, enforce least privilege, and simplify secret rotation.
- [Monitoring Azure AI Services](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Using-Azure-AI-Services-for-Enterprise-Applications/Monitoring-Azure-AI-Services/page.md): Guide to monitoring Azure AI services using metrics, logs, diagnostics, and alerts.
- [Containerizing Azure AI Services](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Using-Azure-AI-Services-for-Enterprise-Applications/Containerizing-Azure-AI-Services/page.md): Guide to deploying and running Azure AI services in containers, covering deployment options, data control, scaling, and a hands-on Text Analytics Sentiment container example

### Analyzing Videos

- [Module Introduction](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Analyzing-Videos/Module-Introduction/page.md): Overview of using Azure Video Indexer to extract searchable video metadata including transcripts, speaker diarization, OCR, emotions, topics, and integrate insights via portal or APIs
- [Video Indexer](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Analyzing-Videos/Video-Indexer/page.md): Overview of Azure AI Video Indexer and how to create resources, upload videos, and retrieve searchable insights such as transcripts, speaker labels, topics, sentiment, faces, and OCR
- [Building Insights](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Analyzing-Videos/Building-Insights/page.md): Using custom AI models and Video Indexer to extract insights from video and audio including face recognition, domain-aware transcription, brand detection, and API or widget integration.

### Analyzing Text

- [Module Introduction](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Analyzing-Text/Module-Introduction/page.md): Overview of AI-powered text analysis tasks and best practices for language detection, key phrase extraction, sentiment, PII detection, summarization, entity linking, translation and pipeline design
- [Azure AI Language Services](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Analyzing-Text/Azure-AI-Language-Services/page.md): Overview of Azure AI Language Services and its text analysis capabilities, examples and best practices for summarization, entity recognition, PII redaction, sentiment, and SDK or REST integration
- [Working with Azure AI Language Services](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Analyzing-Text/Working-with-Azure-AI-Language-Services/page.md): Guide to Azure AI Language Services text analysis features and examples, covering language detection, key phrase extraction, sentiment, named entity recognition, entity linking, summarization, and PII detection.

### Translating Text

- [Module Introduction](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Translating-Text/Module-Introduction/page.md): Guide to using AI and Azure Translator for scalable multilingual translation, plus customizing domain-specific terminology and compliance considerations
- [Translator Service](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Translating-Text/Translator-Service/page.md): An API that detects language, translates text into multiple target languages, and transliterates scripts for fast multilingual communication, localization, and pronunciation assistance.
- [Working with Translator Service](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Translating-Text/Working-with-Translator-Service/page.md): Guide to using Azure Translator to detect language, translate text into multiple languages, and transliterate scripts with REST examples and a Python SDK sample.
- [Custom Translation](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Translating-Text/Custom-Translation/page.md): Explains how to train and deploy Azure Custom Translator models using parallel corpora so translations reflect organization or industry specific terminology

### Develop a Question Answering Solution

- [Module Introduction](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Develop-a-Question-Answering-Solution/Module-Introduction/page.md): Guide to building and maintaining a question answering knowledge base with Azure AI Language, covering ingestion, multi-turn context, ranking, publishing, security, and active learning
- [Introduction to QnA](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Develop-a-Question-Answering-Solution/Introduction-to-QnA/page.md): Explains QnA systems and knowledge bases, contrasts static answers with dynamic language understanding, and guides building, testing, publishing, and integrating KBs via APIs and SDKs.
- [Working with Question Answering](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Develop-a-Question-Answering-Solution/Working-with-Question-Answering/page.md): Guide to creating, populating, deploying, and querying Azure Custom Question Answering projects, with request and response examples and prediction endpoint usage.
- [Fine Tuning Question Answering Performance](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Develop-a-Question-Answering-Solution/Fine-Tuning-Question-Answering-Performance/page.md): Guide to improving Azure Custom Question Answering using implicit learning, explicit user feedback, and synonyms to increase accuracy and relevance.

### Develop a Conversational Language Understanding App

- [Module Introduction](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Develop-a-Conversational-Language-Understanding-App/Module-Introduction/page.md): Guide to building conversational language-understanding applications with Azure AI Language covering provisioning resources, modeling intents utterances and entities, entity recognition, training evaluation and deployment best practices
- [What Is Language Understanding](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Develop-a-Conversational-Language-Understanding-App/What-Is-Language-Understanding/page.md): Explains language understanding pipeline, intent and entity extraction, response execution, and differences between NLP NLU and CLU for designing reliable conversational applications.
- [Intents Utterances and Entities](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Develop-a-Conversational-Language-Understanding-App/Intents-Utterances-and-Entities/page.md): Describes intents, utterances, and entities in conversational AI and guidance for designing intent classification and entity extraction to build reliable NLU systems
- [Azure AI Language Capabilities](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Develop-a-Conversational-Language-Understanding-App/Azure-AI-Language-Capabilities/page.md): Overview of Azure AI Language Services features and a Language Studio walkthrough to build, train, deploy, and consume a conversational language understanding project with intents, entities, and Python SDK
- [Training Testing Publishing and Reviewing](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Develop-a-Conversational-Language-Understanding-App/Training-Testing-Publishing-and-Reviewing/page.md): Lifecycle guide for conversational language understanding models covering training, testing, publishing, monitoring, and retraining to improve intent detection and entity extraction.

### Custom Classification and Named Entity Extraction

- [Module Introduction](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Custom-Classification-and-Named-Entity-Extraction/Module-Introduction/page.md): Guide to building custom document classifiers and named entity extraction models covering labeling, training, evaluation, deployment, and post-deployment monitoring and best practices.
- [Custom Text Classification](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Custom-Classification-and-Named-Entity-Extraction/Custom-Text-Classification/page.md): Guide for building, training, and deploying custom text classification models using Azure Language Studio including data labeling, evaluation, deployment, SDK examples, and best practices.
- [Custom Named Entity Recognition](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Custom-Classification-and-Named-Entity-Extraction/Custom-Named-Entity-Recognition/page.md): Guide to building and deploying Custom Named Entity Recognition models in Azure AI Language Studio, covering data connection, annotation, training, evaluation, and best practices
- [Review and Improve Model](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Custom-Classification-and-Named-Entity-Extraction/Review-and-Improve-Model/page.md): Guide to evaluating and iteratively improving ML models with metrics, error analysis, data augmentation, monitoring, and practical steps for handling low training data and deployment

### Speech Recognition, Translation, and Synthesis

- [Module Introduction](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Speech-Recognition-Translation-and-Synthesis/Module-Introduction/page.md): Overview of speech recognition, translation, and synthesis, teaching setup, SSML customization, and practical integration for building voice enabled multilingual and accessible applications.
- [Speech Service](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Speech-Recognition-Translation-and-Synthesis/Speech-Service/page.md): Overview of Azure AI Speech services, including speech to text, text to speech, translation, speaker recognition, intent extraction, SDK and REST usage, examples, and best practices.
- [Speech to Text and Text to Speech](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Speech-Recognition-Translation-and-Synthesis/Speech-to-Text-and-Text-to-Speech/page.md): Overview of Azure Speech-to-Text and Text-to-Speech capabilities, pipelines, APIs, SDKs, result fields, and using Azure Portal and Speech Studio for testing and integration.
- [Audio Format and Voices](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Speech-Recognition-Translation-and-Synthesis/Audio-Format-and-Voices/page.md): Guidance on choosing audio formats, sample rates, and voice types and configuring Azure Speech SDK for neural and standard text to speech with code examples
- [Speech Synthesis Markup Language SSML](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Speech-Recognition-Translation-and-Synthesis/Speech-Synthesis-Markup-Language-SSML/page.md): Explains SSML, an XML markup for controlling text-to-speech voice, prosody, pronunciation, pauses, expressive styles, and using Azure Speech Studio and SDKs to author and synthesize speech.
- [Translating Speech to Text](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Speech-Recognition-Translation-and-Synthesis/Translating-Speech-to-Text/page.md): Guide to using Azure Speech Service to transcribe spoken audio, translate into multiple languages, and optionally synthesize translated text, with pipeline explanation and Python examples.

### Get Started with Azure OpenAI Service

- [Module Introduction](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Get-Started-with-Azure-OpenAI-Service/Module-Introduction/page.md): Introduction to provisioning Azure OpenAI resources, deploying generative models, and using the Azure AI Foundry portal for experimentation, model management, and governance
- [What Is Generative AI](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Get-Started-with-Azure-OpenAI-Service/What-Is-Generative-AI/page.md): Overview of generative AI, its evolution, key model types, applications, capabilities, risks, and responsible deployment practices
- [Deploying an Azure OpenAI Resource](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Get-Started-with-Azure-OpenAI-Service/Deploying-an-Azure-OpenAI-Resource/page.md): Guide for creating and managing an Azure OpenAI resource via the Azure portal or CLI, including post deployment keys, endpoints, and troubleshooting
- [AI Foundry Portal](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Get-Started-with-Azure-OpenAI-Service/AI-Foundry-Portal/page.md): Overview of Azure AI Foundry Portal for discovering, deploying, customizing, and testing generative AI models and workflows including chat, images, audio, embeddings, and fine-tuning.
- [Deploying Generative AI Models](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Get-Started-with-Azure-OpenAI-Service/Deploying-Generative-AI-Models/page.md): Guide to deploying and integrating generative AI models with Azure AI Foundry covering quota checks, portal and CLI deployments including fine tuning, and SDK-based application integration.
- [Using Prompts to Get Completions and Testing Models](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Get-Started-with-Azure-OpenAI-Service/Using-Prompts-to-Get-Completions-and-Testing-Models/page.md): Guide to designing and testing prompts for generating model completions using Azure OpenAI Studio, with tips and example Python code

### Develop Apps with Azure OpenAI Service

- [Module Introduction](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Develop-Apps-with-Azure-OpenAI-Service/Module-Introduction/page.md): Guide to deploying and integrating Azure OpenAI models into applications, covering REST API, SDKs, chat, summarization, RAG, security, and backend best practices.
- [Integrating Azure OpenAI into Your App](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Develop-Apps-with-Azure-OpenAI-Service/Integrating-Azure-OpenAI-into-Your-App/page.md): Guide to integrating Azure OpenAI into applications, covering endpoints, authentication, chat completion and embeddings usage, security best practices, and example request and message patterns
- [Using the Azure OpenAI REST API](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Develop-Apps-with-Azure-OpenAI-Service/Using-the-Azure-OpenAI-REST-API/page.md): Guide to using Azure OpenAI REST API endpoints—completions, embeddings, chat completions—with example request and response payloads, deployment details, and curl and Postman tips.
- [Using Language Specific SDKs](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Develop-Apps-with-Azure-OpenAI-Service/Using-Language-Specific-SDKs/page.md): Explains using language-specific Azure OpenAI SDKs, shows a Python Flask integration, environment variable security, and tuning parameters for chat-based model deployments.

### Apply Prompt Engineering

- [Module Introduction](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Apply-Prompt-Engineering/Module-Introduction/page.md): Guide to prompt engineering for Azure OpenAI covering prompt design, endpoint differences, advanced techniques, safety, testing, and deploying reliable controllable AI outputs.
- [What Is Prompt Engineering](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Apply-Prompt-Engineering/What-Is-Prompt-Engineering/page.md): A practical guide to prompt engineering teaching specificity, structured outputs, added context, and bias mitigation so generative AI yields more accurate, relevant, and fair responses.
- [Using Prompt Engineering](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Apply-Prompt-Engineering/Using-Prompt-Engineering/page.md): How to design structured prompts and system messages to elicit more relevant, actionable, and prioritized responses from language models, with examples and a practical checklist.
- [Providing Clear Instructions](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Apply-Prompt-Engineering/Providing-Clear-Instructions/page.md): Guidelines for writing clear, structured prompts—using primary, supporting, and grounding content, cues, and explicit output formats to improve AI response relevance and usability.
- [Using System Messages](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Apply-Prompt-Engineering/Using-System-Messages/page.md): Explains system messages that set persistent assistant role, tone, constraints, and output format, with best practices and examples for effective prompt engineering
- [Conversation History](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Apply-Prompt-Engineering/Conversation-History/page.md): Explains using conversation history and few-shot examples to guide AI behavior, demonstrating email classification into Work Personal or Spam and providing best practices for prompt design
- [Chain of Thought](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Apply-Prompt-Engineering/Chain-of-Thought/page.md): Describes chain-of-thought prompting that elicits step-by-step reasoning from models to improve accuracy, transparency, and explainability.

### Implement Retrieval Augmented Generation (RAG) with Azure OpenAI Service

- [Module Introduction](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Implement-Retrieval-Augmented-Generation-RAG-with-Azure-OpenAI-Service/Module-Introduction/page.md): Guide to implementing Retrieval-Augmented Generation with Azure OpenAI Service, covering embeddings, vector search, REST API and SDK workflows to integrate and retrieve your data for grounded model responses
- [What Is RAG](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Implement-Retrieval-Augmented-Generation-RAG-with-Azure-OpenAI-Service/What-Is-RAG/page.md): Describes Retrieval-Augmented Generation, combining LLMs with vectorized external knowledge to generate up-to-date, grounded answers with source citations.
- [How Azure OpenAI Can Use Your Data](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Implement-Retrieval-Augmented-Generation-RAG-with-Azure-OpenAI-Service/How-Azure-OpenAI-Can-Use-Your-Data/page.md): Explains using Retrieval-Augmented Generation with Azure OpenAI to ground responses in private company documents, reducing hallucination and ensuring traceable, domain-specific answers.
- [Working with Custom Data Sources](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Implement-Retrieval-Augmented-Generation-RAG-with-Azure-OpenAI-Service/Working-with-Custom-Data-Sources/page.md): Guide to grounding Azure OpenAI with custom data sources using RAG, including chat playground, Blob Storage indexing, REST and SDK patterns, and a Python end to end example.

### Implementing an Intelligent Search Solution

- [Module Introduction](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Implementing-an-Intelligent-Search-Solution/Module-Introduction/page.md): Guide to building end to end Azure AI Search solutions by provisioning services, defining indexes, adding custom enrichment skills, and storing enriched content for advanced queries and analytics
- [Azure AI Search](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Implementing-an-Intelligent-Search-Solution/Azure-AI-Search/page.md): Cloud search service that uses AI for semantic understanding, spell correction, enrichment, and personalized relevance to improve search and product discovery.
- [Enrichment Pipeline](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Implementing-an-Intelligent-Search-Solution/Enrichment-Pipeline/page.md): Explains Azure Cognitive Search enrichment pipeline converting raw files and images into structured searchable index documents using AI skills like language detection OCR key phrase extraction and entity recognition.

### Create a Custom Skill for Azure AI Search

- [Module Introduction](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Create-a-Custom-Skill-for-Azure-AI-Search/Module-Introduction/page.md): How to design, implement, host, and register custom HTTP JSON skills to extend Azure AI Search enrichment pipelines, covering API contract, hosting, authentication, and deployment best practices.
- [What Are Custom Skills](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Create-a-Custom-Skill-for-Azure-AI-Search/What-Are-Custom-Skills/page.md): Explains custom skills for Azure AI Search enabling domain-specific document enrichment, extraction, ML integration, and indexing to improve search accuracy and handle domain-specific logic
- [Custom Skill Interfaces](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Create-a-Custom-Skill-for-Azure-AI-Search/Custom-Skill-Interfaces/page.md): Explains Azure AI Search custom skill input and output JSON schemas, required recordId and data structure, plus error and warning patterns for reliable enrichment
- [Adding a Custom Skill to a Skillset](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Create-a-Custom-Skill-for-Azure-AI-Search/Adding-a-Custom-Skill-to-a-Skillset/page.md): Guide to adding a custom Web API skill to Azure Cognitive Search skillsets, implementing an Azure Function extractor and mapping outputs into an indexer for enrichment.

### Creating a Knowledge Store

- [Module Introduction](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Creating-a-Knowledge-Store/Module-Introduction/page.md): Explains designing and configuring an Azure AI knowledge store to persist enriched pipeline outputs, map projections for analytics, and enable consumption by BI, Synapse, and automation tools.
- [What Is Knowledge Store](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Creating-a-Knowledge-Store/What-Is-Knowledge-Store/page.md): Explains Azure AI Search Knowledge Store storing extracted insights from documents as structured projections for analytics, search, and integration.
- [Using the Shaper Skill for Projections](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Creating-a-Knowledge-Store/Using-the-Shaper-Skill-for-Projections/page.md): Explains using Azure Cognitive Search Shaper skill to project and structure extracted data into compact JSON for easier querying and storage
- [Implementing a Knowledge Store](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Creating-a-Knowledge-Store/Implementing-a-Knowledge-Store/page.md): Guide to configuring Azure Cognitive Search knowledge store to persist enrichment outputs as JSON objects, tables, or files, with architecture, portal steps, and skillset JSON examples.

### Develop a Document Intelligence Solution

- [Module Introduction](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Develop-a-Document-Intelligence-Solution/Module-Introduction/page.md): Overview of Azure AI Document Intelligence, covering model types, labeling and training custom models, and integrating document analysis APIs into applications.
- [Document Intelligence Service](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Develop-a-Document-Intelligence-Solution/Document-Intelligence-Service/page.md): Explains automating extraction and structuring of text and data from documents using Document Intelligence for faster, accurate processing, model types, deployments, outputs, and a university admissions scenario.
- [Working with Document Intelligence Service](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Develop-a-Document-Intelligence-Solution/Working-with-Document-Intelligence-Service/page.md): Guide to Azure AI Document Intelligence covering REST and SDK calls, polling for results, interpreting structured OCR outputs, and testing prebuilt document models in Document Intelligence Studio.
- [Training Custom Models](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Develop-a-Document-Intelligence-Solution/Training-Custom-Models/page.md): Guide to training custom classification and extraction models with Azure Document Intelligence, covering requirements, model types, Studio workflow, auto-labeling, and a Python example.
- [Accuracy and Confidence Scores](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Develop-a-Document-Intelligence-Solution/Accuracy-and-Confidence-Scores/page.md): Explains estimated per-field accuracy versus per-prediction confidence in Azure Document Intelligence, how to view them in Studio, and how to use them for deployment and runtime decisions
- [Analyzing Documents Using Custom Model](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Develop-a-Document-Intelligence-Solution/Analyzing-Documents-Using-Custom-Model/page.md): Guide for running a deployed Azure Document Intelligence custom model to analyze documents, authenticate requests, use SDKs, and retrieve structured AnalyzeResult via poller.

### Analyze and Manipulate Images

- [Image Analysis Using Azure AI Vision](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Analyze-and-Manipulate-Images/Image-Analysis-Using-Azure-AI-Vision/page.md): Overview of Azure AI Vision image analysis capabilities, outputs, use cases, and deployment guidance for object detection, OCR, captioning, and multimodal embeddings
- [Working with Image Analysis](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Analyze-and-Manipulate-Images/Working-with-Image-Analysis/page.md): Guide to using Azure AI Vision to analyze images via REST and SDKs, configure analysis options, and parse structured results like captions, objects, OCR, and smart crops.
- [OCR Using Azure AI Vision](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Analyze-and-Manipulate-Images/OCR-Using-Azure-AI-Vision/page.md): Guide to using Azure AI Vision Read API for OCR, comparing Read and Document Intelligence, explaining JSON output structure and showing a Python example for extracting text and coordinates

### Detecting Faces with the Azure AI Vision

- [Face Detection Analysis and Recognition](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Detecting-Faces-with-the-Azure-AI-Vision/Face-Detection-Analysis-and-Recognition/page.md): Overview of Azure face detection, analysis, and recognition workflows, comparing Image Analysis and Face API, use cases, pipeline, capabilities, and privacy considerations
- [Considerations for Face Detection and Recognition](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Detecting-Faces-with-the-Azure-AI-Vision/Considerations-for-Face-Detection-and-Recognition/page.md): Guidance for responsible deployment of face detection and recognition systems emphasizing access controls, data privacy and security, transparency, fairness, and legal compliance.
- [Face Service](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Detecting-Faces-with-the-Azure-AI-Vision/Face-Service/page.md): Overview of Azure Face Service features for detecting, analyzing, and recognizing faces including attributes, landmarks, verification, persisted recognition, liveness detection, and privacy and compliance guidance.
- [Face Detection Using Azure AI Vision](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Detecting-Faces-with-the-Azure-AI-Vision/Face-Detection-Using-Azure-AI-Vision/page.md): Guide to using Azure AI Vision Face API to detect faces, return bounding boxes, landmarks, and optional attributes, with SDK examples, parameters, and deployment steps.

### Custom Vision Models with Azure AI Custom Vision

- [Custom Vision Model](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Custom-Vision-Models-with-Azure-AI-Custom-Vision/Custom-Vision-Model/page.md): Guide to using Azure Custom Vision to train, deploy, and improve image classification and object detection models for domain specific defect detection, inspection workflows, and best practices.
- [Image Classification and Object Detection](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Custom-Vision-Models-with-Azure-AI-Custom-Vision/Image-Classification-and-Object-Detection/page.md): Explains differences between image classification and object detection, workflows, use cases, annotation formats, and best practices for training and evaluation.
- [Training Custom Models](https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Custom-Vision-Models-with-Azure-AI-Custom-Vision/Training-Custom-Models/page.md): Guide to building, training, evaluating, and publishing image classification and object detection models with Azure Custom Vision Studio.