The AI-3022: Implement AI Skills in Azure AI Search course is designed to help developers and AI engineers unlock the full potential of Azure Cognitive Search by integrating advanced AI skills. Learn how to implement AI-powered search solutions that can analyze and enrich unstructured data, making it searchable and discoverable. This course focuses on practical implementation using Azure AI services, including Cognitive Search, natural language processing (NLP), computer vision, and speech recognition. Through hands-on labs and real-world scenarios, you'll learn to create AI-driven search solutions that automatically extract insights from documents, images, videos, and more, delivering smarter search experiences for users. By the end of the course, you’ll have the skills to build and deploy AI-enhanced search solutions that provide personalized, intelligent, and contextual results.
Familiarity with Azure Cognitive Search and basic knowledge of Azure services.
Some experience with cloud computing and machine learning concepts is helpful but not required.
Basic proficiency in programming languages such as C#, Python, or JavaScript will be beneficial for implementing search solutions.
Understanding of natural language processing (NLP) and text analytics can be helpful, but no prior experience with advanced AI is necessary.
Learning Objectives
By the end of the AI-3022: Implement AI Skills in Azure AI Search course, you will be able to:
Understand how Azure Cognitive Search works and how to enhance it with AI skills to process unstructured data.
Learn to integrate AI-powered cognitive skills into Azure Search to automatically extract meaningful data from documents, images, and videos.
Implement text analytics capabilities to enable search results that reflect key insights from natural language processing (NLP).
Use computer vision and image analysis skills to enhance search results by indexing and recognizing content in visual data.
Leverage speech recognition and audio analysis to make search solutions more accessible and contextually relevant.
Design search systems that provide personalized, context-aware search results based on user behavior and data patterns.
Optimize search performance using AI-driven filters, facets, and relevance tuning to deliver better search experiences.
Understand AI ethics in search systems, ensuring data privacy, security, and fairness when processing sensitive information.
Implement AI models and machine learning algorithms in search queries to enhance data retrieval, including relevance scoring and contextual matching.
Apply the knowledge gained in the course to build and deploy AI-enhanced search applications for enterprise-level systems and services.
Target Audience
This course is ideal for:
Developers and software engineers who want to integrate AI capabilities into search applications using Azure Cognitive Search.
AI engineers and data scientists interested in leveraging Azure AI skills to enhance search experiences in large-scale data systems.
Cloud architects and technical consultants focused on building AI-powered search solutions for enterprises.
Business analysts and solution architects looking to apply AI to optimize search-driven business processes, including document management, content discovery, and customer support.
Azure developers seeking to gain expertise in Azure Cognitive Search and AI skill integration for smart search applications.
Technical leaders and IT professionals wanting to understand how AI and search work together in the Azure platform to improve user experiences.
Course Prerequisites
Learning Objectives
Target Audience
Course Modules
