Microsoft AI-102 – Designing and Implementing an Azure AI Solution Certification Training Course
Length
5 days / 5 weeks
Price
$2999
Days
Mon - Fri
Why Choose This Course
The AI-102 course explores how modern applications use artificial intelligence on Microsoft Azure to solve real business problems. It focuses on building, integrating, and maintaining AI features such as language understanding, image analysis, conversational bots, and intelligent search. Instead of staying abstract, the course looks closely at how these services are applied in production environments, where performance, reliability, and security all matter.
Throughout the course, learners work with Azure AI services in a practical context, learning how different components fit together within cloud-based solutions. This includes designing AI-powered features that interact with existing applications, handling data responsibly, and monitoring solutions once they are live. Ethical and responsible use of AI is also part of the discussion, reflecting the expectations placed on organisations operating across multiple countries and regulatory frameworks.
AI-102 is designed for a global audience of developers, engineers, and solution-focused professionals who already have experience with software or cloud platforms and want to extend those skills into AI-enabled solutions. The knowledge gained applies across industries such as technology, finance, healthcare, retail, and the public sector, where AI is increasingly embedded into everyday systems. As organisations worldwide continue to adopt AI-driven services, this course provides a clear, practical pathway to understanding how those solutions are designed and implemented on Azure.
Prerequisites
- There are no formal prerequisites for this course.
- For the certification, Microsoft expects familiarity with Azure AI services and programming in Python or C#.
Exam
Candidates can achieve this certification by passing the following exam(s).
- Designing and Implementing a Microsoft Azure AI Solution (AI‑102).
Books
- AI‑102 course material included.
Delivery
- Live virtual online training attend in real-time from anywhere
Skills Gained
- Plan and manage an Azure AI solution, including governance, cost,securityand lifecycle considerations.
- Implement generative AI solutions in Azure AI Foundry, selecting models from thecatalogand evaluating performance.
- Build agentic solutions that orchestrate tools,functionsand workflows for multi‑step tasks.
- Create computer vision solutions with Azure AI Vision and custom vision scenarios.
- Develop natural language processing solutions using Azure AI Language and Speech capabilities.
- Implement knowledge mining and document intelligence with Azure AI Search and information extraction.
- Integrate services securely using SDKs and REST APIs, applying responsible AI and data protection controls.
- Design end‑to‑end architectures that meet reliability,scalabilityand complianceobjectives.
- Troubleshoot andmonitorAI applications;instrumentfor metrics,loggingand model quality.
- Prepare effectively for the AI‑102 exam using the updated skills measured and practice assessments.
Audience
- Azure AI engineers, software developers and solution architects building, managing and deploying AI solutions on Azure.
- Professionals using Python or C# who integrate AI via SDKs and REST APIs across vision, language, search and generative workloads.
Course Schedule & Pricing
Choose the schedule that fits your life — all options include full course materials & certification support
Full-time immersion for rapid certification readiness.
Balance your career while you upgrade your skills.
Maximum flexibility for busy working professionals.
Outline
- Certification overview: role,responsibilitiesand capabilities of the Azure AI Engineer Associate.
- Plan and manage Azure AI solutions: architecture design, governance,costand security planning.
- Responsible AI: content safety, risk controls, evaluation workflows in Azure AI Foundry.
- Azure AI Foundry model catalog and deployments: model choice, endpoints,usageand evaluation.
- Agents and tool integration: orchestrating multi‑tool pipelines and function calls.
- Generative AI apps: prompts, grounding, retrieval, safetyconfigurationsand metrics.
- Computer vision: image analysis, custom vision, videoscenariosand content moderation.
- Natural language processing: classification, extraction,summarisation,translationand speech.
- Knowledge mining and search: index design, skillsets, enrichmentpipelinesand query patterns.
- Document intelligence: form recognition, layout, tableextractionand integration patterns.
- SDKs and REST APIs: Python and C# usage, authentication,securityand telemetry.
- Deployment and operations: pipelines, configuration, monitoring,rollbackand DR considerations.
- Exam preparation: practice assessment, exam sandbox and Microsoft Learn paths.
- Renewal guidance: annual renewal assessment and updated English version date.
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Frequently Asked Questions (FAQ's)
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