Free Udemy Course: Microsoft AI-102: Azure AI Engineer Associate Practice Exams

Prepare for the Microsoft AI-102 Exam: Designing and Implementing an Azure AI Solution This course provides the most realistic preparation for the Microsoft AI-102 certification exam, meticulously updated to match Microsoft’s latest exam blueprint, domains, and question styles.Unlike product-overview training, this is a solution-focused, scenario-driven course designed to test your ability to design, implement, and optimize AI-powered applications using Azure Cognitive Services, Azure Machine Learning, and Azure OpenAI capabilities.You’ll master all key AI-102 exam domains, including:Azure Cognitive Services IntegrationLanguage, Speech, Vision, and Decision servicesKnowledge mining and intelligent searchDesigning secure, efficient service integrationsAzure Machine Learning (Azure ML)Building, training, and deploying machine learning modelsUsing pipelines, datasets, and compute clustersManaging and optimizing ML lifecycle with MLOps principlesConversational AI & Azure Bot FrameworkDesigning and implementing chatbots using Azure Bot ServiceIntegrating Language Understanding (LUIS / Conversational Language Understanding)Handling multi-turn conversations and adaptive dialogsAzure OpenAI & Generative AI Solutions (New for 2025)Designing enterprise-ready generative AI solutionsFine-tuning GPT models for custom scenariosIntegrating AI safely and securely into business workflowsSecurity, Compliance, & Responsible AIApplying Microsoft’s Responsible AI guidelinesImplementing authentication, authorization, and data protectionEvaluating bias, explainability, and regulatory complianceMonitoring, Optimization & AutomationUsing Application Insights, Log Analytics, and Azure MonitorAutomating model retraining and endpoint scalingCost optimization strategies for AI workloadsEach practice scenario features real-world AI case studies and trade-off analysis to ensure you don’t just memorize concepts—you apply them:Evaluate business and technical requirements to select the right Azure AI architectureDesign scalable AI-driven solutions leveraging Cognitive Services and Azure MLIntegrate AI models into applications with performance, security, and compliance in mindOptimize cost, scalability, and latency trade-offs for enterprise-grade deploymentsApply Responsible AI principles to design transparent and ethical AI systemsImplement CI/CD pipelines to automate testing, deployment, and monitoring of AI solutionsBy the end of this course, you’ll be able to:Confidently approach the AI-102 exam with a solution architect’s mindset, not just developer-level knowledgeDesign and implement end-to-end AI solutions across Azure Cognitive Services, Azure ML, and OpenAI integrationsBalance business, technical, and regulatory constraints when building production-ready AI systemsJustify architectural decisions with scalability, security, performance, and cost trade-offsPrepare for enterprise-level AI solution design and position yourself for advanced Azure AI certificationsOur content is continuously updated to reflect:The latest AI-102 exam blueprint and question formatsMicrosoft’s evolving Azure AI ecosystem (Azure OpenAI, Cognitive Services, Azure ML, Copilot integrations)Industry trends in generative AI, responsible AI, automation, and enterprise-scale deploymentsWhether you’re aiming to pass the AI-102 exam, master Azure AI solution design, or lead enterprise AI initiatives, this course equips you with practical, exam-ready expertise—not just theory.Join thousands of AI engineers, developers, and solution architects worldwide who’ve accelerated their careers with battle-tested AI-102 preparation, and take the next step toward becoming a Microsoft Certified Azure AI Engineer.