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- Expired on August 30, 2025
- Last Update: August 29, 2025
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Price:
44.99 $0 $
About This Course
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 Integration
Language, Speech, Vision, and Decision services
Knowledge mining and intelligent search
Designing secure, efficient service integrations
Azure Machine Learning (Azure ML)
Building, training, and deploying machine learning models
Using pipelines, datasets, and compute clusters
Managing and optimizing ML lifecycle with MLOps principles
Conversational AI & Azure Bot Framework
Designing and implementing chatbots using Azure Bot Service
Integrating Language Understanding (LUIS / Conversational Language Understanding)
Handling multi-turn conversations and adaptive dialogs
Azure OpenAI & Generative AI Solutions (New for 2025)
Designing enterprise-ready generative AI solutions
Fine-tuning GPT models for custom scenarios
Integrating AI safely and securely into business workflows
Security, Compliance, & Responsible AI
Applying Microsoft’s Responsible AI guidelines
Implementing authentication, authorization, and data protection
Evaluating bias, explainability, and regulatory compliance
Monitoring, Optimization & Automation
Using Application Insights, Log Analytics, and Azure Monitor
Automating model retraining and endpoint scaling
Cost optimization strategies for AI workloads
Each 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 architecture
Design scalable AI-driven solutions leveraging Cognitive Services and Azure ML
Integrate AI models into applications with performance, security, and compliance in mind
Optimize cost, scalability, and latency trade-offs for enterprise-grade deployments
Apply Responsible AI principles to design transparent and ethical AI systems
Implement CI/CD pipelines to automate testing, deployment, and monitoring of AI solutions
By 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 knowledge
Design and implement end-to-end AI solutions across Azure Cognitive Services, Azure ML, and OpenAI integrations
Balance business, technical, and regulatory constraints when building production-ready AI systems
Justify architectural decisions with scalability, security, performance, and cost trade-offs
Prepare for enterprise-level AI solution design and position yourself for advanced Azure AI certifications
Our content is continuously updated to reflect:
The latest AI-102 exam blueprint and question formats
Microsoft’s evolving Azure AI ecosystem (Azure OpenAI, Cognitive Services, Azure ML, Copilot integrations)
Industry trends in generative AI, responsible AI, automation, and enterprise-scale deployments
Whether 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.
