Azure AI Engineer (AI-102) Certification Preparation Program
Duration
2 Day
Level
Basic to Advanced Level
Design and Tailor this course
As per your team needs
Overview
This intensive 2-day certification preparation program is designed to equip participants with the technical depth, architectural clarity, and hands-on experience required to successfully pass the AI-102: Designing and Implementing a Microsoft Azure AI Solution exam. The course blends foundational concepts with advanced implementation practices across Azure AI services including cognitive services, language, vision, speech, conversational AI, knowledge mining, and generative AI integration.
Participants will gain exam-oriented insights, architectural design thinking, real-world troubleshooting exposure, and best practices for building secure, scalable, and production-ready AI solutions on Azure.
Audience
- Professionals preparing for AI-102 certification
- AI Engineers and Cloud Engineers working with Azure AI services
- Developers integrating AI capabilities into enterprise applications
- Solution Architects designing AI-driven systems
- Data Engineers expanding into AI solution implementation
- Consultants delivering Azure AI implementations
Prerequisites
- Basic knowledge of Azure fundamentals (AZ-900 level recommended)
- Understanding of REST APIs and JSON
- Basic programming knowledge (Python or C# preferred)
- Familiarity with cloud concepts
Curriculum
Module 5: Speech & Multimodal Solutions
Topics
- Speech-to-text
- Text-to-speech
- Translation services
- Real-time streaming scenarios
Subtopics
- Speech SDK implementation
- Custom speech models
- Performance and latency optimization
Sample Questions / Tips & Tricks
- Implementing speech recognition in applications using Azure AI Speech
- Building real-time transcription workflow
- Optimizing audio input format and batching for low latency
Module 6: Knowledge Mining & Document Intelligence
Topics
- Azure AI Document Intelligence
- Form recognizer models
- Azure AI Search integration
- Indexing strategies
Subtopics
- Prebuilt vs custom extraction models
- Cognitive skillsets
- Enrichment pipelines
- Query optimization
Sample Questions / Tips & Tricks
- Extracting structured data from PDFs
- Creating search index with cognitive enrichment
- Designing searchable knowledge stores for enterprise scenarios
Module 7: Generative AI & Azure OpenAI Integration
Topics
- Capabilities of Azure OpenAI Service
- Prompt engineering principles
- Retrieval Augmented Generation (RAG)
- Embeddings and vector search
Subtopics
- Model selection strategies
- Token management
- Content filtering and safety
- Cost governance
Sample Questions / Tips & Tricks
- Calling Azure OpenAI APIs securely
- Implementing RAG with Azure AI Search
- Building enterprise Q&A assistant with grounding data
- Managing token limits and response optimization
Module 8: Security, Governance & Production Readiness
Topics
- Authentication & authorization
- Role-based access control (RBAC)
- Key Vault integration
- Network security
Subtopics
- Managed identities
- Private endpoints
- Data privacy considerations
- Monitoring and logging
Sample Questions / Tips & Tricks
- Securing AI resources using RBAC
- Implementing secrets management with Azure Key Vault
- Monitoring usage and performance via Azure Monitor
- Designing secure production deployments
Certification Preparation & Case Study
End-to-End Case Study: Designing AI Solution for Retail Enterprise
- Architecture discussion and design trade-offs
- Scalability and performance considerations
- Cost optimization strategies
- Troubleshooting common exam scenarios
- Practice questions walkthrough
- Exam readiness checklist
This completes the structured, exam-aligned AI-102 preparation outline covering implementation, security, governance, and enterprise deployment scenarios.
After completing this program, participants will be able to:
• Design secure and scalable Azure AI solutions
• Implement multimodal AI capabilities in enterprise systems
• Integrate generative AI responsibly into business workflows
• Optimize AI workloads for performance and cost
• Troubleshoot production AI implementations
• Confidently attempt and pass the AI-102 certification exam
• Deliver measurable business value through AI-driven automation, customer intelligence, and knowledge acceleration
Duration
2 Day
Level
Basic to Advanced Level
Design and Tailor this course
As per your team needs
