Overview
Build Intelligent AI Applications, Copilots & AI Agents on Microsoft Azure
Master the development of modern AI-powered applications using Microsoft Azure. This comprehensive AI-103 training program enables developers to design, build, deploy, and manage intelligent applications leveraging Azure OpenAI, Large Language Models (LLMs), AI Agents, Retrieval-Augmented Generation (RAG), Prompt Engineering, and Azure AI Services.
Participants will learn how to create enterprise-grade AI assistants, copilots, conversational experiences, document intelligence solutions, knowledge assistants, and autonomous AI agents using the latest Microsoft AI ecosystem.
This course combines theory, architecture design, hands-on labs, and real-world business use cases to prepare professionals for the Microsoft AI-103 certification and enterprise AI projects.
Completing this training does not itself confer Microsoft certification.
Prerequisites
- Basic Programming Experience (Python, C#, JavaScript, or Java)
- REST APIs and JSON
- Cloud Computing Fundamentals
- Basic Azure Knowledge
Curriculum
Module 1: Introduction to Azure AI Development
- Generative AI Fundamentals
- Large Language Models (LLMs)
- Azure AI Ecosystem
- AI Application Architecture
- Azure AI Services Overview
- Azure OpenAI Overview
- Responsible AI Principles
Practical lab
- Azure AI Environment Setup
- Explore Azure AI Services
Module 2: Azure OpenAI Service
- Azure OpenAI Architecture
- Available Language Models
- Model Selection Strategies
- Text Generation
- Chat Completion Models
- Embeddings Models
- Model Parameters & Configuration
- Token Management
Practical lab
- Generate AI Responses
- Build Chat-Based Applications
Module 3: Prompt Engineering Fundamentals
- Prompt Design Techniques
- Zero-Shot Prompting
- Few-Shot Prompting
- Chain-of-Thought Prompting
- Context Management
- Prompt Testing
- Prompt Optimization
- Prompt Security
Practical lab
- Design Effective Prompts
- Optimize AI Outputs
Module 4: Developing AI Chat Applications
- Conversational AI Design
- Multi-Turn Conversations
- Context Window Management
- Session Handling
- Memory Management
- Chat History Strategies
- User Experience Design
Practical lab
- Build Intelligent Chat Assistant
- Implement Conversation Memory
Module 5: Retrieval-Augmented Generation (RAG)
- RAG Architecture
- Knowledge Grounding
- Embeddings
- Semantic Search
- Vector Databases
- Document Retrieval
- Context Enrichment
- Enterprise Knowledge Platforms
Practical lab
- Build Enterprise Knowledge Assistant
- Implement Semantic Search
Module 6: Azure AI Search Integration
- Azure AI Search Architecture
- Index Design
- Data Sources
- Search Pipelines
- Vector Search
- Hybrid Search
- Semantic Ranking
- Search Optimization
Practical lab
- Create Search Index
- Integrate RAG with AI Search
Module 7: AI Agents Development
- Introduction to AI Agents
- Agent Architecture Patterns
- Agent Instructions
- Tool Calling
- Function Calling
- Agent Planning
- Multi-Agent Systems
- Enterprise Agent Design
Practical lab
- Develop AI Agent
- Integrate External Tools
Module 8: Azure AI Foundry
- Azure AI Foundry Overview
- Projects & Workspaces
- Model Catalog
- Prompt Flow
- Agent Builder
- Model Evaluation
- Deployment Management
Practical lab
- Build AI Solution in Foundry
- Deploy AI Agent
Module 9: Document Intelligence Solutions
- Azure Document Intelligence
- OCR Processing
- Invoice Extraction
- Form Recognition
- Data Extraction
- Structured Document Processing
- Enterprise Automation
Practical lab
- Process Business Documents
- Extract Structured Data
Module 10: AI Content Safety & Responsible AI
- AI Security Fundamentals
- Content Filtering
- Prompt Injection Protection
- Data Privacy
- Ethical AI Practices
- Responsible AI Framework
- Governance Controls
Practical lab
- Implement AI Safety Controls
- Configure Content Filters
Module 11: Deploying AI Applications
- AI Application Deployment
- Azure App Services
- Container-Based Deployment
- API Management
- Configuration Management
- Scaling AI Applications
- Monitoring AI Workloads
Practical lab
- Deploy Production AI Solution
- Configure Application Monitoring
Module 12: Monitoring & Optimization
- Application Insights
- Azure Monitor
- Usage Analytics
- Token Consumption Analysis
- Cost Optimization
- Performance Optimization
- Error Handling & Troubleshooting
Practical lab
- Monitor AI Application Health
- Optimize AI Performance
Features
- Instructor-Led Expert Training
- Hands-On Practical Labs
- AI Agents & Copilot Development
- Project-Based Learning
Course Fees
Virtual Instructor-Led Training
| One-to-One Private Batch | Public Batch |
|---|---|
| Fees : ₹90,000 + 18% GST | Fees : ₹20,000 + 18% GST |
| 2hrs : Mon - Fri | 2hrs : Mon - Fri |
| 4hrs : Sat - Sun | 4hrs : Sat - Sun |
