Overview
Educora’s AI-200 training focuses on developing the backend, infrastructure, data, integration, security and monitoring layers of AI applications on Microsoft Azure. The programme covers containerised applications, Azure hosting and orchestration, AI data services and vector databases, event-driven integration, security, observability and troubleshooting.
Practical labs cover deploying AI services, implementing vector search, integrating Azure services and monitoring application operations. The course follows an AI-focused cloud development path. Completing the training does not itself confer Microsoft certification.
Prerequisites
- Participants should have at least one-year development and Microsoft Azure experience.
- They must be able to program in an Azure supported language at the intermediate level. (C#, JavaScript, Python, or Java)
- A general understanding of HTML, the HTTP protocol and REST API interfaces should be beneficial.
Curriculum
Azure AI Cloud Development Fundamentals
Module 1: Introduction to AI Cloud Development
- AI-200 Certification Overview
- Azure AI Solution Architecture
- AI Application Development Lifecycle
- Role of AI Cloud Developer
- AI-103 vs AI-200 vs AI-300
Practical lab
- Setup Azure Subscription
- Install Azure CLI
- Configure VS Code
- Create Developer Environment
Module 2: Containerized AI Applications
Topics
- Docker Fundamentals
- Container Images
- Azure Container Registry (ACR)
- Image Versioning
- Container Security
Practical lab
- Build AI API using FastAPI
- Create Docker Image
- Push Container to ACR
Azure Hosting & Orchestration
Module 3: Azure Container Apps
Topics
- Azure Container Apps
- Environment Configuration
- Secrets Management
- Autoscaling
- KEDA Event-Driven Scaling
- Revision Management
Practical lab
- Deploy AI Application
- Configure Auto Scaling
Module 4: Azure Kubernetes Service (AKS)
Topics
- AKS Architecture
- Deploying AI Workloads
- Kubernetes Manifests
- Rolling Updates
- Monitoring Containers
- Troubleshooting
Practical lab
- Deploy AI Service on AKS
- Configure Ingress
- Troubleshoot Deployment
AI Data Layer & Vector Databases
Module 5: Azure Cosmos DB for AI
Topics
- Cosmos DB Fundamentals
- NoSQL Design
- SDK Integration
- Query Optimization
- Change Feed
- AI Data Patterns
Practical lab
- Store Embeddings
- Query Knowledge Base
Module 6: Vector Search & RAG Storage
Topics
- Embeddings
- Vector Databases
- Similarity Search
- Retrieval Augmented Generation (RAG)
- Metadata Filtering
Practical lab
- Build Vector Search
- Create Enterprise Knowledge Base
Module 7: PostgreSQL for AI Applications
Topics
- Azure PostgreSQL
- pgvector Extension
- AI Workload Design
- Schema Design
- Indexing Strategies
- Performance Optimization
Practical lab
- Create pgvector Database
- Implement Semantic Search
AI Integration & Event Architecture
Module 8: Azure Functions
Topics
- Serverless Computing
- Event-Driven AI Processing
- Function Triggers
- Durable Functions
Practical lab
- Process Documents Using Functions
Module 9: Service Bus & Event Grid
Topics
- Event-Driven Architecture
- Message Queues
- Topics & Subscriptions
- Event Grid
- Integration Patterns
Practical lab
- Connect AI Services
- Build Event Processing Pipeline
Module 10: Backend Integration
Topics
- Azure SDKs
- REST APIs
- Third-Party Integrations
- OpenAI API Connectivity
- Enterprise AI Integration
Practical lab
- Connect Azure OpenAI
- Create Intelligent API Gateway
Security, Monitoring & Operations
Module 11: Security for AI Applications
Topics
- Azure Key Vault
- Managed Identities
- Entra ID Integration
- Secret Management
- RBAC
- Secure AI Services
Practical lab
- Secure Azure OpenAI Access
- Implement Managed Identity
Module 12: Monitoring & Observability
Topics
- Azure Monitor
- Application Insights
- OpenTelemetry
- Distributed Tracing
- Performance Monitoring
Practical lab
- Configure Monitoring Dashboard
- Trace AI Requests
Module 13: Troubleshooting & Optimization
Topics
- Log Analytics
- KQL Queries
- Alerting
- Performance Tuning
- Cost Optimization
- Capacity Planning
Practical lab
- Diagnose AI Application Issues
AI200 includes monitoring, troubleshooting, security, observability, and application operations.
Features
- Personalised Learning Plan
- Flexible Scheduling
- Expert Instructor
- Hands-on Project-Based Training
- Support After Training
- Interview Preparation
Course Fees
Virtual Instructor-Led Training
| One-to-One Private Batch | Public Batch |
|---|---|
| Fees : ₹90,000 + 18% GST | Fees : ₹15,000 + 18% GST |
| 2hrs : Mon - Fri | 2hrs : Mon - Fri |
| 4hrs : Sat - Sun | 4hrs : Sat - Sun |
FAQs
1Do you accept card or online payments?
Yes, we do.
2Are course fees refundable if I cancel my enrolment?
No.
3Do you provide placement support after training?
We provide placement support, but do not guarantee employment or placement.
4Do you offer corporate training?
Yes, we offer corporate training.
5How will I receive my certificate after completing the course?
Our team will provide a digital certificate after you complete the training.
6Can I see the trainer’s profile before enrolling?
Yes, you can.
7Can I request a demo session before enrolling?
Yes, you can.
