AI-200: Azure AI Developer Associate
Build production-ready AI applications on Azure
Develop enterprise-grade AI applications using Azure OpenAI Service, Computer Vision, and Language Services to deliver generative AI solutions, agentic systems, and intelligent automation for Australian organisations.
At a Glance
Who it's for
- Software developers building AI-powered applications
- Cloud engineers implementing Azure AI services
- Solution architects designing intelligent systems
- Data engineers integrating AI into data pipelines
- DevOps professionals deploying AI solutions
- IT professionals preparing for AI-102 certification
Course Details
Course Overview
Build production-ready AI applications on Microsoft Azure in this comprehensive 24-hour developer-focused course. You'll gain hands-on experience implementing generative AI solutions with Azure OpenAI Service, creating intelligent agents with tool-calling capabilities, and deploying computer vision and natural language processing systems. Through practical labs and real-world scenarios, you'll learn to architect secure, scalable AI solutions while implementing responsible AI practices and content safety controls aligned with Australian Privacy Principles. Perfect for developers and engineers preparing for the Microsoft AI-102 certification or building enterprise AI capabilities for Australian organisations.
What You'll Learn
Course Curriculum
Module 1: Plan and Manage an Azure AI Solution
5 hours- Provisioning Azure AI services and Microsoft AI Foundry portal
- Managing authentication, keys, and managed identities
- Implementing network security and private endpoints
- Monitoring AI service usage, costs, and performance metrics
- Configuring diagnostic logging and Application Insights
- Resource planning and capacity management
- Multi-region deployment strategies
Module 2: Implement Generative AI Solutions
5 hours- Building applications with Azure OpenAI Service
- Deploying and managing GPT models
- Advanced prompt engineering and system message design
- Token management, optimisation, and cost control
- Implementing streaming responses and chat completions
- Function calling and structured outputs
- Integrating embeddings for semantic search
- Fine-tuning custom models for domain-specific use cases
Module 3: Implement an Agentic AI Solution
3 hours- Understanding AI agents and autonomous systems
- Creating custom agents with tool-calling capabilities
- Implementing function definitions and execution workflows
- Building multi-agent orchestration systems
- Managing agent memory and conversation state
- Integrating agents with external APIs and data sources
- Testing and debugging agentic workflows
Module 4: Computer Vision and NLP Solutions
6 hours- Image analysis with Azure Computer Vision API
- Object detection and classification with Custom Vision
- Face detection and facial recognition services
- Video analysis using Azure Video Indexer
- Text analytics and sentiment analysis
- Language translation with Azure Translator
- Named entity recognition and key phrase extraction
- Conversational language understanding (CLU)
Module 5: Knowledge Mining and Document Intelligence
3 hours- Implementing Azure AI Search for knowledge mining
- Creating search indexes with enrichment pipelines
- Configuring vector search and semantic ranking
- Building custom skills and cognitive enrichments
- Document Intelligence for form and document processing
- Custom model training for invoice and receipt extraction
- Integrating search with Power BI and applications
Module 6: Responsible AI and Content Safety
2 hours- Implementing Azure AI Content Safety service
- Configuring content filters for harmful content detection
- Managing blocklists and custom filtering rules
- Implementing prompt shields for jailbreak protection
- Monitoring and auditing AI system outputs
- Applying responsible AI principles to Australian Privacy Principles
- Compliance considerations for ISO 27001 and Essential Eight
- Incident response for AI safety events
Who Should Attend
- Software developers and application engineers
- Cloud solution architects and engineers
- Data engineers and AI specialists
- DevOps and platform engineers
- IT professionals transitioning to AI development
- Developers preparing for AI-102 certification
- Technical leads implementing enterprise AI solutions
Prerequisites
Before enrolling, please ensure you meet these requirements:
- • Programming experience in Python or C# (intermediate level)
- • Understanding of REST APIs and JSON data formats
- • Basic knowledge of cloud computing concepts
- • Familiarity with Azure fundamentals (or AI-901 equivalent)
- • Experience with version control (Git) helpful
- • Basic understanding of machine learning concepts beneficial
Delivery, Format and Logistics
Delivery Mode
Live online with extensive hands-on labs
Maximum 16 participants for intensive hands-on labs
What You'll Need
- Computer with modern web browser and development environment
- Active Microsoft Azure subscription (free tier acceptable)
- Visual Studio Code or preferred IDE installed
- Reliable internet connection (minimum 15 Mbps)
- Basic programming experience in Python or C# required
- Familiarity with REST APIs and JSON helpful
What You'll Receive
- 24 hours of instructor-led training over 3 days
- Comprehensive hands-on labs with real Azure AI services
- Azure AI developer toolkit and code samples
- AI-102 exam preparation materials and practice tests
- Architecture templates for common AI patterns
- Responsible AI implementation checklist
- Certificate of completion
- 6 months access to course materials
Frequently Asked Questions
Not Ready to Enrol?
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Next Intake
September 2026 — register your interest at educ4te.com
Format
Live online with extensive hands-on labs
Group & Enterprise Options
Discounted rates available for teams of 3+ delegates. Contact us for in-house delivery options.
What's Included
- 24 hours of instructor-led training over 3 days
- Comprehensive hands-on labs with real Azure AI services
- Azure AI developer toolkit and code samples
- AI-102 exam preparation materials and practice tests
- Architecture templates for common AI patterns
- Responsible AI implementation checklist
- Certificate of completion
- 6 months access to course materials
Have questions about this course?