Mastering AI-Driven Automation with Microsoft Graph API
You're not behind. But you're not ahead either. While AI reshapes enterprise workflows at lightning speed, the pressure mounts to deliver automation that actually moves the needle - not just code that compiles. Manual processes, disjointed systems, and repetitive data tasks are draining your team’s capacity. Meanwhile, decision-makers demand real-time insights, proactive responses, and intelligent automation - not scripts that break when the schema changes. Mastering AI-Driven Automation with Microsoft Graph API is the structured breakthrough you need. This is not theory. It’s the exact roadmap to take your AI automation concepts from experimental to board-approved in under 30 days - complete with a documented, secure, and scalable integration strategy ready for enterprise deployment. One senior solutions architect used this framework to replace a 12-hour monthly reporting cycle with a 9-minute AI-triggered automation pipeline. The result? A documented 78% reduction in operational lag and formal recognition by their CIO - all built using the techniques taught in this course. This isn’t about chasing trends. It’s about owning the architecture that connects AI models to live business data in Microsoft 365 and Azure environments. No guesswork. No outdated tutorials. Just precise, audit-ready automation workflows that scale. From concept to production, this system bridges the gap between knowing API basics and delivering intelligent, self-adjusting automations that integrate seamlessly across Outlook, Teams, SharePoint, and beyond. Here’s how this course is structured to help you get there.Course Format & Delivery Details Self-Paced, Immediate Online Access - Learn on Your Terms
This is a fully self-paced course with immediate online access upon enrollment. There are no fixed start dates, no weekly schedules, and no time zone conflicts. You advance through the material at your own speed, on your own timeline, from any location. Most learners complete the core automation framework in 12–17 hours and implement their first production-ready workflow within 10 days. Advanced integration patterns and certification prep add an additional 8–10 hours for full mastery. Lifetime Access, Zero Ongoing Cost
You receive lifetime access to all course materials, including every update released in the future. As Microsoft Graph evolves and new AI connectors emerge, your access is automatically refreshed at no extra charge. This is a permanent asset in your technical library. - 24/7 global access across all devices
- Mobile-optimized for learning during commutes, flights, or downtime
- Progress tracking to resume exactly where you left off
Direct Support from Certified Architects
Enrollment includes dedicated instructor support via structured guidance channels. You’ll have access to architect-level feedback on implementation challenges, authentication design, and workflow validation. This is not generic help - it’s targeted engineering assistance to unblock your real-world use cases. Certificate of Completion by The Art of Service
Upon finishing the course, you earn a Certificate of Completion issued by The Art of Service - a globally recognised credential trusted by enterprises, government agencies, and IT leaders worldwide. This certificate validates your ability to design, secure, and deploy production-grade AI automations using Microsoft Graph API. The Art of Service has trained over 150,000 professionals in enterprise architecture and automation frameworks. Our certifications are cited in promotion packages, job applications, and compliance documentation - because they reflect real engineering discipline, not just conceptual knowledge. Transparent, Upfront Pricing - No Hidden Fees
The total investment is straightforward with no hidden costs, subscriptions, or renewal fees. You pay once and own full access forever. There are no tiered upgrades, premium add-ons, or paywalls for advanced content. We accept all major payment methods, including Visa, Mastercard, and PayPal - processed through secure, PCI-compliant gateways for your protection. 100% Satisfied or Refunded - Zero Risk Enrollment
We offer a complete money-back guarantee. If you follow the course structure, complete the hands-on implementation guides, and don’t feel confident deploying AI-driven workflows using Microsoft Graph API - you’re entitled to a full refund, no questions asked. This removes all risk and places the outcome squarely on the quality of the content. Enrollment Confirmation & Access Delivery
After enrollment, you’ll receive a confirmation email immediately. A separate access email with login details and course entry instructions will be sent once the materials are fully configured in your account. This ensures full system readiness before you begin. This Works Even If…
- You’ve struggled with Graph API documentation before
- You’re not a full-time developer but need to integrate AI logic
- Your organisation restricts admin consent for app registrations
- You work in a highly regulated environment (finance, healthcare, government)
- You’re transitioning from legacy automation tools like Power Automate without clear migration paths
Real practitioners from enterprise IT, compliance, DevOps, and solution architecture roles have used this framework under strict governance - and succeeded. Testimonial: *“I used to waste weeks negotiating API permissions. After applying the delegated vs application permissions blueprint from this course, I got approval in two days and deployed an auto-classification bot for sensitive emails. The CISO referenced my work in the quarterly risk review.”* – L. Tran, IT Solutions Lead, Financial Services Your success doesn’t depend on prior expertise - it depends on having the right implementation patterns. We provide them.
Module 1: Foundations of AI-Driven Automation - Understanding the shift from rule-based to AI-powered automation
- Defining intelligent workflows in enterprise contexts
- Overview of Microsoft 365 data ecosystem and real-time signals
- How AI models consume live data via APIs
- The role of Microsoft Graph API in next-gen automation
- Differentiating between cloud-only and hybrid deployment models
- Use cases for AI triggers: email sentiment, calendar patterns, file activity
- Key challenges in automating with dynamic user data
- Security, compliance, and audit implications of AI access
- Establishing success criteria for AI automation projects
Module 2: Microsoft Graph API Core Architecture - REST principles and endpoint structure in Microsoft Graph
- Navigating the Graph Explorer tool for rapid prototyping
- Understanding resource types: users, groups, messages, sites, drives
- Working with OData queries in filtering and sorting
- Batching requests to optimise performance and reduce throttling
- Managing $select, $expand, $filter, $top parameters efficiently
- Handling delta queries for incremental data sync
- Using changelogs for Teams channels, SharePoint files, OneNote pages
- Implementing pagination for large result sets
- Error handling patterns: HTTP 429, 503, and retry logic
- Rate limiting strategies and burst detection
- Best practices for request optimisation and payload minimisation
Module 3: Authentication and Authorization Deep Dive - Microsoft Identity Platform (Azure AD) integration
- Understanding OAuth 2.0 and OpenID Connect flows
- App registrations vs service principals: what’s the difference?
- Configuring applications in the Azure portal
- Delegated permissions vs application permissions
- Choosing between interactive and daemon workflows
- Implementing client credentials flow for background services
- Using certificate-based authentication for higher security
- Securing client secrets with Azure Key Vault
- Dynamic consent acquisition and user grant workflows
- Handling multi-tenant versus single-tenant application scope
- Permission scopes for Mail.Read, Files.ReadWrite, Sites.ReadWrite.All
- Admin consent workflows and approval delegation
- Managing token lifetimes and refresh tokens
- Implementing conditional access policies for app access
- Audit logging app permissions via Microsoft Defender for Cloud Apps
Module 4: Connecting AI Models to Graph Data - Designing data pipelines for AI inference engines
- Extracting text content from emails, chats, and documents
- Preserving metadata context during AI processing
- Preprocessing user-generated content for NLP models
- Calling Azure Cognitive Services from Graph-triggered workflows
- Using Language Understanding (LUIS) for intent detection in chat
- Integrating Azure Form Recognizer with SharePoint document libraries
- Parsing meeting transcripts from Teams recordings
- Automatically tagging files based on content and context
- Handling multilingual content in global enterprises
- Setting up confidence thresholds for automated decisions
- Implementing human-in-the-loop review for low-confidence predictions
- Versioning AI models and managing fallback logic
- Latency considerations in real-time versus batch processing
- Securing API keys and endpoints used by AI models
Module 5: Designing Event-Driven Automation Workflows - Concept of push versus poll-based event handling
- Overview of Microsoft Graph webhooks (subscriptions)
- Creating and managing webhook subscriptions via API
- Validating incoming notifications from Graph
- Receiving change notifications for mail, events, files, and chats
- Extending subscriptions beyond 4230-minute limit
- Reissuing subscription renewals automatically
- Designing idempotent event processors to prevent duplicates
- Routing events to message queues like Azure Service Bus
- Scaling event processing with Azure Functions
- Implementing dead-letter queues for failed events
- Monitoring event delivery latency and failure rates
- Correlating events across multiple users and resources
- Using change notification encryption for sensitive data
- Building custom validation servers for webhook setup
Module 6: Building Intelligent Document Automation - Automating document classification in SharePoint and OneDrive
- Extracting structured data from invoices, contracts, and forms
- Applying AI metadata tags based on document content
- Version control and audit trail preservation
- Auto-routing documents to correct libraries or teams
- Generating executive summaries from long reports
- Detecting sensitive information using Microsoft Purview
- Applying retention labels triggered by AI insights
- Automating NDA redaction workflows with AI and Graph
- Tracking document access patterns over time
- Proactively archiving stale files based on usage
- Binding documents to CRM or ERP records via Power Platform
- Creating searchable knowledge bases from unstructured content
- Summarising meeting notes and action items automatically
- Integrating with Microsoft Syntex for content understanding
Module 7: AI-Enhanced Communication Automation - Monitoring inbox patterns for priority escalations
- Automatic email triage using sentiment and intent analysis
- Flagging urgent messages based on language and sender history
- Generating draft replies using language models
- Automatically scheduling follow-up tasks from emails
- Tagging messages for compliance review
- Analysing Teams chat sentiment during project phases
- Identifying collaboration bottlenecks via message volume trends
- Auto-inviting stakeholders based on email thread context
- Creating recurring meeting summaries with highlights
- Automating calendar availability checks across time zones
- Blocking focus time based on workload predictions
- Alerting managers to response time delays
- Integrating communication insights into performance dashboards
- Enforcing data handling policies in external email exchanges
Module 8: Secure AI Automation in Regulated Environments - Designing for compliance with GDPR, HIPAA, SOX, CCPA
- Implementing data minimisation in AI workflows
- Audit logging all Graph API calls and AI decisions
- Storing logs securely in Azure Monitor and Log Analytics
- Masking PII before sending to AI models
- Using sensitivity labels to govern automation rules
- Enforcing justification requirements for automated actions
- Implementing dual approval for high-risk automations
- Testing access controls in non-production environments
- Using Microsoft Purview for data classification and leakage prevention
- Securing service accounts with Privileged Identity Management
- Monitoring for anomalous automation behaviour
- Creating incident response playbooks for API misuse
- Documenting data flows for regulatory audits
- Obtaining legal sign-off on AI automation policies
Module 9: Advanced Integration with Power Platform & Azure - Integrating Graph API with Power Automate custom connectors
- Using Azure Logic Apps for enterprise-grade orchestration
- Calling Graph from Durable Functions with state management
- Building custom APIs with Azure API Management
- Exposing Graph data safely to low-code platforms
- Creating reusable automation templates
- Implementing API versioning and deprecation strategies
- Rate limiting external access to internal automation APIs
- Using Azure Event Grid to fan out Graph events
- Visualising workflow execution in Application Insights
- Monitoring performance with custom metrics and alerts
- Deploying automation workflows via CI/CD pipelines
- Managing configuration across dev, test, and prod environments
- Using ARM templates or Bicep for infrastructure as code
- Automating compliance checks with Azure Policy
Module 10: Performance, Scalability & Optimisation - Analysing API usage patterns and bottleneck identification
- Designing for high availability and fault tolerance
- Caching strategies for frequently accessed data
- Implementing retries with exponential backoff
- Using distributed locks to prevent race conditions
- Profiling execution time of AI and Graph interactions
- Reducing network roundtrips with batched operations
- Optimising payload size with selective field returns
- Sharding workloads across multiple tenants or regions
- Estimating monthly call volume and budgeting quotas
- Monitoring usage against Microsoft’s service limits
- Requesting service plan increases when necessary
- Designing fallback mechanisms during Graph outages
- Implementing graceful degradation for non-critical features
- Load testing automation workflows before production
Module 11: Real-World Implementation Projects - Project 1: Automated meeting summary generator with action items
- Connecting to Teams meeting transcripts via Graph
- Calling Azure Cognitive Services for key phrase extraction
- Generating bullet-point summaries with custom logic
- Publishing summaries to SharePoint and notifying attendees
- Project 2: Intelligent email routing system
- Detecting support request patterns in inbound messages
- Classifying urgency using sentiment and keywords
- Routing to correct teams with metadata tagging
- Creating tickets in ServiceNow or Jira via API
- Project 3: Proactive document compliance monitor
- Scanning newly uploaded files in SharePoint
- Detecting personal data with Microsoft Purview
- Applying mandatory retention labels
- Sending notifications to data stewards for review
Module 12: Certification Preparation & Next Steps - Review of core competencies for AI-Driven Graph Automation
- Practice assessment with scenario-based questions
- How to document your automation design for evaluation
- Preparing evidence of implementation proficiency
- Submission process for the Certificate of Completion
- How to reference your certification on LinkedIn and resumes
- Connecting with the global Art of Service alumni network
- Accessing advanced automation design patterns (exclusive)
- Staying updated via official Graph changelogs
- Joining Microsoft’s developer early access programs
- Building a public portfolio of automation solutions
- Transitioning from automation engineer to automation architect
- Leading AI integration initiatives in your organisation
- Presenting your automation ROI to executive stakeholders
- Continuing education paths in AI, security, and cloud architecture
- Understanding the shift from rule-based to AI-powered automation
- Defining intelligent workflows in enterprise contexts
- Overview of Microsoft 365 data ecosystem and real-time signals
- How AI models consume live data via APIs
- The role of Microsoft Graph API in next-gen automation
- Differentiating between cloud-only and hybrid deployment models
- Use cases for AI triggers: email sentiment, calendar patterns, file activity
- Key challenges in automating with dynamic user data
- Security, compliance, and audit implications of AI access
- Establishing success criteria for AI automation projects
Module 2: Microsoft Graph API Core Architecture - REST principles and endpoint structure in Microsoft Graph
- Navigating the Graph Explorer tool for rapid prototyping
- Understanding resource types: users, groups, messages, sites, drives
- Working with OData queries in filtering and sorting
- Batching requests to optimise performance and reduce throttling
- Managing $select, $expand, $filter, $top parameters efficiently
- Handling delta queries for incremental data sync
- Using changelogs for Teams channels, SharePoint files, OneNote pages
- Implementing pagination for large result sets
- Error handling patterns: HTTP 429, 503, and retry logic
- Rate limiting strategies and burst detection
- Best practices for request optimisation and payload minimisation
Module 3: Authentication and Authorization Deep Dive - Microsoft Identity Platform (Azure AD) integration
- Understanding OAuth 2.0 and OpenID Connect flows
- App registrations vs service principals: what’s the difference?
- Configuring applications in the Azure portal
- Delegated permissions vs application permissions
- Choosing between interactive and daemon workflows
- Implementing client credentials flow for background services
- Using certificate-based authentication for higher security
- Securing client secrets with Azure Key Vault
- Dynamic consent acquisition and user grant workflows
- Handling multi-tenant versus single-tenant application scope
- Permission scopes for Mail.Read, Files.ReadWrite, Sites.ReadWrite.All
- Admin consent workflows and approval delegation
- Managing token lifetimes and refresh tokens
- Implementing conditional access policies for app access
- Audit logging app permissions via Microsoft Defender for Cloud Apps
Module 4: Connecting AI Models to Graph Data - Designing data pipelines for AI inference engines
- Extracting text content from emails, chats, and documents
- Preserving metadata context during AI processing
- Preprocessing user-generated content for NLP models
- Calling Azure Cognitive Services from Graph-triggered workflows
- Using Language Understanding (LUIS) for intent detection in chat
- Integrating Azure Form Recognizer with SharePoint document libraries
- Parsing meeting transcripts from Teams recordings
- Automatically tagging files based on content and context
- Handling multilingual content in global enterprises
- Setting up confidence thresholds for automated decisions
- Implementing human-in-the-loop review for low-confidence predictions
- Versioning AI models and managing fallback logic
- Latency considerations in real-time versus batch processing
- Securing API keys and endpoints used by AI models
Module 5: Designing Event-Driven Automation Workflows - Concept of push versus poll-based event handling
- Overview of Microsoft Graph webhooks (subscriptions)
- Creating and managing webhook subscriptions via API
- Validating incoming notifications from Graph
- Receiving change notifications for mail, events, files, and chats
- Extending subscriptions beyond 4230-minute limit
- Reissuing subscription renewals automatically
- Designing idempotent event processors to prevent duplicates
- Routing events to message queues like Azure Service Bus
- Scaling event processing with Azure Functions
- Implementing dead-letter queues for failed events
- Monitoring event delivery latency and failure rates
- Correlating events across multiple users and resources
- Using change notification encryption for sensitive data
- Building custom validation servers for webhook setup
Module 6: Building Intelligent Document Automation - Automating document classification in SharePoint and OneDrive
- Extracting structured data from invoices, contracts, and forms
- Applying AI metadata tags based on document content
- Version control and audit trail preservation
- Auto-routing documents to correct libraries or teams
- Generating executive summaries from long reports
- Detecting sensitive information using Microsoft Purview
- Applying retention labels triggered by AI insights
- Automating NDA redaction workflows with AI and Graph
- Tracking document access patterns over time
- Proactively archiving stale files based on usage
- Binding documents to CRM or ERP records via Power Platform
- Creating searchable knowledge bases from unstructured content
- Summarising meeting notes and action items automatically
- Integrating with Microsoft Syntex for content understanding
Module 7: AI-Enhanced Communication Automation - Monitoring inbox patterns for priority escalations
- Automatic email triage using sentiment and intent analysis
- Flagging urgent messages based on language and sender history
- Generating draft replies using language models
- Automatically scheduling follow-up tasks from emails
- Tagging messages for compliance review
- Analysing Teams chat sentiment during project phases
- Identifying collaboration bottlenecks via message volume trends
- Auto-inviting stakeholders based on email thread context
- Creating recurring meeting summaries with highlights
- Automating calendar availability checks across time zones
- Blocking focus time based on workload predictions
- Alerting managers to response time delays
- Integrating communication insights into performance dashboards
- Enforcing data handling policies in external email exchanges
Module 8: Secure AI Automation in Regulated Environments - Designing for compliance with GDPR, HIPAA, SOX, CCPA
- Implementing data minimisation in AI workflows
- Audit logging all Graph API calls and AI decisions
- Storing logs securely in Azure Monitor and Log Analytics
- Masking PII before sending to AI models
- Using sensitivity labels to govern automation rules
- Enforcing justification requirements for automated actions
- Implementing dual approval for high-risk automations
- Testing access controls in non-production environments
- Using Microsoft Purview for data classification and leakage prevention
- Securing service accounts with Privileged Identity Management
- Monitoring for anomalous automation behaviour
- Creating incident response playbooks for API misuse
- Documenting data flows for regulatory audits
- Obtaining legal sign-off on AI automation policies
Module 9: Advanced Integration with Power Platform & Azure - Integrating Graph API with Power Automate custom connectors
- Using Azure Logic Apps for enterprise-grade orchestration
- Calling Graph from Durable Functions with state management
- Building custom APIs with Azure API Management
- Exposing Graph data safely to low-code platforms
- Creating reusable automation templates
- Implementing API versioning and deprecation strategies
- Rate limiting external access to internal automation APIs
- Using Azure Event Grid to fan out Graph events
- Visualising workflow execution in Application Insights
- Monitoring performance with custom metrics and alerts
- Deploying automation workflows via CI/CD pipelines
- Managing configuration across dev, test, and prod environments
- Using ARM templates or Bicep for infrastructure as code
- Automating compliance checks with Azure Policy
Module 10: Performance, Scalability & Optimisation - Analysing API usage patterns and bottleneck identification
- Designing for high availability and fault tolerance
- Caching strategies for frequently accessed data
- Implementing retries with exponential backoff
- Using distributed locks to prevent race conditions
- Profiling execution time of AI and Graph interactions
- Reducing network roundtrips with batched operations
- Optimising payload size with selective field returns
- Sharding workloads across multiple tenants or regions
- Estimating monthly call volume and budgeting quotas
- Monitoring usage against Microsoft’s service limits
- Requesting service plan increases when necessary
- Designing fallback mechanisms during Graph outages
- Implementing graceful degradation for non-critical features
- Load testing automation workflows before production
Module 11: Real-World Implementation Projects - Project 1: Automated meeting summary generator with action items
- Connecting to Teams meeting transcripts via Graph
- Calling Azure Cognitive Services for key phrase extraction
- Generating bullet-point summaries with custom logic
- Publishing summaries to SharePoint and notifying attendees
- Project 2: Intelligent email routing system
- Detecting support request patterns in inbound messages
- Classifying urgency using sentiment and keywords
- Routing to correct teams with metadata tagging
- Creating tickets in ServiceNow or Jira via API
- Project 3: Proactive document compliance monitor
- Scanning newly uploaded files in SharePoint
- Detecting personal data with Microsoft Purview
- Applying mandatory retention labels
- Sending notifications to data stewards for review
Module 12: Certification Preparation & Next Steps - Review of core competencies for AI-Driven Graph Automation
- Practice assessment with scenario-based questions
- How to document your automation design for evaluation
- Preparing evidence of implementation proficiency
- Submission process for the Certificate of Completion
- How to reference your certification on LinkedIn and resumes
- Connecting with the global Art of Service alumni network
- Accessing advanced automation design patterns (exclusive)
- Staying updated via official Graph changelogs
- Joining Microsoft’s developer early access programs
- Building a public portfolio of automation solutions
- Transitioning from automation engineer to automation architect
- Leading AI integration initiatives in your organisation
- Presenting your automation ROI to executive stakeholders
- Continuing education paths in AI, security, and cloud architecture
- Microsoft Identity Platform (Azure AD) integration
- Understanding OAuth 2.0 and OpenID Connect flows
- App registrations vs service principals: what’s the difference?
- Configuring applications in the Azure portal
- Delegated permissions vs application permissions
- Choosing between interactive and daemon workflows
- Implementing client credentials flow for background services
- Using certificate-based authentication for higher security
- Securing client secrets with Azure Key Vault
- Dynamic consent acquisition and user grant workflows
- Handling multi-tenant versus single-tenant application scope
- Permission scopes for Mail.Read, Files.ReadWrite, Sites.ReadWrite.All
- Admin consent workflows and approval delegation
- Managing token lifetimes and refresh tokens
- Implementing conditional access policies for app access
- Audit logging app permissions via Microsoft Defender for Cloud Apps
Module 4: Connecting AI Models to Graph Data - Designing data pipelines for AI inference engines
- Extracting text content from emails, chats, and documents
- Preserving metadata context during AI processing
- Preprocessing user-generated content for NLP models
- Calling Azure Cognitive Services from Graph-triggered workflows
- Using Language Understanding (LUIS) for intent detection in chat
- Integrating Azure Form Recognizer with SharePoint document libraries
- Parsing meeting transcripts from Teams recordings
- Automatically tagging files based on content and context
- Handling multilingual content in global enterprises
- Setting up confidence thresholds for automated decisions
- Implementing human-in-the-loop review for low-confidence predictions
- Versioning AI models and managing fallback logic
- Latency considerations in real-time versus batch processing
- Securing API keys and endpoints used by AI models
Module 5: Designing Event-Driven Automation Workflows - Concept of push versus poll-based event handling
- Overview of Microsoft Graph webhooks (subscriptions)
- Creating and managing webhook subscriptions via API
- Validating incoming notifications from Graph
- Receiving change notifications for mail, events, files, and chats
- Extending subscriptions beyond 4230-minute limit
- Reissuing subscription renewals automatically
- Designing idempotent event processors to prevent duplicates
- Routing events to message queues like Azure Service Bus
- Scaling event processing with Azure Functions
- Implementing dead-letter queues for failed events
- Monitoring event delivery latency and failure rates
- Correlating events across multiple users and resources
- Using change notification encryption for sensitive data
- Building custom validation servers for webhook setup
Module 6: Building Intelligent Document Automation - Automating document classification in SharePoint and OneDrive
- Extracting structured data from invoices, contracts, and forms
- Applying AI metadata tags based on document content
- Version control and audit trail preservation
- Auto-routing documents to correct libraries or teams
- Generating executive summaries from long reports
- Detecting sensitive information using Microsoft Purview
- Applying retention labels triggered by AI insights
- Automating NDA redaction workflows with AI and Graph
- Tracking document access patterns over time
- Proactively archiving stale files based on usage
- Binding documents to CRM or ERP records via Power Platform
- Creating searchable knowledge bases from unstructured content
- Summarising meeting notes and action items automatically
- Integrating with Microsoft Syntex for content understanding
Module 7: AI-Enhanced Communication Automation - Monitoring inbox patterns for priority escalations
- Automatic email triage using sentiment and intent analysis
- Flagging urgent messages based on language and sender history
- Generating draft replies using language models
- Automatically scheduling follow-up tasks from emails
- Tagging messages for compliance review
- Analysing Teams chat sentiment during project phases
- Identifying collaboration bottlenecks via message volume trends
- Auto-inviting stakeholders based on email thread context
- Creating recurring meeting summaries with highlights
- Automating calendar availability checks across time zones
- Blocking focus time based on workload predictions
- Alerting managers to response time delays
- Integrating communication insights into performance dashboards
- Enforcing data handling policies in external email exchanges
Module 8: Secure AI Automation in Regulated Environments - Designing for compliance with GDPR, HIPAA, SOX, CCPA
- Implementing data minimisation in AI workflows
- Audit logging all Graph API calls and AI decisions
- Storing logs securely in Azure Monitor and Log Analytics
- Masking PII before sending to AI models
- Using sensitivity labels to govern automation rules
- Enforcing justification requirements for automated actions
- Implementing dual approval for high-risk automations
- Testing access controls in non-production environments
- Using Microsoft Purview for data classification and leakage prevention
- Securing service accounts with Privileged Identity Management
- Monitoring for anomalous automation behaviour
- Creating incident response playbooks for API misuse
- Documenting data flows for regulatory audits
- Obtaining legal sign-off on AI automation policies
Module 9: Advanced Integration with Power Platform & Azure - Integrating Graph API with Power Automate custom connectors
- Using Azure Logic Apps for enterprise-grade orchestration
- Calling Graph from Durable Functions with state management
- Building custom APIs with Azure API Management
- Exposing Graph data safely to low-code platforms
- Creating reusable automation templates
- Implementing API versioning and deprecation strategies
- Rate limiting external access to internal automation APIs
- Using Azure Event Grid to fan out Graph events
- Visualising workflow execution in Application Insights
- Monitoring performance with custom metrics and alerts
- Deploying automation workflows via CI/CD pipelines
- Managing configuration across dev, test, and prod environments
- Using ARM templates or Bicep for infrastructure as code
- Automating compliance checks with Azure Policy
Module 10: Performance, Scalability & Optimisation - Analysing API usage patterns and bottleneck identification
- Designing for high availability and fault tolerance
- Caching strategies for frequently accessed data
- Implementing retries with exponential backoff
- Using distributed locks to prevent race conditions
- Profiling execution time of AI and Graph interactions
- Reducing network roundtrips with batched operations
- Optimising payload size with selective field returns
- Sharding workloads across multiple tenants or regions
- Estimating monthly call volume and budgeting quotas
- Monitoring usage against Microsoft’s service limits
- Requesting service plan increases when necessary
- Designing fallback mechanisms during Graph outages
- Implementing graceful degradation for non-critical features
- Load testing automation workflows before production
Module 11: Real-World Implementation Projects - Project 1: Automated meeting summary generator with action items
- Connecting to Teams meeting transcripts via Graph
- Calling Azure Cognitive Services for key phrase extraction
- Generating bullet-point summaries with custom logic
- Publishing summaries to SharePoint and notifying attendees
- Project 2: Intelligent email routing system
- Detecting support request patterns in inbound messages
- Classifying urgency using sentiment and keywords
- Routing to correct teams with metadata tagging
- Creating tickets in ServiceNow or Jira via API
- Project 3: Proactive document compliance monitor
- Scanning newly uploaded files in SharePoint
- Detecting personal data with Microsoft Purview
- Applying mandatory retention labels
- Sending notifications to data stewards for review
Module 12: Certification Preparation & Next Steps - Review of core competencies for AI-Driven Graph Automation
- Practice assessment with scenario-based questions
- How to document your automation design for evaluation
- Preparing evidence of implementation proficiency
- Submission process for the Certificate of Completion
- How to reference your certification on LinkedIn and resumes
- Connecting with the global Art of Service alumni network
- Accessing advanced automation design patterns (exclusive)
- Staying updated via official Graph changelogs
- Joining Microsoft’s developer early access programs
- Building a public portfolio of automation solutions
- Transitioning from automation engineer to automation architect
- Leading AI integration initiatives in your organisation
- Presenting your automation ROI to executive stakeholders
- Continuing education paths in AI, security, and cloud architecture
- Concept of push versus poll-based event handling
- Overview of Microsoft Graph webhooks (subscriptions)
- Creating and managing webhook subscriptions via API
- Validating incoming notifications from Graph
- Receiving change notifications for mail, events, files, and chats
- Extending subscriptions beyond 4230-minute limit
- Reissuing subscription renewals automatically
- Designing idempotent event processors to prevent duplicates
- Routing events to message queues like Azure Service Bus
- Scaling event processing with Azure Functions
- Implementing dead-letter queues for failed events
- Monitoring event delivery latency and failure rates
- Correlating events across multiple users and resources
- Using change notification encryption for sensitive data
- Building custom validation servers for webhook setup
Module 6: Building Intelligent Document Automation - Automating document classification in SharePoint and OneDrive
- Extracting structured data from invoices, contracts, and forms
- Applying AI metadata tags based on document content
- Version control and audit trail preservation
- Auto-routing documents to correct libraries or teams
- Generating executive summaries from long reports
- Detecting sensitive information using Microsoft Purview
- Applying retention labels triggered by AI insights
- Automating NDA redaction workflows with AI and Graph
- Tracking document access patterns over time
- Proactively archiving stale files based on usage
- Binding documents to CRM or ERP records via Power Platform
- Creating searchable knowledge bases from unstructured content
- Summarising meeting notes and action items automatically
- Integrating with Microsoft Syntex for content understanding
Module 7: AI-Enhanced Communication Automation - Monitoring inbox patterns for priority escalations
- Automatic email triage using sentiment and intent analysis
- Flagging urgent messages based on language and sender history
- Generating draft replies using language models
- Automatically scheduling follow-up tasks from emails
- Tagging messages for compliance review
- Analysing Teams chat sentiment during project phases
- Identifying collaboration bottlenecks via message volume trends
- Auto-inviting stakeholders based on email thread context
- Creating recurring meeting summaries with highlights
- Automating calendar availability checks across time zones
- Blocking focus time based on workload predictions
- Alerting managers to response time delays
- Integrating communication insights into performance dashboards
- Enforcing data handling policies in external email exchanges
Module 8: Secure AI Automation in Regulated Environments - Designing for compliance with GDPR, HIPAA, SOX, CCPA
- Implementing data minimisation in AI workflows
- Audit logging all Graph API calls and AI decisions
- Storing logs securely in Azure Monitor and Log Analytics
- Masking PII before sending to AI models
- Using sensitivity labels to govern automation rules
- Enforcing justification requirements for automated actions
- Implementing dual approval for high-risk automations
- Testing access controls in non-production environments
- Using Microsoft Purview for data classification and leakage prevention
- Securing service accounts with Privileged Identity Management
- Monitoring for anomalous automation behaviour
- Creating incident response playbooks for API misuse
- Documenting data flows for regulatory audits
- Obtaining legal sign-off on AI automation policies
Module 9: Advanced Integration with Power Platform & Azure - Integrating Graph API with Power Automate custom connectors
- Using Azure Logic Apps for enterprise-grade orchestration
- Calling Graph from Durable Functions with state management
- Building custom APIs with Azure API Management
- Exposing Graph data safely to low-code platforms
- Creating reusable automation templates
- Implementing API versioning and deprecation strategies
- Rate limiting external access to internal automation APIs
- Using Azure Event Grid to fan out Graph events
- Visualising workflow execution in Application Insights
- Monitoring performance with custom metrics and alerts
- Deploying automation workflows via CI/CD pipelines
- Managing configuration across dev, test, and prod environments
- Using ARM templates or Bicep for infrastructure as code
- Automating compliance checks with Azure Policy
Module 10: Performance, Scalability & Optimisation - Analysing API usage patterns and bottleneck identification
- Designing for high availability and fault tolerance
- Caching strategies for frequently accessed data
- Implementing retries with exponential backoff
- Using distributed locks to prevent race conditions
- Profiling execution time of AI and Graph interactions
- Reducing network roundtrips with batched operations
- Optimising payload size with selective field returns
- Sharding workloads across multiple tenants or regions
- Estimating monthly call volume and budgeting quotas
- Monitoring usage against Microsoft’s service limits
- Requesting service plan increases when necessary
- Designing fallback mechanisms during Graph outages
- Implementing graceful degradation for non-critical features
- Load testing automation workflows before production
Module 11: Real-World Implementation Projects - Project 1: Automated meeting summary generator with action items
- Connecting to Teams meeting transcripts via Graph
- Calling Azure Cognitive Services for key phrase extraction
- Generating bullet-point summaries with custom logic
- Publishing summaries to SharePoint and notifying attendees
- Project 2: Intelligent email routing system
- Detecting support request patterns in inbound messages
- Classifying urgency using sentiment and keywords
- Routing to correct teams with metadata tagging
- Creating tickets in ServiceNow or Jira via API
- Project 3: Proactive document compliance monitor
- Scanning newly uploaded files in SharePoint
- Detecting personal data with Microsoft Purview
- Applying mandatory retention labels
- Sending notifications to data stewards for review
Module 12: Certification Preparation & Next Steps - Review of core competencies for AI-Driven Graph Automation
- Practice assessment with scenario-based questions
- How to document your automation design for evaluation
- Preparing evidence of implementation proficiency
- Submission process for the Certificate of Completion
- How to reference your certification on LinkedIn and resumes
- Connecting with the global Art of Service alumni network
- Accessing advanced automation design patterns (exclusive)
- Staying updated via official Graph changelogs
- Joining Microsoft’s developer early access programs
- Building a public portfolio of automation solutions
- Transitioning from automation engineer to automation architect
- Leading AI integration initiatives in your organisation
- Presenting your automation ROI to executive stakeholders
- Continuing education paths in AI, security, and cloud architecture
- Monitoring inbox patterns for priority escalations
- Automatic email triage using sentiment and intent analysis
- Flagging urgent messages based on language and sender history
- Generating draft replies using language models
- Automatically scheduling follow-up tasks from emails
- Tagging messages for compliance review
- Analysing Teams chat sentiment during project phases
- Identifying collaboration bottlenecks via message volume trends
- Auto-inviting stakeholders based on email thread context
- Creating recurring meeting summaries with highlights
- Automating calendar availability checks across time zones
- Blocking focus time based on workload predictions
- Alerting managers to response time delays
- Integrating communication insights into performance dashboards
- Enforcing data handling policies in external email exchanges
Module 8: Secure AI Automation in Regulated Environments - Designing for compliance with GDPR, HIPAA, SOX, CCPA
- Implementing data minimisation in AI workflows
- Audit logging all Graph API calls and AI decisions
- Storing logs securely in Azure Monitor and Log Analytics
- Masking PII before sending to AI models
- Using sensitivity labels to govern automation rules
- Enforcing justification requirements for automated actions
- Implementing dual approval for high-risk automations
- Testing access controls in non-production environments
- Using Microsoft Purview for data classification and leakage prevention
- Securing service accounts with Privileged Identity Management
- Monitoring for anomalous automation behaviour
- Creating incident response playbooks for API misuse
- Documenting data flows for regulatory audits
- Obtaining legal sign-off on AI automation policies
Module 9: Advanced Integration with Power Platform & Azure - Integrating Graph API with Power Automate custom connectors
- Using Azure Logic Apps for enterprise-grade orchestration
- Calling Graph from Durable Functions with state management
- Building custom APIs with Azure API Management
- Exposing Graph data safely to low-code platforms
- Creating reusable automation templates
- Implementing API versioning and deprecation strategies
- Rate limiting external access to internal automation APIs
- Using Azure Event Grid to fan out Graph events
- Visualising workflow execution in Application Insights
- Monitoring performance with custom metrics and alerts
- Deploying automation workflows via CI/CD pipelines
- Managing configuration across dev, test, and prod environments
- Using ARM templates or Bicep for infrastructure as code
- Automating compliance checks with Azure Policy
Module 10: Performance, Scalability & Optimisation - Analysing API usage patterns and bottleneck identification
- Designing for high availability and fault tolerance
- Caching strategies for frequently accessed data
- Implementing retries with exponential backoff
- Using distributed locks to prevent race conditions
- Profiling execution time of AI and Graph interactions
- Reducing network roundtrips with batched operations
- Optimising payload size with selective field returns
- Sharding workloads across multiple tenants or regions
- Estimating monthly call volume and budgeting quotas
- Monitoring usage against Microsoft’s service limits
- Requesting service plan increases when necessary
- Designing fallback mechanisms during Graph outages
- Implementing graceful degradation for non-critical features
- Load testing automation workflows before production
Module 11: Real-World Implementation Projects - Project 1: Automated meeting summary generator with action items
- Connecting to Teams meeting transcripts via Graph
- Calling Azure Cognitive Services for key phrase extraction
- Generating bullet-point summaries with custom logic
- Publishing summaries to SharePoint and notifying attendees
- Project 2: Intelligent email routing system
- Detecting support request patterns in inbound messages
- Classifying urgency using sentiment and keywords
- Routing to correct teams with metadata tagging
- Creating tickets in ServiceNow or Jira via API
- Project 3: Proactive document compliance monitor
- Scanning newly uploaded files in SharePoint
- Detecting personal data with Microsoft Purview
- Applying mandatory retention labels
- Sending notifications to data stewards for review
Module 12: Certification Preparation & Next Steps - Review of core competencies for AI-Driven Graph Automation
- Practice assessment with scenario-based questions
- How to document your automation design for evaluation
- Preparing evidence of implementation proficiency
- Submission process for the Certificate of Completion
- How to reference your certification on LinkedIn and resumes
- Connecting with the global Art of Service alumni network
- Accessing advanced automation design patterns (exclusive)
- Staying updated via official Graph changelogs
- Joining Microsoft’s developer early access programs
- Building a public portfolio of automation solutions
- Transitioning from automation engineer to automation architect
- Leading AI integration initiatives in your organisation
- Presenting your automation ROI to executive stakeholders
- Continuing education paths in AI, security, and cloud architecture
- Integrating Graph API with Power Automate custom connectors
- Using Azure Logic Apps for enterprise-grade orchestration
- Calling Graph from Durable Functions with state management
- Building custom APIs with Azure API Management
- Exposing Graph data safely to low-code platforms
- Creating reusable automation templates
- Implementing API versioning and deprecation strategies
- Rate limiting external access to internal automation APIs
- Using Azure Event Grid to fan out Graph events
- Visualising workflow execution in Application Insights
- Monitoring performance with custom metrics and alerts
- Deploying automation workflows via CI/CD pipelines
- Managing configuration across dev, test, and prod environments
- Using ARM templates or Bicep for infrastructure as code
- Automating compliance checks with Azure Policy
Module 10: Performance, Scalability & Optimisation - Analysing API usage patterns and bottleneck identification
- Designing for high availability and fault tolerance
- Caching strategies for frequently accessed data
- Implementing retries with exponential backoff
- Using distributed locks to prevent race conditions
- Profiling execution time of AI and Graph interactions
- Reducing network roundtrips with batched operations
- Optimising payload size with selective field returns
- Sharding workloads across multiple tenants or regions
- Estimating monthly call volume and budgeting quotas
- Monitoring usage against Microsoft’s service limits
- Requesting service plan increases when necessary
- Designing fallback mechanisms during Graph outages
- Implementing graceful degradation for non-critical features
- Load testing automation workflows before production
Module 11: Real-World Implementation Projects - Project 1: Automated meeting summary generator with action items
- Connecting to Teams meeting transcripts via Graph
- Calling Azure Cognitive Services for key phrase extraction
- Generating bullet-point summaries with custom logic
- Publishing summaries to SharePoint and notifying attendees
- Project 2: Intelligent email routing system
- Detecting support request patterns in inbound messages
- Classifying urgency using sentiment and keywords
- Routing to correct teams with metadata tagging
- Creating tickets in ServiceNow or Jira via API
- Project 3: Proactive document compliance monitor
- Scanning newly uploaded files in SharePoint
- Detecting personal data with Microsoft Purview
- Applying mandatory retention labels
- Sending notifications to data stewards for review
Module 12: Certification Preparation & Next Steps - Review of core competencies for AI-Driven Graph Automation
- Practice assessment with scenario-based questions
- How to document your automation design for evaluation
- Preparing evidence of implementation proficiency
- Submission process for the Certificate of Completion
- How to reference your certification on LinkedIn and resumes
- Connecting with the global Art of Service alumni network
- Accessing advanced automation design patterns (exclusive)
- Staying updated via official Graph changelogs
- Joining Microsoft’s developer early access programs
- Building a public portfolio of automation solutions
- Transitioning from automation engineer to automation architect
- Leading AI integration initiatives in your organisation
- Presenting your automation ROI to executive stakeholders
- Continuing education paths in AI, security, and cloud architecture
- Project 1: Automated meeting summary generator with action items
- Connecting to Teams meeting transcripts via Graph
- Calling Azure Cognitive Services for key phrase extraction
- Generating bullet-point summaries with custom logic
- Publishing summaries to SharePoint and notifying attendees
- Project 2: Intelligent email routing system
- Detecting support request patterns in inbound messages
- Classifying urgency using sentiment and keywords
- Routing to correct teams with metadata tagging
- Creating tickets in ServiceNow or Jira via API
- Project 3: Proactive document compliance monitor
- Scanning newly uploaded files in SharePoint
- Detecting personal data with Microsoft Purview
- Applying mandatory retention labels
- Sending notifications to data stewards for review