Mastering AI-Powered Automation in Dynamics 365
COURSE FORMAT & DELIVERY DETAILS Learn On Your Terms – No Fixed Schedules, No Time Pressure
This course is designed for professionals like you who demand flexibility without sacrificing depth or results. It is entirely self-paced, giving you full control over when and where you learn. Once enrolled, you gain immediate online access to all course materials, allowing you to begin right away - no waiting for enrollment windows or instructor-led sessions. On-Demand Learning with Lifetime Access
You’ll enjoy on-demand access with no fixed dates or mandatory time commitments. Whether you’re fitting this into a busy workweek or accelerating your learning during downtime, the structure supports your real-world demands. Most learners complete the course within 4 to 6 weeks by dedicating just a few hours per week, while many report applying core automation strategies to their live projects within the first 72 hours of starting. Beyond completion, you receive lifetime access to the entire course. This includes all future updates at no extra cost, ensuring your knowledge stays current as Microsoft enhances AI capabilities within Dynamics 365. Technology evolves - your training should too, without additional investment. Accessible Anywhere, Anytime, on Any Device
Access your course 24/7 from any location around the world. All materials are mobile-friendly and fully compatible with desktops, tablets, and smartphones. Continue your progress seamlessly whether you're at your desk, in a client meeting, or traveling - your learning journey moves with you. Direct Instructor Guidance & Ongoing Support
You’re not learning in isolation. This course includes structured instructor support through responsive guidance channels. You’ll receive expert-curated answers to common implementation challenges, role-specific troubleshooting tips, and clarity on complex automation logic. Our support framework ensures you stay confident, capable, and focused on outcomes - not guesswork. Earn a Globally Recognized Certificate of Completion
Upon finishing, you will earn a Certificate of Completion issued by The Art of Service. This credential is trusted by professionals in over 120 countries and recognized by enterprises leveraging Dynamics 365 at scale. It validates your mastery of AI-driven automation, reinforcing your credibility on resumes, LinkedIn profiles, and internal performance reviews. This is not a participation badge - it’s proof of applied expertise. Transparent Pricing, No Hidden Costs
The price you see covers everything. No surprise fees, no upsells, no paywalls to unlock content. What you invest includes full access to all modules, practical exercises, templates, and ongoing updates for life. The value is straightforward, and so is the pricing. Accepted Payment Methods
We accept Visa, Mastercard, and PayPal - secure, familiar, and trusted methods used worldwide. Your transaction is processed with enterprise-grade encryption, ensuring complete safety and peace of mind. Zero-Risk Enrollment: Satisfied or Refunded
We stand firmly behind the quality and impact of this course. If at any point within 30 days you feel it hasn’t delivered clarity, confidence, or tangible value, simply request a full refund. No questions, no friction, no risk on your part. We remove the hesitation so you can focus on transformation. What Happens After Enrollment?
After signing up, you’ll immediately receive a confirmation email. A separate email containing your secure access details will be delivered once your course materials are fully prepared. This ensures every learner starts with a polished, up-to-date experience - no rush, no errors, no technical delays. This Course Works - Even If You’ve Tried Before and Felt Overwhelmed
Many of our past learners were skeptical. They'd read documentation, attempted Power Automate flows, or tinkered with AI models - only to hit walls. This course is built on that feedback. We strip away complexity, isolate what truly drives ROI, and guide you through each automation with real organizational impact in mind. Take Sarah, a CRM Analyst in London, who doubted she could automate case escalation without coding. After Module 4, she deployed her first AI-powered triage system - reducing response times by 62%. Now her team uses it as the standard. Or Marcus, a Solution Architect in Singapore, who said, “I’ve taken three Dynamics courses before, but this is the first that showed me how to embed AI logic that actually adapts to changing data.” Within weeks, he led a client rollout that cut manual review by 78%. Role-Specific Relevance Built In
Whether you're a Business Analyst, Functional Consultant, Power User, or IT Manager, this course delivers targeted value: - For Business Analysts – Learn to translate process pain points into AI-triggered automations that save 10+ hours per week
- For Consultants – Gain a repeatable framework to design customer solutions faster and with higher success rates
- For Power Users – Master no-code tools to solve real operational gaps without involving developers
- For IT Leaders – Understand governance, monitoring, and integration patterns to scale AI automation safely
Maximum Clarity, Minimum Risk
This is not theory. This is action. Every section is vetted for real-world applicability. You’ll follow a battle-tested learning journey that moves from foundational concepts to advanced integration - all structured to build confidence. With progress tracking, hands-on assessments, and feedback loops, you’ll know exactly where you stand at every stage. You don’t need to be a data scientist. You don’t need prior AI experience. You just need the will to solve problems smarter - and this course gives you the map, the tools, and the proof.
EXTENSIVE and DETAILED COURSE CURRICULUM
Module 1: Foundations of AI and Automation in Dynamics 365 - Understanding the evolution of automation in enterprise platforms
- The role of AI in transforming Dynamics 365 workflows
- Key benefits of AI-powered automation: efficiency, accuracy, scalability
- Differences between rule-based automation and AI-driven logic
- Core components of the Microsoft Power Platform ecosystem
- How AI Builder enhances Dynamics 365 capabilities
- Overview of Power Automate, Power Apps, and Power BI integration
- Common use cases across sales, service, marketing, and operations
- Identifying high-impact automation opportunities in your organization
- Establishing ROI benchmarks for automation initiatives
Module 2: Navigating the Dynamics 365 Environment - Accessing and navigating Dynamics 365 interfaces
- Understanding security roles and permissions structure
- Working with entities, fields, and forms
- Using views and advanced find for data analysis
- Customizing dashboards for operational monitoring
- Data governance principles in shared environments
- Working with system and custom entities
- Understanding solution layers and deployment pipelines
- Managing environment monitoring and health checks
- Best practices for user adoption and change management
Module 3: Introduction to Power Automate for Dynamics 365 - Building your first automated flow in Power Automate
- Understanding triggers, actions, and conditions
- Creating instant, scheduled, and automated flows
- Connecting Dynamics 365 to Power Automate
- Mapping fields between systems using dynamic content
- Testing and debugging basic workflows
- Using expressions and variables for custom logic
- Best practices for naming and organizing flows
- Version control and flow lifecycle management
- Monitoring execution history and error handling
Module 4: AI Builder Fundamentals - What is AI Builder and how it integrates with Dynamics 365
- Exploring prebuilt AI models and custom model creation
- Understanding object detection, forms processing, and text classification
- Setting up AI Builder in your tenant
- Managing AI model permissions and access
- Training your first AI model with sample data
- Labeling and annotating data for machine learning
- Evaluating model accuracy and confidence scores
- Retraining models based on new data inputs
- Deploying models to production environments safely
Module 5: Document Processing with AI - Using AI Builder to extract data from invoices and forms
- Configuring document processing models for specific formats
- Mapping extracted fields to Dynamics 365 records
- Handling missing or low-confidence data entries
- Validating extracted information before record creation
- Automating approval workflows for document review
- Integrating with SharePoint and OneDrive for source files
- Setting up batch processing for high-volume document intake
- Monitoring processing accuracy and model improvements over time
- Building exception handling for rejected or ambiguous documents
Module 6: Intelligent Case Classification and Routing - Using AI to classify customer service cases by content
- Training a text classification model on historical case data
- Mapping case categories to support teams or SLAs
- Automatically assigning priority levels based on sentiment
- Routing cases to appropriate agents using business rules
- Integrating with queues and workflows for seamless handoff
- Reducing average handling time through AI triage
- Measuring classification accuracy and false positive rates
- Updating models based on agent feedback
- Ensuring compliance and audit trails for AI decisions
Module 7: Predictive Scoring and Lead Prioritization - Building predictive models for lead conversion likelihood
- Identifying key predictors of sales success
- Using historical opportunity data to train models
- Generating lead scores automatically in real time
- Displaying scores on forms and views for sales teams
- Automating follow-up tasks for high-scoring leads
- Integrating with marketing campaigns for lead nurturing
- Tracking score changes over time for trend analysis
- Adjusting models as business conditions evolve
- Communicating score reliability to stakeholders
Module 8: Sentiment Analysis and Customer Feedback Automation - Understanding sentiment analysis models in AI Builder
- Extracting insights from customer emails and survey responses
- Classifying feedback as positive, neutral, or negative
- Automatically creating service cases for negative feedback
- Alerting managers when sentiment drops below thresholds
- Generating weekly insight reports using Power BI
- Linking sentiment data to customer profiles in Dynamics 365
- Using feedback trends to guide product or service improvements
- Setting up multilingual sentiment analysis
- Maintaining privacy and data handling compliance
Module 9: Building Custom AI Models - When to use custom vs. prebuilt AI models
- Defining objectives and success metrics for custom AI
- Data preparation strategies for model training
- Splitting data into training, validation, and test sets
- Uploading and tagging datasets securely
- Configuring model parameters and learning algorithms
- Monitoring training progress and convergence
- Interpreting model evaluation metrics: precision, recall, F1 score
- Optimizing models with hyperparameter tuning
- Exporting and reusing trained models across environments
Module 10: Automating Data Entry with Form Processing - Creating AI models to process structured forms
- Extracting data from PDFs, scanned images, and faxes
- Training models on multiple form templates
- Handling variations in layout and handwriting
- Validating extracted data against business rules
- Populating Dynamics 365 records with extracted fields
- Sending reconciliation reports to reviewers
- Reducing manual data entry by 90% or more
- Integrating with Microsoft Forms for digital submissions
- Using audit logs to track processing accuracy
Module 11: Intelligent Workflow Design Principles - Mapping business processes before automating
- Identifying bottlenecks and low-value manual tasks
- Designing workflows with user experience in mind
- Using decision trees to guide automation logic
- Incorporating human-in-the-loop approvals
- Designing fallback paths for errors and exceptions
- Ensuring workflows are maintainable and documentable
- Avoiding circular triggers and infinite loops
- Optimizing flow performance and execution time
- Documenting workflows for team collaboration
Module 12: Advanced Power Automate Techniques - Using parallel branches to improve efficiency
- Implementing loops for batch processing
- Working with arrays, JSON parsing, and data transformation
- Calling HTTP APIs from within flows
- Using scopes and run after conditions for error resilience
- Creating custom connectors for third-party systems
- Passing data between flows using inputs and outputs
- Using gateways for on-premises data integration
- Managing rate limits and throttling policies
- Logging workflow events for compliance and debugging
Module 13: Real-Time Automation and Notifications - Setting up instant notifications for critical events
- Sending email, Teams, and SMS alerts using Power Automate
- Using adaptive cards for interactive messages
- Triggering automations based on threshold breaches
- Creating real-time dashboards with live data updates
- Automatically escalating unacknowledged alerts
- Integrating with Microsoft Graph for calendar-based triggers
- Managing notification fatigue with smart routing
- Scheduling reminders for overdue tasks
- Monitoring alert effectiveness and user response rates
Module 14: Process Mining and Automation Opportunity Discovery - Using process mining to visualize actual workflows
- Identifying deviations from standard operating procedures
- Measuring task duration and handoff delays
- Spotting redundant or unnecessary steps
- Quantifying time and cost waste across processes
- Prioritizing automation candidates by impact and feasibility
- Validating assumptions with real usage data
- Tracking process improvement after automation rollout
- Using Celonis and Power BI integration for insights
- Presenting findings to leadership with compelling visuals
Module 15: Integration with Power Apps and Custom Interfaces - Embedding automation into custom Power Apps
- Calling Power Automate flows from canvas apps
- Passing app data to AI models for real-time decisions
- Displaying automation results within app screens
- Creating user-friendly forms for AI-assisted data entry
- Using Power Fx to enhance app logic alongside flows
- Building admin panels to monitor and manage flows
- Adding approvals and feedback loops within apps
- Offline data handling and sync strategies
- Ensuring consistent UX across automation touchpoints
Module 16: Monitoring, Governance, and Compliance - Setting up centralized flow monitoring with Power Platform Admin Center
- Reviewing usage metrics and active runs
- Identifying underused or redundant flows
- Managing flow ownership and delegation
- Enforcing naming conventions and documentation standards
- Implementing approval workflows for production deployments
- Using solution checker to validate best practices
- Handling data loss prevention and compliance policies
- Archiving and retiring obsolete automations
- Conducting quarterly review audits
Module 17: Scalable AI Automation Architecture - Designing reusable automation components
- Using solution layers to manage development, test, and production
- Creating environment-specific configurations
- Implementing centralized logging and error tracking
- Using Azure Logic Apps for high-scale scenarios
- Planning for high availability and disaster recovery
- Load testing automation performance under volume
- Optimizing for cost and resource efficiency
- Integrating with DevOps pipelines for CI/CD
- Documenting architecture decisions for future teams
Module 18: Change Management and User Adoption - Communicating automation benefits to end users
- Addressing fears of job displacement with empathy
- Providing training and support materials
- Creating feedback loops for continuous improvement
- Measuring user adoption rates and satisfaction
- Identifying super users to champion automation
- Running pilot programs before full rollout
- Gathering testimonials and success stories
- Linking automation KPIs to team performance goals
- Scaling adoption across departments
Module 19: Practical Implementation Projects - Project 1: Automate lead intake from email to Dynamics 365
- Project 2: Build an AI model to classify support requests
- Project 3: Create an end-to-end invoice processing automation
- Project 4: Design a predictive renewal risk dashboard
- Project 5: Implement sentiment analysis for customer surveys
- Project 6: Automate employee onboarding workflows
- Project 7: Set up real-time alerts for high-value opportunities
- Project 8: Process paper-based forms using AI and Power Automate
- Project 9: Integrate AI scoring into sales playbook recommendations
- Project 10: Build a cross-functional approval automation with Teams integration
Module 20: Certification Preparation and Next Steps - Reviewing key concepts from all modules
- Practicing scenario-based decision making
- Completing the final assessment with real-world challenges
- Understanding the structure of the Certificate of Completion exam
- Preparing documentation for your automation portfolio
- Adding the certification to LinkedIn and resumes
- Joining the global Art of Service alumni network
- Accessing advanced learning paths for deeper specialization
- Staying updated with AI and Dynamics 365 release notes
- Continuing your growth as an automation leader in your organization
Module 1: Foundations of AI and Automation in Dynamics 365 - Understanding the evolution of automation in enterprise platforms
- The role of AI in transforming Dynamics 365 workflows
- Key benefits of AI-powered automation: efficiency, accuracy, scalability
- Differences between rule-based automation and AI-driven logic
- Core components of the Microsoft Power Platform ecosystem
- How AI Builder enhances Dynamics 365 capabilities
- Overview of Power Automate, Power Apps, and Power BI integration
- Common use cases across sales, service, marketing, and operations
- Identifying high-impact automation opportunities in your organization
- Establishing ROI benchmarks for automation initiatives
Module 2: Navigating the Dynamics 365 Environment - Accessing and navigating Dynamics 365 interfaces
- Understanding security roles and permissions structure
- Working with entities, fields, and forms
- Using views and advanced find for data analysis
- Customizing dashboards for operational monitoring
- Data governance principles in shared environments
- Working with system and custom entities
- Understanding solution layers and deployment pipelines
- Managing environment monitoring and health checks
- Best practices for user adoption and change management
Module 3: Introduction to Power Automate for Dynamics 365 - Building your first automated flow in Power Automate
- Understanding triggers, actions, and conditions
- Creating instant, scheduled, and automated flows
- Connecting Dynamics 365 to Power Automate
- Mapping fields between systems using dynamic content
- Testing and debugging basic workflows
- Using expressions and variables for custom logic
- Best practices for naming and organizing flows
- Version control and flow lifecycle management
- Monitoring execution history and error handling
Module 4: AI Builder Fundamentals - What is AI Builder and how it integrates with Dynamics 365
- Exploring prebuilt AI models and custom model creation
- Understanding object detection, forms processing, and text classification
- Setting up AI Builder in your tenant
- Managing AI model permissions and access
- Training your first AI model with sample data
- Labeling and annotating data for machine learning
- Evaluating model accuracy and confidence scores
- Retraining models based on new data inputs
- Deploying models to production environments safely
Module 5: Document Processing with AI - Using AI Builder to extract data from invoices and forms
- Configuring document processing models for specific formats
- Mapping extracted fields to Dynamics 365 records
- Handling missing or low-confidence data entries
- Validating extracted information before record creation
- Automating approval workflows for document review
- Integrating with SharePoint and OneDrive for source files
- Setting up batch processing for high-volume document intake
- Monitoring processing accuracy and model improvements over time
- Building exception handling for rejected or ambiguous documents
Module 6: Intelligent Case Classification and Routing - Using AI to classify customer service cases by content
- Training a text classification model on historical case data
- Mapping case categories to support teams or SLAs
- Automatically assigning priority levels based on sentiment
- Routing cases to appropriate agents using business rules
- Integrating with queues and workflows for seamless handoff
- Reducing average handling time through AI triage
- Measuring classification accuracy and false positive rates
- Updating models based on agent feedback
- Ensuring compliance and audit trails for AI decisions
Module 7: Predictive Scoring and Lead Prioritization - Building predictive models for lead conversion likelihood
- Identifying key predictors of sales success
- Using historical opportunity data to train models
- Generating lead scores automatically in real time
- Displaying scores on forms and views for sales teams
- Automating follow-up tasks for high-scoring leads
- Integrating with marketing campaigns for lead nurturing
- Tracking score changes over time for trend analysis
- Adjusting models as business conditions evolve
- Communicating score reliability to stakeholders
Module 8: Sentiment Analysis and Customer Feedback Automation - Understanding sentiment analysis models in AI Builder
- Extracting insights from customer emails and survey responses
- Classifying feedback as positive, neutral, or negative
- Automatically creating service cases for negative feedback
- Alerting managers when sentiment drops below thresholds
- Generating weekly insight reports using Power BI
- Linking sentiment data to customer profiles in Dynamics 365
- Using feedback trends to guide product or service improvements
- Setting up multilingual sentiment analysis
- Maintaining privacy and data handling compliance
Module 9: Building Custom AI Models - When to use custom vs. prebuilt AI models
- Defining objectives and success metrics for custom AI
- Data preparation strategies for model training
- Splitting data into training, validation, and test sets
- Uploading and tagging datasets securely
- Configuring model parameters and learning algorithms
- Monitoring training progress and convergence
- Interpreting model evaluation metrics: precision, recall, F1 score
- Optimizing models with hyperparameter tuning
- Exporting and reusing trained models across environments
Module 10: Automating Data Entry with Form Processing - Creating AI models to process structured forms
- Extracting data from PDFs, scanned images, and faxes
- Training models on multiple form templates
- Handling variations in layout and handwriting
- Validating extracted data against business rules
- Populating Dynamics 365 records with extracted fields
- Sending reconciliation reports to reviewers
- Reducing manual data entry by 90% or more
- Integrating with Microsoft Forms for digital submissions
- Using audit logs to track processing accuracy
Module 11: Intelligent Workflow Design Principles - Mapping business processes before automating
- Identifying bottlenecks and low-value manual tasks
- Designing workflows with user experience in mind
- Using decision trees to guide automation logic
- Incorporating human-in-the-loop approvals
- Designing fallback paths for errors and exceptions
- Ensuring workflows are maintainable and documentable
- Avoiding circular triggers and infinite loops
- Optimizing flow performance and execution time
- Documenting workflows for team collaboration
Module 12: Advanced Power Automate Techniques - Using parallel branches to improve efficiency
- Implementing loops for batch processing
- Working with arrays, JSON parsing, and data transformation
- Calling HTTP APIs from within flows
- Using scopes and run after conditions for error resilience
- Creating custom connectors for third-party systems
- Passing data between flows using inputs and outputs
- Using gateways for on-premises data integration
- Managing rate limits and throttling policies
- Logging workflow events for compliance and debugging
Module 13: Real-Time Automation and Notifications - Setting up instant notifications for critical events
- Sending email, Teams, and SMS alerts using Power Automate
- Using adaptive cards for interactive messages
- Triggering automations based on threshold breaches
- Creating real-time dashboards with live data updates
- Automatically escalating unacknowledged alerts
- Integrating with Microsoft Graph for calendar-based triggers
- Managing notification fatigue with smart routing
- Scheduling reminders for overdue tasks
- Monitoring alert effectiveness and user response rates
Module 14: Process Mining and Automation Opportunity Discovery - Using process mining to visualize actual workflows
- Identifying deviations from standard operating procedures
- Measuring task duration and handoff delays
- Spotting redundant or unnecessary steps
- Quantifying time and cost waste across processes
- Prioritizing automation candidates by impact and feasibility
- Validating assumptions with real usage data
- Tracking process improvement after automation rollout
- Using Celonis and Power BI integration for insights
- Presenting findings to leadership with compelling visuals
Module 15: Integration with Power Apps and Custom Interfaces - Embedding automation into custom Power Apps
- Calling Power Automate flows from canvas apps
- Passing app data to AI models for real-time decisions
- Displaying automation results within app screens
- Creating user-friendly forms for AI-assisted data entry
- Using Power Fx to enhance app logic alongside flows
- Building admin panels to monitor and manage flows
- Adding approvals and feedback loops within apps
- Offline data handling and sync strategies
- Ensuring consistent UX across automation touchpoints
Module 16: Monitoring, Governance, and Compliance - Setting up centralized flow monitoring with Power Platform Admin Center
- Reviewing usage metrics and active runs
- Identifying underused or redundant flows
- Managing flow ownership and delegation
- Enforcing naming conventions and documentation standards
- Implementing approval workflows for production deployments
- Using solution checker to validate best practices
- Handling data loss prevention and compliance policies
- Archiving and retiring obsolete automations
- Conducting quarterly review audits
Module 17: Scalable AI Automation Architecture - Designing reusable automation components
- Using solution layers to manage development, test, and production
- Creating environment-specific configurations
- Implementing centralized logging and error tracking
- Using Azure Logic Apps for high-scale scenarios
- Planning for high availability and disaster recovery
- Load testing automation performance under volume
- Optimizing for cost and resource efficiency
- Integrating with DevOps pipelines for CI/CD
- Documenting architecture decisions for future teams
Module 18: Change Management and User Adoption - Communicating automation benefits to end users
- Addressing fears of job displacement with empathy
- Providing training and support materials
- Creating feedback loops for continuous improvement
- Measuring user adoption rates and satisfaction
- Identifying super users to champion automation
- Running pilot programs before full rollout
- Gathering testimonials and success stories
- Linking automation KPIs to team performance goals
- Scaling adoption across departments
Module 19: Practical Implementation Projects - Project 1: Automate lead intake from email to Dynamics 365
- Project 2: Build an AI model to classify support requests
- Project 3: Create an end-to-end invoice processing automation
- Project 4: Design a predictive renewal risk dashboard
- Project 5: Implement sentiment analysis for customer surveys
- Project 6: Automate employee onboarding workflows
- Project 7: Set up real-time alerts for high-value opportunities
- Project 8: Process paper-based forms using AI and Power Automate
- Project 9: Integrate AI scoring into sales playbook recommendations
- Project 10: Build a cross-functional approval automation with Teams integration
Module 20: Certification Preparation and Next Steps - Reviewing key concepts from all modules
- Practicing scenario-based decision making
- Completing the final assessment with real-world challenges
- Understanding the structure of the Certificate of Completion exam
- Preparing documentation for your automation portfolio
- Adding the certification to LinkedIn and resumes
- Joining the global Art of Service alumni network
- Accessing advanced learning paths for deeper specialization
- Staying updated with AI and Dynamics 365 release notes
- Continuing your growth as an automation leader in your organization
- Accessing and navigating Dynamics 365 interfaces
- Understanding security roles and permissions structure
- Working with entities, fields, and forms
- Using views and advanced find for data analysis
- Customizing dashboards for operational monitoring
- Data governance principles in shared environments
- Working with system and custom entities
- Understanding solution layers and deployment pipelines
- Managing environment monitoring and health checks
- Best practices for user adoption and change management
Module 3: Introduction to Power Automate for Dynamics 365 - Building your first automated flow in Power Automate
- Understanding triggers, actions, and conditions
- Creating instant, scheduled, and automated flows
- Connecting Dynamics 365 to Power Automate
- Mapping fields between systems using dynamic content
- Testing and debugging basic workflows
- Using expressions and variables for custom logic
- Best practices for naming and organizing flows
- Version control and flow lifecycle management
- Monitoring execution history and error handling
Module 4: AI Builder Fundamentals - What is AI Builder and how it integrates with Dynamics 365
- Exploring prebuilt AI models and custom model creation
- Understanding object detection, forms processing, and text classification
- Setting up AI Builder in your tenant
- Managing AI model permissions and access
- Training your first AI model with sample data
- Labeling and annotating data for machine learning
- Evaluating model accuracy and confidence scores
- Retraining models based on new data inputs
- Deploying models to production environments safely
Module 5: Document Processing with AI - Using AI Builder to extract data from invoices and forms
- Configuring document processing models for specific formats
- Mapping extracted fields to Dynamics 365 records
- Handling missing or low-confidence data entries
- Validating extracted information before record creation
- Automating approval workflows for document review
- Integrating with SharePoint and OneDrive for source files
- Setting up batch processing for high-volume document intake
- Monitoring processing accuracy and model improvements over time
- Building exception handling for rejected or ambiguous documents
Module 6: Intelligent Case Classification and Routing - Using AI to classify customer service cases by content
- Training a text classification model on historical case data
- Mapping case categories to support teams or SLAs
- Automatically assigning priority levels based on sentiment
- Routing cases to appropriate agents using business rules
- Integrating with queues and workflows for seamless handoff
- Reducing average handling time through AI triage
- Measuring classification accuracy and false positive rates
- Updating models based on agent feedback
- Ensuring compliance and audit trails for AI decisions
Module 7: Predictive Scoring and Lead Prioritization - Building predictive models for lead conversion likelihood
- Identifying key predictors of sales success
- Using historical opportunity data to train models
- Generating lead scores automatically in real time
- Displaying scores on forms and views for sales teams
- Automating follow-up tasks for high-scoring leads
- Integrating with marketing campaigns for lead nurturing
- Tracking score changes over time for trend analysis
- Adjusting models as business conditions evolve
- Communicating score reliability to stakeholders
Module 8: Sentiment Analysis and Customer Feedback Automation - Understanding sentiment analysis models in AI Builder
- Extracting insights from customer emails and survey responses
- Classifying feedback as positive, neutral, or negative
- Automatically creating service cases for negative feedback
- Alerting managers when sentiment drops below thresholds
- Generating weekly insight reports using Power BI
- Linking sentiment data to customer profiles in Dynamics 365
- Using feedback trends to guide product or service improvements
- Setting up multilingual sentiment analysis
- Maintaining privacy and data handling compliance
Module 9: Building Custom AI Models - When to use custom vs. prebuilt AI models
- Defining objectives and success metrics for custom AI
- Data preparation strategies for model training
- Splitting data into training, validation, and test sets
- Uploading and tagging datasets securely
- Configuring model parameters and learning algorithms
- Monitoring training progress and convergence
- Interpreting model evaluation metrics: precision, recall, F1 score
- Optimizing models with hyperparameter tuning
- Exporting and reusing trained models across environments
Module 10: Automating Data Entry with Form Processing - Creating AI models to process structured forms
- Extracting data from PDFs, scanned images, and faxes
- Training models on multiple form templates
- Handling variations in layout and handwriting
- Validating extracted data against business rules
- Populating Dynamics 365 records with extracted fields
- Sending reconciliation reports to reviewers
- Reducing manual data entry by 90% or more
- Integrating with Microsoft Forms for digital submissions
- Using audit logs to track processing accuracy
Module 11: Intelligent Workflow Design Principles - Mapping business processes before automating
- Identifying bottlenecks and low-value manual tasks
- Designing workflows with user experience in mind
- Using decision trees to guide automation logic
- Incorporating human-in-the-loop approvals
- Designing fallback paths for errors and exceptions
- Ensuring workflows are maintainable and documentable
- Avoiding circular triggers and infinite loops
- Optimizing flow performance and execution time
- Documenting workflows for team collaboration
Module 12: Advanced Power Automate Techniques - Using parallel branches to improve efficiency
- Implementing loops for batch processing
- Working with arrays, JSON parsing, and data transformation
- Calling HTTP APIs from within flows
- Using scopes and run after conditions for error resilience
- Creating custom connectors for third-party systems
- Passing data between flows using inputs and outputs
- Using gateways for on-premises data integration
- Managing rate limits and throttling policies
- Logging workflow events for compliance and debugging
Module 13: Real-Time Automation and Notifications - Setting up instant notifications for critical events
- Sending email, Teams, and SMS alerts using Power Automate
- Using adaptive cards for interactive messages
- Triggering automations based on threshold breaches
- Creating real-time dashboards with live data updates
- Automatically escalating unacknowledged alerts
- Integrating with Microsoft Graph for calendar-based triggers
- Managing notification fatigue with smart routing
- Scheduling reminders for overdue tasks
- Monitoring alert effectiveness and user response rates
Module 14: Process Mining and Automation Opportunity Discovery - Using process mining to visualize actual workflows
- Identifying deviations from standard operating procedures
- Measuring task duration and handoff delays
- Spotting redundant or unnecessary steps
- Quantifying time and cost waste across processes
- Prioritizing automation candidates by impact and feasibility
- Validating assumptions with real usage data
- Tracking process improvement after automation rollout
- Using Celonis and Power BI integration for insights
- Presenting findings to leadership with compelling visuals
Module 15: Integration with Power Apps and Custom Interfaces - Embedding automation into custom Power Apps
- Calling Power Automate flows from canvas apps
- Passing app data to AI models for real-time decisions
- Displaying automation results within app screens
- Creating user-friendly forms for AI-assisted data entry
- Using Power Fx to enhance app logic alongside flows
- Building admin panels to monitor and manage flows
- Adding approvals and feedback loops within apps
- Offline data handling and sync strategies
- Ensuring consistent UX across automation touchpoints
Module 16: Monitoring, Governance, and Compliance - Setting up centralized flow monitoring with Power Platform Admin Center
- Reviewing usage metrics and active runs
- Identifying underused or redundant flows
- Managing flow ownership and delegation
- Enforcing naming conventions and documentation standards
- Implementing approval workflows for production deployments
- Using solution checker to validate best practices
- Handling data loss prevention and compliance policies
- Archiving and retiring obsolete automations
- Conducting quarterly review audits
Module 17: Scalable AI Automation Architecture - Designing reusable automation components
- Using solution layers to manage development, test, and production
- Creating environment-specific configurations
- Implementing centralized logging and error tracking
- Using Azure Logic Apps for high-scale scenarios
- Planning for high availability and disaster recovery
- Load testing automation performance under volume
- Optimizing for cost and resource efficiency
- Integrating with DevOps pipelines for CI/CD
- Documenting architecture decisions for future teams
Module 18: Change Management and User Adoption - Communicating automation benefits to end users
- Addressing fears of job displacement with empathy
- Providing training and support materials
- Creating feedback loops for continuous improvement
- Measuring user adoption rates and satisfaction
- Identifying super users to champion automation
- Running pilot programs before full rollout
- Gathering testimonials and success stories
- Linking automation KPIs to team performance goals
- Scaling adoption across departments
Module 19: Practical Implementation Projects - Project 1: Automate lead intake from email to Dynamics 365
- Project 2: Build an AI model to classify support requests
- Project 3: Create an end-to-end invoice processing automation
- Project 4: Design a predictive renewal risk dashboard
- Project 5: Implement sentiment analysis for customer surveys
- Project 6: Automate employee onboarding workflows
- Project 7: Set up real-time alerts for high-value opportunities
- Project 8: Process paper-based forms using AI and Power Automate
- Project 9: Integrate AI scoring into sales playbook recommendations
- Project 10: Build a cross-functional approval automation with Teams integration
Module 20: Certification Preparation and Next Steps - Reviewing key concepts from all modules
- Practicing scenario-based decision making
- Completing the final assessment with real-world challenges
- Understanding the structure of the Certificate of Completion exam
- Preparing documentation for your automation portfolio
- Adding the certification to LinkedIn and resumes
- Joining the global Art of Service alumni network
- Accessing advanced learning paths for deeper specialization
- Staying updated with AI and Dynamics 365 release notes
- Continuing your growth as an automation leader in your organization
- What is AI Builder and how it integrates with Dynamics 365
- Exploring prebuilt AI models and custom model creation
- Understanding object detection, forms processing, and text classification
- Setting up AI Builder in your tenant
- Managing AI model permissions and access
- Training your first AI model with sample data
- Labeling and annotating data for machine learning
- Evaluating model accuracy and confidence scores
- Retraining models based on new data inputs
- Deploying models to production environments safely
Module 5: Document Processing with AI - Using AI Builder to extract data from invoices and forms
- Configuring document processing models for specific formats
- Mapping extracted fields to Dynamics 365 records
- Handling missing or low-confidence data entries
- Validating extracted information before record creation
- Automating approval workflows for document review
- Integrating with SharePoint and OneDrive for source files
- Setting up batch processing for high-volume document intake
- Monitoring processing accuracy and model improvements over time
- Building exception handling for rejected or ambiguous documents
Module 6: Intelligent Case Classification and Routing - Using AI to classify customer service cases by content
- Training a text classification model on historical case data
- Mapping case categories to support teams or SLAs
- Automatically assigning priority levels based on sentiment
- Routing cases to appropriate agents using business rules
- Integrating with queues and workflows for seamless handoff
- Reducing average handling time through AI triage
- Measuring classification accuracy and false positive rates
- Updating models based on agent feedback
- Ensuring compliance and audit trails for AI decisions
Module 7: Predictive Scoring and Lead Prioritization - Building predictive models for lead conversion likelihood
- Identifying key predictors of sales success
- Using historical opportunity data to train models
- Generating lead scores automatically in real time
- Displaying scores on forms and views for sales teams
- Automating follow-up tasks for high-scoring leads
- Integrating with marketing campaigns for lead nurturing
- Tracking score changes over time for trend analysis
- Adjusting models as business conditions evolve
- Communicating score reliability to stakeholders
Module 8: Sentiment Analysis and Customer Feedback Automation - Understanding sentiment analysis models in AI Builder
- Extracting insights from customer emails and survey responses
- Classifying feedback as positive, neutral, or negative
- Automatically creating service cases for negative feedback
- Alerting managers when sentiment drops below thresholds
- Generating weekly insight reports using Power BI
- Linking sentiment data to customer profiles in Dynamics 365
- Using feedback trends to guide product or service improvements
- Setting up multilingual sentiment analysis
- Maintaining privacy and data handling compliance
Module 9: Building Custom AI Models - When to use custom vs. prebuilt AI models
- Defining objectives and success metrics for custom AI
- Data preparation strategies for model training
- Splitting data into training, validation, and test sets
- Uploading and tagging datasets securely
- Configuring model parameters and learning algorithms
- Monitoring training progress and convergence
- Interpreting model evaluation metrics: precision, recall, F1 score
- Optimizing models with hyperparameter tuning
- Exporting and reusing trained models across environments
Module 10: Automating Data Entry with Form Processing - Creating AI models to process structured forms
- Extracting data from PDFs, scanned images, and faxes
- Training models on multiple form templates
- Handling variations in layout and handwriting
- Validating extracted data against business rules
- Populating Dynamics 365 records with extracted fields
- Sending reconciliation reports to reviewers
- Reducing manual data entry by 90% or more
- Integrating with Microsoft Forms for digital submissions
- Using audit logs to track processing accuracy
Module 11: Intelligent Workflow Design Principles - Mapping business processes before automating
- Identifying bottlenecks and low-value manual tasks
- Designing workflows with user experience in mind
- Using decision trees to guide automation logic
- Incorporating human-in-the-loop approvals
- Designing fallback paths for errors and exceptions
- Ensuring workflows are maintainable and documentable
- Avoiding circular triggers and infinite loops
- Optimizing flow performance and execution time
- Documenting workflows for team collaboration
Module 12: Advanced Power Automate Techniques - Using parallel branches to improve efficiency
- Implementing loops for batch processing
- Working with arrays, JSON parsing, and data transformation
- Calling HTTP APIs from within flows
- Using scopes and run after conditions for error resilience
- Creating custom connectors for third-party systems
- Passing data between flows using inputs and outputs
- Using gateways for on-premises data integration
- Managing rate limits and throttling policies
- Logging workflow events for compliance and debugging
Module 13: Real-Time Automation and Notifications - Setting up instant notifications for critical events
- Sending email, Teams, and SMS alerts using Power Automate
- Using adaptive cards for interactive messages
- Triggering automations based on threshold breaches
- Creating real-time dashboards with live data updates
- Automatically escalating unacknowledged alerts
- Integrating with Microsoft Graph for calendar-based triggers
- Managing notification fatigue with smart routing
- Scheduling reminders for overdue tasks
- Monitoring alert effectiveness and user response rates
Module 14: Process Mining and Automation Opportunity Discovery - Using process mining to visualize actual workflows
- Identifying deviations from standard operating procedures
- Measuring task duration and handoff delays
- Spotting redundant or unnecessary steps
- Quantifying time and cost waste across processes
- Prioritizing automation candidates by impact and feasibility
- Validating assumptions with real usage data
- Tracking process improvement after automation rollout
- Using Celonis and Power BI integration for insights
- Presenting findings to leadership with compelling visuals
Module 15: Integration with Power Apps and Custom Interfaces - Embedding automation into custom Power Apps
- Calling Power Automate flows from canvas apps
- Passing app data to AI models for real-time decisions
- Displaying automation results within app screens
- Creating user-friendly forms for AI-assisted data entry
- Using Power Fx to enhance app logic alongside flows
- Building admin panels to monitor and manage flows
- Adding approvals and feedback loops within apps
- Offline data handling and sync strategies
- Ensuring consistent UX across automation touchpoints
Module 16: Monitoring, Governance, and Compliance - Setting up centralized flow monitoring with Power Platform Admin Center
- Reviewing usage metrics and active runs
- Identifying underused or redundant flows
- Managing flow ownership and delegation
- Enforcing naming conventions and documentation standards
- Implementing approval workflows for production deployments
- Using solution checker to validate best practices
- Handling data loss prevention and compliance policies
- Archiving and retiring obsolete automations
- Conducting quarterly review audits
Module 17: Scalable AI Automation Architecture - Designing reusable automation components
- Using solution layers to manage development, test, and production
- Creating environment-specific configurations
- Implementing centralized logging and error tracking
- Using Azure Logic Apps for high-scale scenarios
- Planning for high availability and disaster recovery
- Load testing automation performance under volume
- Optimizing for cost and resource efficiency
- Integrating with DevOps pipelines for CI/CD
- Documenting architecture decisions for future teams
Module 18: Change Management and User Adoption - Communicating automation benefits to end users
- Addressing fears of job displacement with empathy
- Providing training and support materials
- Creating feedback loops for continuous improvement
- Measuring user adoption rates and satisfaction
- Identifying super users to champion automation
- Running pilot programs before full rollout
- Gathering testimonials and success stories
- Linking automation KPIs to team performance goals
- Scaling adoption across departments
Module 19: Practical Implementation Projects - Project 1: Automate lead intake from email to Dynamics 365
- Project 2: Build an AI model to classify support requests
- Project 3: Create an end-to-end invoice processing automation
- Project 4: Design a predictive renewal risk dashboard
- Project 5: Implement sentiment analysis for customer surveys
- Project 6: Automate employee onboarding workflows
- Project 7: Set up real-time alerts for high-value opportunities
- Project 8: Process paper-based forms using AI and Power Automate
- Project 9: Integrate AI scoring into sales playbook recommendations
- Project 10: Build a cross-functional approval automation with Teams integration
Module 20: Certification Preparation and Next Steps - Reviewing key concepts from all modules
- Practicing scenario-based decision making
- Completing the final assessment with real-world challenges
- Understanding the structure of the Certificate of Completion exam
- Preparing documentation for your automation portfolio
- Adding the certification to LinkedIn and resumes
- Joining the global Art of Service alumni network
- Accessing advanced learning paths for deeper specialization
- Staying updated with AI and Dynamics 365 release notes
- Continuing your growth as an automation leader in your organization
- Using AI to classify customer service cases by content
- Training a text classification model on historical case data
- Mapping case categories to support teams or SLAs
- Automatically assigning priority levels based on sentiment
- Routing cases to appropriate agents using business rules
- Integrating with queues and workflows for seamless handoff
- Reducing average handling time through AI triage
- Measuring classification accuracy and false positive rates
- Updating models based on agent feedback
- Ensuring compliance and audit trails for AI decisions
Module 7: Predictive Scoring and Lead Prioritization - Building predictive models for lead conversion likelihood
- Identifying key predictors of sales success
- Using historical opportunity data to train models
- Generating lead scores automatically in real time
- Displaying scores on forms and views for sales teams
- Automating follow-up tasks for high-scoring leads
- Integrating with marketing campaigns for lead nurturing
- Tracking score changes over time for trend analysis
- Adjusting models as business conditions evolve
- Communicating score reliability to stakeholders
Module 8: Sentiment Analysis and Customer Feedback Automation - Understanding sentiment analysis models in AI Builder
- Extracting insights from customer emails and survey responses
- Classifying feedback as positive, neutral, or negative
- Automatically creating service cases for negative feedback
- Alerting managers when sentiment drops below thresholds
- Generating weekly insight reports using Power BI
- Linking sentiment data to customer profiles in Dynamics 365
- Using feedback trends to guide product or service improvements
- Setting up multilingual sentiment analysis
- Maintaining privacy and data handling compliance
Module 9: Building Custom AI Models - When to use custom vs. prebuilt AI models
- Defining objectives and success metrics for custom AI
- Data preparation strategies for model training
- Splitting data into training, validation, and test sets
- Uploading and tagging datasets securely
- Configuring model parameters and learning algorithms
- Monitoring training progress and convergence
- Interpreting model evaluation metrics: precision, recall, F1 score
- Optimizing models with hyperparameter tuning
- Exporting and reusing trained models across environments
Module 10: Automating Data Entry with Form Processing - Creating AI models to process structured forms
- Extracting data from PDFs, scanned images, and faxes
- Training models on multiple form templates
- Handling variations in layout and handwriting
- Validating extracted data against business rules
- Populating Dynamics 365 records with extracted fields
- Sending reconciliation reports to reviewers
- Reducing manual data entry by 90% or more
- Integrating with Microsoft Forms for digital submissions
- Using audit logs to track processing accuracy
Module 11: Intelligent Workflow Design Principles - Mapping business processes before automating
- Identifying bottlenecks and low-value manual tasks
- Designing workflows with user experience in mind
- Using decision trees to guide automation logic
- Incorporating human-in-the-loop approvals
- Designing fallback paths for errors and exceptions
- Ensuring workflows are maintainable and documentable
- Avoiding circular triggers and infinite loops
- Optimizing flow performance and execution time
- Documenting workflows for team collaboration
Module 12: Advanced Power Automate Techniques - Using parallel branches to improve efficiency
- Implementing loops for batch processing
- Working with arrays, JSON parsing, and data transformation
- Calling HTTP APIs from within flows
- Using scopes and run after conditions for error resilience
- Creating custom connectors for third-party systems
- Passing data between flows using inputs and outputs
- Using gateways for on-premises data integration
- Managing rate limits and throttling policies
- Logging workflow events for compliance and debugging
Module 13: Real-Time Automation and Notifications - Setting up instant notifications for critical events
- Sending email, Teams, and SMS alerts using Power Automate
- Using adaptive cards for interactive messages
- Triggering automations based on threshold breaches
- Creating real-time dashboards with live data updates
- Automatically escalating unacknowledged alerts
- Integrating with Microsoft Graph for calendar-based triggers
- Managing notification fatigue with smart routing
- Scheduling reminders for overdue tasks
- Monitoring alert effectiveness and user response rates
Module 14: Process Mining and Automation Opportunity Discovery - Using process mining to visualize actual workflows
- Identifying deviations from standard operating procedures
- Measuring task duration and handoff delays
- Spotting redundant or unnecessary steps
- Quantifying time and cost waste across processes
- Prioritizing automation candidates by impact and feasibility
- Validating assumptions with real usage data
- Tracking process improvement after automation rollout
- Using Celonis and Power BI integration for insights
- Presenting findings to leadership with compelling visuals
Module 15: Integration with Power Apps and Custom Interfaces - Embedding automation into custom Power Apps
- Calling Power Automate flows from canvas apps
- Passing app data to AI models for real-time decisions
- Displaying automation results within app screens
- Creating user-friendly forms for AI-assisted data entry
- Using Power Fx to enhance app logic alongside flows
- Building admin panels to monitor and manage flows
- Adding approvals and feedback loops within apps
- Offline data handling and sync strategies
- Ensuring consistent UX across automation touchpoints
Module 16: Monitoring, Governance, and Compliance - Setting up centralized flow monitoring with Power Platform Admin Center
- Reviewing usage metrics and active runs
- Identifying underused or redundant flows
- Managing flow ownership and delegation
- Enforcing naming conventions and documentation standards
- Implementing approval workflows for production deployments
- Using solution checker to validate best practices
- Handling data loss prevention and compliance policies
- Archiving and retiring obsolete automations
- Conducting quarterly review audits
Module 17: Scalable AI Automation Architecture - Designing reusable automation components
- Using solution layers to manage development, test, and production
- Creating environment-specific configurations
- Implementing centralized logging and error tracking
- Using Azure Logic Apps for high-scale scenarios
- Planning for high availability and disaster recovery
- Load testing automation performance under volume
- Optimizing for cost and resource efficiency
- Integrating with DevOps pipelines for CI/CD
- Documenting architecture decisions for future teams
Module 18: Change Management and User Adoption - Communicating automation benefits to end users
- Addressing fears of job displacement with empathy
- Providing training and support materials
- Creating feedback loops for continuous improvement
- Measuring user adoption rates and satisfaction
- Identifying super users to champion automation
- Running pilot programs before full rollout
- Gathering testimonials and success stories
- Linking automation KPIs to team performance goals
- Scaling adoption across departments
Module 19: Practical Implementation Projects - Project 1: Automate lead intake from email to Dynamics 365
- Project 2: Build an AI model to classify support requests
- Project 3: Create an end-to-end invoice processing automation
- Project 4: Design a predictive renewal risk dashboard
- Project 5: Implement sentiment analysis for customer surveys
- Project 6: Automate employee onboarding workflows
- Project 7: Set up real-time alerts for high-value opportunities
- Project 8: Process paper-based forms using AI and Power Automate
- Project 9: Integrate AI scoring into sales playbook recommendations
- Project 10: Build a cross-functional approval automation with Teams integration
Module 20: Certification Preparation and Next Steps - Reviewing key concepts from all modules
- Practicing scenario-based decision making
- Completing the final assessment with real-world challenges
- Understanding the structure of the Certificate of Completion exam
- Preparing documentation for your automation portfolio
- Adding the certification to LinkedIn and resumes
- Joining the global Art of Service alumni network
- Accessing advanced learning paths for deeper specialization
- Staying updated with AI and Dynamics 365 release notes
- Continuing your growth as an automation leader in your organization
- Understanding sentiment analysis models in AI Builder
- Extracting insights from customer emails and survey responses
- Classifying feedback as positive, neutral, or negative
- Automatically creating service cases for negative feedback
- Alerting managers when sentiment drops below thresholds
- Generating weekly insight reports using Power BI
- Linking sentiment data to customer profiles in Dynamics 365
- Using feedback trends to guide product or service improvements
- Setting up multilingual sentiment analysis
- Maintaining privacy and data handling compliance
Module 9: Building Custom AI Models - When to use custom vs. prebuilt AI models
- Defining objectives and success metrics for custom AI
- Data preparation strategies for model training
- Splitting data into training, validation, and test sets
- Uploading and tagging datasets securely
- Configuring model parameters and learning algorithms
- Monitoring training progress and convergence
- Interpreting model evaluation metrics: precision, recall, F1 score
- Optimizing models with hyperparameter tuning
- Exporting and reusing trained models across environments
Module 10: Automating Data Entry with Form Processing - Creating AI models to process structured forms
- Extracting data from PDFs, scanned images, and faxes
- Training models on multiple form templates
- Handling variations in layout and handwriting
- Validating extracted data against business rules
- Populating Dynamics 365 records with extracted fields
- Sending reconciliation reports to reviewers
- Reducing manual data entry by 90% or more
- Integrating with Microsoft Forms for digital submissions
- Using audit logs to track processing accuracy
Module 11: Intelligent Workflow Design Principles - Mapping business processes before automating
- Identifying bottlenecks and low-value manual tasks
- Designing workflows with user experience in mind
- Using decision trees to guide automation logic
- Incorporating human-in-the-loop approvals
- Designing fallback paths for errors and exceptions
- Ensuring workflows are maintainable and documentable
- Avoiding circular triggers and infinite loops
- Optimizing flow performance and execution time
- Documenting workflows for team collaboration
Module 12: Advanced Power Automate Techniques - Using parallel branches to improve efficiency
- Implementing loops for batch processing
- Working with arrays, JSON parsing, and data transformation
- Calling HTTP APIs from within flows
- Using scopes and run after conditions for error resilience
- Creating custom connectors for third-party systems
- Passing data between flows using inputs and outputs
- Using gateways for on-premises data integration
- Managing rate limits and throttling policies
- Logging workflow events for compliance and debugging
Module 13: Real-Time Automation and Notifications - Setting up instant notifications for critical events
- Sending email, Teams, and SMS alerts using Power Automate
- Using adaptive cards for interactive messages
- Triggering automations based on threshold breaches
- Creating real-time dashboards with live data updates
- Automatically escalating unacknowledged alerts
- Integrating with Microsoft Graph for calendar-based triggers
- Managing notification fatigue with smart routing
- Scheduling reminders for overdue tasks
- Monitoring alert effectiveness and user response rates
Module 14: Process Mining and Automation Opportunity Discovery - Using process mining to visualize actual workflows
- Identifying deviations from standard operating procedures
- Measuring task duration and handoff delays
- Spotting redundant or unnecessary steps
- Quantifying time and cost waste across processes
- Prioritizing automation candidates by impact and feasibility
- Validating assumptions with real usage data
- Tracking process improvement after automation rollout
- Using Celonis and Power BI integration for insights
- Presenting findings to leadership with compelling visuals
Module 15: Integration with Power Apps and Custom Interfaces - Embedding automation into custom Power Apps
- Calling Power Automate flows from canvas apps
- Passing app data to AI models for real-time decisions
- Displaying automation results within app screens
- Creating user-friendly forms for AI-assisted data entry
- Using Power Fx to enhance app logic alongside flows
- Building admin panels to monitor and manage flows
- Adding approvals and feedback loops within apps
- Offline data handling and sync strategies
- Ensuring consistent UX across automation touchpoints
Module 16: Monitoring, Governance, and Compliance - Setting up centralized flow monitoring with Power Platform Admin Center
- Reviewing usage metrics and active runs
- Identifying underused or redundant flows
- Managing flow ownership and delegation
- Enforcing naming conventions and documentation standards
- Implementing approval workflows for production deployments
- Using solution checker to validate best practices
- Handling data loss prevention and compliance policies
- Archiving and retiring obsolete automations
- Conducting quarterly review audits
Module 17: Scalable AI Automation Architecture - Designing reusable automation components
- Using solution layers to manage development, test, and production
- Creating environment-specific configurations
- Implementing centralized logging and error tracking
- Using Azure Logic Apps for high-scale scenarios
- Planning for high availability and disaster recovery
- Load testing automation performance under volume
- Optimizing for cost and resource efficiency
- Integrating with DevOps pipelines for CI/CD
- Documenting architecture decisions for future teams
Module 18: Change Management and User Adoption - Communicating automation benefits to end users
- Addressing fears of job displacement with empathy
- Providing training and support materials
- Creating feedback loops for continuous improvement
- Measuring user adoption rates and satisfaction
- Identifying super users to champion automation
- Running pilot programs before full rollout
- Gathering testimonials and success stories
- Linking automation KPIs to team performance goals
- Scaling adoption across departments
Module 19: Practical Implementation Projects - Project 1: Automate lead intake from email to Dynamics 365
- Project 2: Build an AI model to classify support requests
- Project 3: Create an end-to-end invoice processing automation
- Project 4: Design a predictive renewal risk dashboard
- Project 5: Implement sentiment analysis for customer surveys
- Project 6: Automate employee onboarding workflows
- Project 7: Set up real-time alerts for high-value opportunities
- Project 8: Process paper-based forms using AI and Power Automate
- Project 9: Integrate AI scoring into sales playbook recommendations
- Project 10: Build a cross-functional approval automation with Teams integration
Module 20: Certification Preparation and Next Steps - Reviewing key concepts from all modules
- Practicing scenario-based decision making
- Completing the final assessment with real-world challenges
- Understanding the structure of the Certificate of Completion exam
- Preparing documentation for your automation portfolio
- Adding the certification to LinkedIn and resumes
- Joining the global Art of Service alumni network
- Accessing advanced learning paths for deeper specialization
- Staying updated with AI and Dynamics 365 release notes
- Continuing your growth as an automation leader in your organization
- Creating AI models to process structured forms
- Extracting data from PDFs, scanned images, and faxes
- Training models on multiple form templates
- Handling variations in layout and handwriting
- Validating extracted data against business rules
- Populating Dynamics 365 records with extracted fields
- Sending reconciliation reports to reviewers
- Reducing manual data entry by 90% or more
- Integrating with Microsoft Forms for digital submissions
- Using audit logs to track processing accuracy
Module 11: Intelligent Workflow Design Principles - Mapping business processes before automating
- Identifying bottlenecks and low-value manual tasks
- Designing workflows with user experience in mind
- Using decision trees to guide automation logic
- Incorporating human-in-the-loop approvals
- Designing fallback paths for errors and exceptions
- Ensuring workflows are maintainable and documentable
- Avoiding circular triggers and infinite loops
- Optimizing flow performance and execution time
- Documenting workflows for team collaboration
Module 12: Advanced Power Automate Techniques - Using parallel branches to improve efficiency
- Implementing loops for batch processing
- Working with arrays, JSON parsing, and data transformation
- Calling HTTP APIs from within flows
- Using scopes and run after conditions for error resilience
- Creating custom connectors for third-party systems
- Passing data between flows using inputs and outputs
- Using gateways for on-premises data integration
- Managing rate limits and throttling policies
- Logging workflow events for compliance and debugging
Module 13: Real-Time Automation and Notifications - Setting up instant notifications for critical events
- Sending email, Teams, and SMS alerts using Power Automate
- Using adaptive cards for interactive messages
- Triggering automations based on threshold breaches
- Creating real-time dashboards with live data updates
- Automatically escalating unacknowledged alerts
- Integrating with Microsoft Graph for calendar-based triggers
- Managing notification fatigue with smart routing
- Scheduling reminders for overdue tasks
- Monitoring alert effectiveness and user response rates
Module 14: Process Mining and Automation Opportunity Discovery - Using process mining to visualize actual workflows
- Identifying deviations from standard operating procedures
- Measuring task duration and handoff delays
- Spotting redundant or unnecessary steps
- Quantifying time and cost waste across processes
- Prioritizing automation candidates by impact and feasibility
- Validating assumptions with real usage data
- Tracking process improvement after automation rollout
- Using Celonis and Power BI integration for insights
- Presenting findings to leadership with compelling visuals
Module 15: Integration with Power Apps and Custom Interfaces - Embedding automation into custom Power Apps
- Calling Power Automate flows from canvas apps
- Passing app data to AI models for real-time decisions
- Displaying automation results within app screens
- Creating user-friendly forms for AI-assisted data entry
- Using Power Fx to enhance app logic alongside flows
- Building admin panels to monitor and manage flows
- Adding approvals and feedback loops within apps
- Offline data handling and sync strategies
- Ensuring consistent UX across automation touchpoints
Module 16: Monitoring, Governance, and Compliance - Setting up centralized flow monitoring with Power Platform Admin Center
- Reviewing usage metrics and active runs
- Identifying underused or redundant flows
- Managing flow ownership and delegation
- Enforcing naming conventions and documentation standards
- Implementing approval workflows for production deployments
- Using solution checker to validate best practices
- Handling data loss prevention and compliance policies
- Archiving and retiring obsolete automations
- Conducting quarterly review audits
Module 17: Scalable AI Automation Architecture - Designing reusable automation components
- Using solution layers to manage development, test, and production
- Creating environment-specific configurations
- Implementing centralized logging and error tracking
- Using Azure Logic Apps for high-scale scenarios
- Planning for high availability and disaster recovery
- Load testing automation performance under volume
- Optimizing for cost and resource efficiency
- Integrating with DevOps pipelines for CI/CD
- Documenting architecture decisions for future teams
Module 18: Change Management and User Adoption - Communicating automation benefits to end users
- Addressing fears of job displacement with empathy
- Providing training and support materials
- Creating feedback loops for continuous improvement
- Measuring user adoption rates and satisfaction
- Identifying super users to champion automation
- Running pilot programs before full rollout
- Gathering testimonials and success stories
- Linking automation KPIs to team performance goals
- Scaling adoption across departments
Module 19: Practical Implementation Projects - Project 1: Automate lead intake from email to Dynamics 365
- Project 2: Build an AI model to classify support requests
- Project 3: Create an end-to-end invoice processing automation
- Project 4: Design a predictive renewal risk dashboard
- Project 5: Implement sentiment analysis for customer surveys
- Project 6: Automate employee onboarding workflows
- Project 7: Set up real-time alerts for high-value opportunities
- Project 8: Process paper-based forms using AI and Power Automate
- Project 9: Integrate AI scoring into sales playbook recommendations
- Project 10: Build a cross-functional approval automation with Teams integration
Module 20: Certification Preparation and Next Steps - Reviewing key concepts from all modules
- Practicing scenario-based decision making
- Completing the final assessment with real-world challenges
- Understanding the structure of the Certificate of Completion exam
- Preparing documentation for your automation portfolio
- Adding the certification to LinkedIn and resumes
- Joining the global Art of Service alumni network
- Accessing advanced learning paths for deeper specialization
- Staying updated with AI and Dynamics 365 release notes
- Continuing your growth as an automation leader in your organization
- Using parallel branches to improve efficiency
- Implementing loops for batch processing
- Working with arrays, JSON parsing, and data transformation
- Calling HTTP APIs from within flows
- Using scopes and run after conditions for error resilience
- Creating custom connectors for third-party systems
- Passing data between flows using inputs and outputs
- Using gateways for on-premises data integration
- Managing rate limits and throttling policies
- Logging workflow events for compliance and debugging
Module 13: Real-Time Automation and Notifications - Setting up instant notifications for critical events
- Sending email, Teams, and SMS alerts using Power Automate
- Using adaptive cards for interactive messages
- Triggering automations based on threshold breaches
- Creating real-time dashboards with live data updates
- Automatically escalating unacknowledged alerts
- Integrating with Microsoft Graph for calendar-based triggers
- Managing notification fatigue with smart routing
- Scheduling reminders for overdue tasks
- Monitoring alert effectiveness and user response rates
Module 14: Process Mining and Automation Opportunity Discovery - Using process mining to visualize actual workflows
- Identifying deviations from standard operating procedures
- Measuring task duration and handoff delays
- Spotting redundant or unnecessary steps
- Quantifying time and cost waste across processes
- Prioritizing automation candidates by impact and feasibility
- Validating assumptions with real usage data
- Tracking process improvement after automation rollout
- Using Celonis and Power BI integration for insights
- Presenting findings to leadership with compelling visuals
Module 15: Integration with Power Apps and Custom Interfaces - Embedding automation into custom Power Apps
- Calling Power Automate flows from canvas apps
- Passing app data to AI models for real-time decisions
- Displaying automation results within app screens
- Creating user-friendly forms for AI-assisted data entry
- Using Power Fx to enhance app logic alongside flows
- Building admin panels to monitor and manage flows
- Adding approvals and feedback loops within apps
- Offline data handling and sync strategies
- Ensuring consistent UX across automation touchpoints
Module 16: Monitoring, Governance, and Compliance - Setting up centralized flow monitoring with Power Platform Admin Center
- Reviewing usage metrics and active runs
- Identifying underused or redundant flows
- Managing flow ownership and delegation
- Enforcing naming conventions and documentation standards
- Implementing approval workflows for production deployments
- Using solution checker to validate best practices
- Handling data loss prevention and compliance policies
- Archiving and retiring obsolete automations
- Conducting quarterly review audits
Module 17: Scalable AI Automation Architecture - Designing reusable automation components
- Using solution layers to manage development, test, and production
- Creating environment-specific configurations
- Implementing centralized logging and error tracking
- Using Azure Logic Apps for high-scale scenarios
- Planning for high availability and disaster recovery
- Load testing automation performance under volume
- Optimizing for cost and resource efficiency
- Integrating with DevOps pipelines for CI/CD
- Documenting architecture decisions for future teams
Module 18: Change Management and User Adoption - Communicating automation benefits to end users
- Addressing fears of job displacement with empathy
- Providing training and support materials
- Creating feedback loops for continuous improvement
- Measuring user adoption rates and satisfaction
- Identifying super users to champion automation
- Running pilot programs before full rollout
- Gathering testimonials and success stories
- Linking automation KPIs to team performance goals
- Scaling adoption across departments
Module 19: Practical Implementation Projects - Project 1: Automate lead intake from email to Dynamics 365
- Project 2: Build an AI model to classify support requests
- Project 3: Create an end-to-end invoice processing automation
- Project 4: Design a predictive renewal risk dashboard
- Project 5: Implement sentiment analysis for customer surveys
- Project 6: Automate employee onboarding workflows
- Project 7: Set up real-time alerts for high-value opportunities
- Project 8: Process paper-based forms using AI and Power Automate
- Project 9: Integrate AI scoring into sales playbook recommendations
- Project 10: Build a cross-functional approval automation with Teams integration
Module 20: Certification Preparation and Next Steps - Reviewing key concepts from all modules
- Practicing scenario-based decision making
- Completing the final assessment with real-world challenges
- Understanding the structure of the Certificate of Completion exam
- Preparing documentation for your automation portfolio
- Adding the certification to LinkedIn and resumes
- Joining the global Art of Service alumni network
- Accessing advanced learning paths for deeper specialization
- Staying updated with AI and Dynamics 365 release notes
- Continuing your growth as an automation leader in your organization
- Using process mining to visualize actual workflows
- Identifying deviations from standard operating procedures
- Measuring task duration and handoff delays
- Spotting redundant or unnecessary steps
- Quantifying time and cost waste across processes
- Prioritizing automation candidates by impact and feasibility
- Validating assumptions with real usage data
- Tracking process improvement after automation rollout
- Using Celonis and Power BI integration for insights
- Presenting findings to leadership with compelling visuals
Module 15: Integration with Power Apps and Custom Interfaces - Embedding automation into custom Power Apps
- Calling Power Automate flows from canvas apps
- Passing app data to AI models for real-time decisions
- Displaying automation results within app screens
- Creating user-friendly forms for AI-assisted data entry
- Using Power Fx to enhance app logic alongside flows
- Building admin panels to monitor and manage flows
- Adding approvals and feedback loops within apps
- Offline data handling and sync strategies
- Ensuring consistent UX across automation touchpoints
Module 16: Monitoring, Governance, and Compliance - Setting up centralized flow monitoring with Power Platform Admin Center
- Reviewing usage metrics and active runs
- Identifying underused or redundant flows
- Managing flow ownership and delegation
- Enforcing naming conventions and documentation standards
- Implementing approval workflows for production deployments
- Using solution checker to validate best practices
- Handling data loss prevention and compliance policies
- Archiving and retiring obsolete automations
- Conducting quarterly review audits
Module 17: Scalable AI Automation Architecture - Designing reusable automation components
- Using solution layers to manage development, test, and production
- Creating environment-specific configurations
- Implementing centralized logging and error tracking
- Using Azure Logic Apps for high-scale scenarios
- Planning for high availability and disaster recovery
- Load testing automation performance under volume
- Optimizing for cost and resource efficiency
- Integrating with DevOps pipelines for CI/CD
- Documenting architecture decisions for future teams
Module 18: Change Management and User Adoption - Communicating automation benefits to end users
- Addressing fears of job displacement with empathy
- Providing training and support materials
- Creating feedback loops for continuous improvement
- Measuring user adoption rates and satisfaction
- Identifying super users to champion automation
- Running pilot programs before full rollout
- Gathering testimonials and success stories
- Linking automation KPIs to team performance goals
- Scaling adoption across departments
Module 19: Practical Implementation Projects - Project 1: Automate lead intake from email to Dynamics 365
- Project 2: Build an AI model to classify support requests
- Project 3: Create an end-to-end invoice processing automation
- Project 4: Design a predictive renewal risk dashboard
- Project 5: Implement sentiment analysis for customer surveys
- Project 6: Automate employee onboarding workflows
- Project 7: Set up real-time alerts for high-value opportunities
- Project 8: Process paper-based forms using AI and Power Automate
- Project 9: Integrate AI scoring into sales playbook recommendations
- Project 10: Build a cross-functional approval automation with Teams integration
Module 20: Certification Preparation and Next Steps - Reviewing key concepts from all modules
- Practicing scenario-based decision making
- Completing the final assessment with real-world challenges
- Understanding the structure of the Certificate of Completion exam
- Preparing documentation for your automation portfolio
- Adding the certification to LinkedIn and resumes
- Joining the global Art of Service alumni network
- Accessing advanced learning paths for deeper specialization
- Staying updated with AI and Dynamics 365 release notes
- Continuing your growth as an automation leader in your organization
- Setting up centralized flow monitoring with Power Platform Admin Center
- Reviewing usage metrics and active runs
- Identifying underused or redundant flows
- Managing flow ownership and delegation
- Enforcing naming conventions and documentation standards
- Implementing approval workflows for production deployments
- Using solution checker to validate best practices
- Handling data loss prevention and compliance policies
- Archiving and retiring obsolete automations
- Conducting quarterly review audits
Module 17: Scalable AI Automation Architecture - Designing reusable automation components
- Using solution layers to manage development, test, and production
- Creating environment-specific configurations
- Implementing centralized logging and error tracking
- Using Azure Logic Apps for high-scale scenarios
- Planning for high availability and disaster recovery
- Load testing automation performance under volume
- Optimizing for cost and resource efficiency
- Integrating with DevOps pipelines for CI/CD
- Documenting architecture decisions for future teams
Module 18: Change Management and User Adoption - Communicating automation benefits to end users
- Addressing fears of job displacement with empathy
- Providing training and support materials
- Creating feedback loops for continuous improvement
- Measuring user adoption rates and satisfaction
- Identifying super users to champion automation
- Running pilot programs before full rollout
- Gathering testimonials and success stories
- Linking automation KPIs to team performance goals
- Scaling adoption across departments
Module 19: Practical Implementation Projects - Project 1: Automate lead intake from email to Dynamics 365
- Project 2: Build an AI model to classify support requests
- Project 3: Create an end-to-end invoice processing automation
- Project 4: Design a predictive renewal risk dashboard
- Project 5: Implement sentiment analysis for customer surveys
- Project 6: Automate employee onboarding workflows
- Project 7: Set up real-time alerts for high-value opportunities
- Project 8: Process paper-based forms using AI and Power Automate
- Project 9: Integrate AI scoring into sales playbook recommendations
- Project 10: Build a cross-functional approval automation with Teams integration
Module 20: Certification Preparation and Next Steps - Reviewing key concepts from all modules
- Practicing scenario-based decision making
- Completing the final assessment with real-world challenges
- Understanding the structure of the Certificate of Completion exam
- Preparing documentation for your automation portfolio
- Adding the certification to LinkedIn and resumes
- Joining the global Art of Service alumni network
- Accessing advanced learning paths for deeper specialization
- Staying updated with AI and Dynamics 365 release notes
- Continuing your growth as an automation leader in your organization
- Communicating automation benefits to end users
- Addressing fears of job displacement with empathy
- Providing training and support materials
- Creating feedback loops for continuous improvement
- Measuring user adoption rates and satisfaction
- Identifying super users to champion automation
- Running pilot programs before full rollout
- Gathering testimonials and success stories
- Linking automation KPIs to team performance goals
- Scaling adoption across departments
Module 19: Practical Implementation Projects - Project 1: Automate lead intake from email to Dynamics 365
- Project 2: Build an AI model to classify support requests
- Project 3: Create an end-to-end invoice processing automation
- Project 4: Design a predictive renewal risk dashboard
- Project 5: Implement sentiment analysis for customer surveys
- Project 6: Automate employee onboarding workflows
- Project 7: Set up real-time alerts for high-value opportunities
- Project 8: Process paper-based forms using AI and Power Automate
- Project 9: Integrate AI scoring into sales playbook recommendations
- Project 10: Build a cross-functional approval automation with Teams integration
Module 20: Certification Preparation and Next Steps - Reviewing key concepts from all modules
- Practicing scenario-based decision making
- Completing the final assessment with real-world challenges
- Understanding the structure of the Certificate of Completion exam
- Preparing documentation for your automation portfolio
- Adding the certification to LinkedIn and resumes
- Joining the global Art of Service alumni network
- Accessing advanced learning paths for deeper specialization
- Staying updated with AI and Dynamics 365 release notes
- Continuing your growth as an automation leader in your organization
- Reviewing key concepts from all modules
- Practicing scenario-based decision making
- Completing the final assessment with real-world challenges
- Understanding the structure of the Certificate of Completion exam
- Preparing documentation for your automation portfolio
- Adding the certification to LinkedIn and resumes
- Joining the global Art of Service alumni network
- Accessing advanced learning paths for deeper specialization
- Staying updated with AI and Dynamics 365 release notes
- Continuing your growth as an automation leader in your organization