Course Outline
Introduction to AI Builder and Low-Code AI
- AI Builder capabilities and typical business scenarios
- Licensing, governance, and tenant-level considerations
- Overview of integrations with the Power Platform (Power Apps, Power Automate, Dataverse)
OCR and Form Processing: Structured and Unstructured Documents
- Distinguishing between structured templates and free-form documents
- Preparing training data: field labelling, sample variety, and quality standards
- Constructing an AI Builder form processing model and assessing extraction accuracy
- Post-processing extracted data: validation, normalisation, and error management
- Practical lab: performing OCR extraction from mixed form types and integrating it into a processing flow
Prediction Models: Classification and Regression
- Defining the problem: qualitative (classification) versus quantitative (regression) tasks
- Feature preparation and managing missing data within Power Platform workflows
- Training, testing, and interpreting model metrics (accuracy, precision, recall, RMSE)
- Practical lab: building a custom prediction model for churn/scoring or numerical forecasting
Integration with Power Apps and Power Automate
- Embedding AI Builder models into canvas and model-driven apps
- Practical lab: a complete end-to-end scenario covering document upload, OCR, prediction, and workflow automation
Complementary Process Mining Concepts (Optional)
- How Process Mining aids in discovering, analysing, and improving processes using event logs
- Utilising Process Mining outputs to guide model features and automate improvement cycles
- Practical example: combining Process Mining insights with AI Builder to minimise manual exceptions
Production Considerations, Governance, and Monitoring
- Data governance, privacy, and compliance when using AI Builder on sensitive documents
- Operationalising models through alerts, dashboards, and human-in-the-loop validation
Summary and Next Steps
Requirements
- Practical experience with Power Apps, Power Automate, or Power Platform administration
- Proficiency with datasets, Excel/CSV exports, and fundamental data cleaning
Target Audience
- Power Platform developers and solution architects
- Data analysts and process owners looking to leverage AI for automation
- Business automation leads prioritising document processing and forecasting use cases
Testimonials (3)
Practical and hands on labs on report developmemt using Power BI The labs were excellent and the trainer offered very good hands on sessions
Sinzala Sichaanji - Bank of Zambia
Course - Mastering Power Platform: Power Apps, Power Automate, DataVerse, Power BI, and Power Virtual Agents
We did quite complex examples, so we could get a feeling of how the real work with Power Automate Desktop can look like in the real world scenario.
Michal Strnad - MicroNova AG
Course - Microsoft Flow/Power Automate
Dynamic, adaptive, and informative
