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Schița de curs
Introduction to AI Builder and Low-Code AI
- AI Builder capabilities and common scenarios
- Licensing, governance, and tenant-level considerations
- Overview of the Power Platform integrations (Power Apps, Power Automate, Dataverse)
OCR and Form Processing: Structured and Unstructured Documents
- Differences between structured templates and free-form documents
- Preparing training data: labeling fields, sample diversity, and quality guidelines
- Building an AI Builder form processing model and evaluating extraction accuracy
- Post-processing extracted data: validation, normalization, and error handling
- Hands-on lab: OCR extraction from mixed form types and integration into a processing flow
Prediction Models: Classification and Regression
- Problem framing: qualitative (classification) vs quantitative (regression) tasks
- Feature preparation and handling missing data within Power Platform workflows
- Training, testing, and interpreting model metrics (accuracy, precision, recall, RMSE)
- Model explainability and fairness considerations in business use cases
- Hands-on lab: build a custom prediction model for churn/score or numeric forecast
Integration with Power Apps and Power Automate
- Embedding AI Builder models into canvas and model-driven apps
- Creating automated flows to process extracted data and trigger business actions
- Design patterns for scalable, maintainable AI-driven apps
- Hands-on lab: end-to-end scenario — document upload, OCR, prediction, and workflow automation
Complementary Process Mining Concepts (Optional)
- How Process Mining helps discover, analyze and improve processes using event logs
- Using Process Mining outputs to inform model features and automate improvement loops
- Practical example: combine Process Mining insights with AI Builder to reduce manual exceptions
Production Considerations, Governance, and Monitoring
- Data governance, privacy, and compliance when using AI Builder on sensitive documents
- Model lifecycle: retraining, versioning, and performance monitoring
- Operationalizing models with alerts, dashboards, and human-in-the-loop validation
Summary and Next Steps
Cerințe
- Experience with Power Apps, Power Automate, or Power Platform administration
- Familiarity with data concepts, basic ML ideas, and model evaluation
- Comfort working with datasets, Excel/CSV exports, and basic data cleansing
Audience
- Power Platform developers and solution architects
- Data analysts and process owners seeking automation through AI
- Business automation leads focused on document processing and prediction use cases
14 ore
Mărturii (2)
Am crezut că formatorul a fost foarte atrăgător și a fost foarte rapid în picioare pentru a răspunde la întrebări legate de munca noastră și a adaptat cu adevărat predarea la nevoile noastre și a mers mai sus și mai departe pentru a le satisface. Nu l-aș putea recomanda suficient pe Shaun!
Tom King - Complete Coherence
Curs - Microsoft Power Platform Fundamentals
Tradus de catre o masina
Într-adevăr, admir pacatele Instructorului față de toți cei care îl întrebau să repete ceva de 4-5 ori. Cred, de asemenea, că are o cunoștințe profundă despre subiectul acesta, dar, ca și s-a spus mai sus, nu am dedicat suficient timp acestui aspect. În plus, era bine să avem instruire practică, unde am putea să aplicăm în timp real ceea ce ne-am învățat, însă din nou, aș dori să știu mai multe despre PowerApps, nu despre SharePoint, deoarece sunt foarte familiarizat cu acesta. Dacă aș dori să învăț mai multe, probabil alegem o instruire pentru SharePoint, nu pentru PowerApps.
Patrycja - EY GDS
Curs - Microsoft Flow/Power Automate
Tradus de catre o masina
