Gracias por enviar su consulta! Uno de los miembros de nuestro equipo se pondrá en contacto con usted en breve.
Gracias por enviar su reserva! Uno de los miembros de nuestro equipo se pondrá en contacto con usted en breve.
Programa del Curso
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
Requerimientos
- 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 Horas
Testimonios (2)
¡Pensé que el entrenador era muy interesante y fue muy rápido para responder preguntas relacionadas con nuestro trabajo y realmente adaptó la enseñanza a nuestras necesidades y se esforzó al máximo para satisfacerlas! ¡No podría recomendar a Shaun lo suficiente!
Tom King - Complete Coherence
Curso - Microsoft Power Platform Fundamentals
Traducción Automática
es un tema nuevo para mi
