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Course Outline
UiPath IPA Architecture & Environment Setup
- RPA vs. IPA: When to use traditional automation vs. AI-driven workflows
- UiPath ecosystem overview: Studio, Orchestrator, Robot, AI Center, Document Understanding
- Installing UiPath Community Edition & validating runtime environment
- Workflow foundations: Sequences, State Machines, Flowcharts, and .NET/C#/VB integration points
- Lab 1: Environment provisioning, connecting Studio to Orchestrator, and deploying a baseline automation
Computer Vision for Robust UI Automation
- Limitations of traditional selectors & the role of Computer Vision
- UiPath Computer Vision engine: image matching, fuzzy matching, and resolution-independent automation
- Handling dynamic, virtualized, or API-restricted interfaces
- Fallback strategies & error recovery for CV-based interactions
- Lab 2: Build a CV-driven workflow to locate, verify, and interact with non-intrusive screen elements across multiple UI states
AI-Powered Text Processing & Sentiment Analysis
- Integrating AI into RPA: Architecture & data flow considerations
- UiPath’s built-in NLP & language pattern detection activities
- Performing sentiment analysis on unstructured content (emails, reviews, chat logs, documents)
- Connecting external AI services (Azure Cognitive Services, AWS Comprehend, or custom APIs)
- Lab 3: Process a batch of unstructured text, extract key language patterns, and output sentiment scores into structured formats
Multi-Robot Orchestration & Enterprise Management
- Orchestrator deep dive: Environments, Queues, Assets, Users, & Security Roles
- Robot types: Attended, Unattended, & Hybrid configurations
- Enabling robots to manage other robots: Queue-driven work distribution, dynamic scaling, & supervisor patterns
- Monitoring, logging, exception handling, & audit trails at scale
- Lab 4: Configure Orchestrator, deploy a multi-robot queue system, and validate cross-robot task distribution & error routing
End-to-End IPA Design & Production Readiness
- Architecting an IPA solution: Data ingestion → AI processing → RPA execution → output routing
- Optimizing performance: CV tuning, queue prioritization, retry logic, & memory management
- Security & compliance: credential management, data masking, & enterprise governance
- Transitioning from training to production: deployment pipelines, version control, & maintenance strategies
- Capstone: Build & deploy a complete IPA workflow combining Computer Vision, AI/NLP, multi-robot orchestration, and scheduled execution
Q&A, Customization & Advanced Pathways
- Review of key IPA patterns & troubleshooting common pitfalls
- Advanced paths: Process Mining, Automation Hub, .NET library interop, & API-first automation
- Enterprise licensing pathways vs. Community Edition limitations
- Open Q&A and personalized implementation guidance
- Customization Options: Available for domain-specific datasets, proprietary UI automation, or hybrid cloud/on-prem deployment
To request a customized training schedule or enterprise-grade delivery, please contact our solutions team.
Requirements
- Basic programming experience in .NET, C#, VB, or a similar Object-Oriented Programming (OOP)/scripting language.
- Familiarity with basic automation concepts is beneficial but not required.
Audience
- Software Developers & Automation Engineers
- Business Intelligence Professionals with technical expertise
- Digital Marketing Professionals with technical expertise
- IT/Operations Leads looking to extend legacy RPA with AI capabilities
14 Hours
Testimonials (4)
Individualized attention to our questions and problems.
Marcel Furrer - HOCH Health Ostschweiz
Course - UiPath: Deploying a Robotic Workforce
Machine Translated
the template provided. they will come in handy on my day to day duties
Lineo Nchaba - Revenue Services Lesotho
Course - UiPath for Business Analysts
He is very competent, organized, and he loves his job.
Limpho - Revenue Services Lesotho
Course - UiPath Automation Solution Architect
Individual support