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Robotic Process Automation Course content

Duration Mode Structure
5 Days (40 Hours) Classroom or Online Classes + Lab Sessions + Quizzes / Assessments

Summary

Module # Topic Day1 Day2 Day3 Day4 Day5
Module 1 RPA Introduction
Module 2 UiPath Introduction
Module 3 UI Automation
Module 4 Programming and Data Manipulation
Module 5 Image and Text Automation (Citrix)
Module 6 Excel, PDF, Email Automation
Module 7 Orchestrator
Module 8 Cognitive Automation


Module 1 RPA Introduction
  • 1.RPA Introduction
    • What is RPA?
    • How RPA Works?
    • Processes Suitable for RPA
    • RPA Market Size and Growth
    • RPA Development Skills
  • 2.RPA and AI
    • AI Technologies and RPA
    • Digital Workforce
  • 3.RPA Benefits and Use Cases
    • Benefits of RPA
    • Digital Workforce
  • 4.RPA Products
    • RPA Products
    • Leadership Positions
    • Product Selection Criteria
Module 2 UiPath Introduction
  • 1.UiPath Introduction
    • UiPath Software
    • Studio.Robot.Orchestrator.UiExplorer
    • UiPath UI and Keyboard Shortcuts
    • Updating UiPath Studio
    • Chrome & Firefox Extensions
    • Connecting to a Source Control /li>
    • Enabling Tracing
  • 2.Workflows
    • Sequences
    • Flowcharts
    • State Machines
  • 3. Activities and Packages
    • Activities
    • Packages and Managing Packages
Module 3 UI Automation
  • 1.UI Elements
    • About UI Elements
    • UI Activities Properties
    • Input Methods
    • Output Methods (Screen Scraping)
    • Relative Scraping
  • 2.Selectors
    • About Selectors
    • Selectors with Wildcards
    • Full Versus Partial Selectors
    • UiPath Explorer
  • 3.Recording
    • Recording Types | Basic | Desktop | Web | Citrix |
    • Automatic Recording
    • Manual Recording
  • 4.UI Automation
    • Mouse. Keyboard. Find. Control.
  • 5.User Events
    • Element Triggers
    • Image Triggers
    • System Triggers
  • 6.Screen Scraping
    • Full Text
    • Visible Text
    • OCR
  • 7.Data Scraping
    • Structured Data / Tabular Data
    • Semi-Structured / Patterned Data
Module 4 Programming and Data Manipulation
  • 1.Data Types
    • Scalar
    • Arrays and Collections
    • User Defined, Libraries
  • 2.Variables
    • Managing Variables
    • Naming Best Practices
    • The Variables Panel
    • Types of Variables (GenericValue, o String, Boolean, Number, DateTime)
  • 3.Arguments
    • Managing Arguments
    • The Arguments Panel
    • Naming Best Practices
    • Using Arguments
  • 4.Namespaces
    • Importing Namespaces
  • 4.Namespaces
    • Importing Namespaces
  • 5.Control Flows
    • If | While | Do While | For-Each, Break, Continue | Switch
    • Assign | Delay
  • 6.Data Manipulation
    • Runtime Data Manipulation
  • 7.Error Handling
    • Try-Catch
  • 8.Debugging
    • Debugging a Workflow
Module 5 Image and Text Automation
  • 1.About Image and Text Automation
  • 2.Image and Text Automation (Citrix)
    • Mouse and Keyboard Activities
    • Text, OCR and Image Activities
Module 6 Excel, PDF, Email Automation
  • 1.Excel Automation
    • Excel App Integration vs Workbook
    • Excel Application Scope
    • Read, Write and Append Range
    • Read and Write Cell
    • Build Data Table
    • Read Row
  • 2.PDF Automation
    • Native and Image PDF
    • Extracting Large Text Data
    • Extracting Specific Elements
    • Find Element
    • Find Image
    • Find Relative Element
    • Scrape Relative
  • 3.Email Automation
    • Email as Input and Output
    • Email Protocols(SMTP, POP3, Outlook, IAMP, Exchange)
    • Mail Activities(Get, Send, Move, Delete)
    • Save Mail Message
Module 7 Orchestrator
  • 1.Orchestrator
    • Control Center
    • Dashboard
    • Provisioning and Deployment
    • Robots and Environments
    • Processes and Packages
    • Jobs and Schedules
    • Queues and Transactions
    • Assets, Alerts, Audit, Logs
    • Users and Roles
Module 8 Cognitive Automation
  • 1.AI and RPA
    • Building Digital Workforce
  • 2.Text Analysis
    • Natural Language Processing (NLP)
    • Google Text Analysis
  • 3.Language Translation
    • Google Text Translate
  • 4.Integrating ML
    • Calling ML Python Programs