Tell us what you'd like to learn

Takes under a minute. Our team will call or WhatsApp you with upcoming batch dates that suit your schedule.

About you
What are you interested in?
About this course · 40 hours

RPA with AI: learn to combine Blue Prism digital workers with artificial intelligence, so your automations can read documents, understand text, make judgement calls and handle work that fixed rules cannot. You build solid Blue Prism foundations first (objects, processes, work queues and Control Room), then bring AI into every stage: intelligent document processing, generative-AI services connected through web APIs for extracting, summarising and classifying information, and automations that hand uncertain cases to a person. Every module is hands-on, and the course ends with a capstone that delivers a complete AI-enabled automation, using RPA and AI together. Suitable for beginners, testers, analysts and developers moving into automation; no programming background is required.

Course content
  1. RPA with AI: the big picture
    • What RPA is, and how it differs from scripting
    • What AI adds to automation, and where rules are still the better choice
    • Blue Prism architecture: Control Room, Object Studio, Process Studio and System Manager
    • Digital workers, objects and processes
  2. Object Studio
    • Application Modeller and spying: Windows, browser and region modes
    • Actions, wait stages and reusable business objects
    • Object design standards
  3. Process Studio
    • Stages: data, decision, calculation, loop and collection
    • Pages, sub-processes, blocks and parameters
    • Building and testing a process
  4. Working with data
    • Collections and data items
    • Excel, text, date and number handling
    • Cleaning and standardising messy data with AI (names, addresses, categories)
    • Email and file automation
  5. Exception handling and recovery
    • Block, recover and resume
    • Exception types, retries and logging
    • Using AI to classify failures and summarise exceptions for a human
    • Designing for safe failure
  6. Work queues and Control Room
    • Queue design, item states and prioritisation
    • Adding AI steps to a work item: confidence checks, retries and a fall-back to a person
    • Scheduling, sessions and digital-worker management
    • Credentials, environment variables and monitoring
  7. Web services and APIs
    • Web API services: REST and SOAP
    • Authentication and handling JSON responses
    • Connecting AI services to your processes
  8. AI + RPA: intelligent document processing
    • Digitising documents, classifying them and extracting fields (for example with Blue Prism Decipher IDP)
    • Human validation of low-confidence results
    • Measuring accuracy and straight-through rates
  9. AI + RPA: generative AI in workflows
    • Calling language-model services through web APIs
    • Writing prompts for extraction, summarising, classification and drafting replies
    • Turning model answers into structured data
    • Guardrails: accuracy checks, privacy and cost control
  10. AI + RPA: deciding and acting
    • Letting an AI decide, and a digital worker act: designing the hand-off
    • Human approval steps and fall-back paths
    • Monitoring and auditing AI decisions
  11. Governance and best practice
    • Design standards, versioning and release management
    • Security, audit and governing AI use
    • Operating a digital workforce
  12. Capstone project
    • Build, test and present an AI-enabled automation from request to deployment, using RPA and AI together
Weekday = Mon–Fri · Weekend = Sat/Sun