Intelligent automation (IA) is a combination of technologies such as RPA (automation of routine tasks), artificial intelligence (AI/ML), and intelligent document processing (IDP), whose goal is to increase efficiency, reduce errors, and accelerate business processes.
This training is designed to provide a basic understanding of intelligent automation and its components. Participants will learn how to recognize processes suitable for automation, learn about basic IA technologies (RPA, AI, IDP, NLP, Process Mining), and gain practical insight into what it's like to work with IA tools like UiPath. Special focus is placed on evaluating the value of IA in different business functions, as well as on the criteria that determine whether a process is suitable for automation. Attendees will have the opportunity to see through mini-cases and live demonstrations how IA works in practice - without the need for coding. The training combines theory and practice and is an excellent introduction to the world of automation and digital process transformation.
The training is intended for everyone who wants to gain a basic understanding of IA technologies - from operational workers to management, regardless of the sector in which they work and regardless of previous technical knowledge.
01 Introduction to Intelligent Automation and process understanding
What is IA: A combination of RPA + AI + IDP
Key benefits: speed, scalability, error reduction, 24/7 availability
Where IA brings value: finance, logistics, HR, customer support
What are business processes?
Difference Between Functions and Processes
Basic characteristics of the process
The importance of mapping and analysis
02 How to Identify Processes for Automation (IA Perspective)
Criteria: repetitiveness, structure, volume, stability
Process prioritization matrix (complexity vs benefit)
Guidelines for "quick wins" and strategic IA initiatives
Mini-case: identifying IA potential through examples
03 An overview of the key components of IA
RPA - Automation of routine, rule-based tasks
AI / ML – Learning from data, decision making and prediction
IDP - Recognition and processing of data from documents
NLP - Language understanding and processing (text, email)
Process & Task Mining - Analysis of activities and data
04 Hands-on demonstration of IA tools and discussion
View work in a tool (eg UiPath StudioX, Document Understanding)
Task automation (PDF reading, email entry, data entry)
Focus on work logic - no coding
Q&A and discussion on IA expansion opportunities
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