Skip to main content

Digitalisation of Business and Industry Processes - Professional Diploma

Gain the skills to help businesses achieve the benefits of digitalisation, including increased efficiency and greater business agility.

Key information

EU fees per year €5,250
NFQ Level NFQ Level 9 Minor
Duration One year
Attendance Part-time
Programme type Taught, Professional / Flexible
Delivery Blended
Start date September
Award Professional Diploma
Register your interest

Equip yourself to act as a “Digital Leader” within your organisation with UL’s Professional Diploma in Digitalisation of Business and Industry Processes. 

Learn to integrate systems, analyse critical data, and identify opportunities to add value through process digitalisation. 

Delivered via industry-led online lectures, tutorials, and practical modules this programme is suitable for business or engineering professionals seeking to drive digital transformation through AI, IoT, and data analytics.  

The programme and its assignments focus on the process of digitalisation in your organisation. This includes; Process Mapping, Digitalisation frameworks, Robotic Process Automation (RPA), cyber-physical systems and IoT, data analytics and machine learning. You will work on an applied research project where you can focus on an area of particular interest to you or your organisation. 

The programme has been developed in conjunction with an Industry Expert Working Group to meet the demand for process digitalisation and data analytics in business and industry. 

We need your consent to load this YouTube content

During this programme, you will

  • Explore how digital transformation reshapes businesses by embedding technology to boost efficiency, agility, and value creation for stakeholders.
  • Explore how to increase digitalisation of business processes, from design through to process execution.
  • Understand the concepts needed for system integration and process digitalisation such as Robotics Process Automation, Cyber-physical Systems and Internet of Things and Data Analysis. 
  • Gain skills to collect, clean, visualise and interpret data rooted in best data analysis practice. 
© 2026 University of Limerick