Module Code: H9IAPI
Long Title Intelligent Agents and Process Automation
Title Intelligent Agents and Process Automation
Module Level: LEVEL 9
EQF Level: 7
EHEA Level: Second Cycle
Credits: 5
Module Coordinator: Rejwanul Haque
Module Author: Shauni Hegarty
Departments: School of Computing
Specifications of the qualifications and experience required of staff

PhD/Master’s degree in a computing or cognate discipline. May have industry experience also. 

Learning Outcomes
On successful completion of this module the learner will be able to:
# Learning Outcome Description
LO1 Demonstrate expert knowledge of the theory and concepts underpinning intelligent agents and business process management.
LO2 Determine, design, and document business processes.
LO3 Critically analyse the capabilities and limitations of intelligent agents into business process automation.
LO4 Evaluate and apply principles of intelligent agents to implement automated processes in various real-world business scenarios.
Module Recommendations

This is prior learning (or a practical skill) that is required before enrolment on this module. While the prior learning is expressed as named NCI module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).

No recommendations listed
Co-requisite Modules
No Co-requisite modules listed
Entry requirements

Applicants are required to hold a minimum of a Level 8 honours qualification (2.2 or higher) or equivalent on the National Qualifications Framework in either STEM (e.g., Information Management Systems, Information Technologies, Computer Science, Computer Engineer) or Business (e.g., Business Information Systems, Business Administration, Economics) discipline and a minimum of three years of relevant work experience in industry, ideally but not necessarily, in management. Previous numerical and computer proficiencies should be part of their work experience or formal training. Graduates from disciplines which do not have technical or mathematical problem-solving skills embedded in their programme will need to be able to demonstrate technical or mathematical problem-solving skills in addition to their level 8 programme qualifications (Certifications, Additional Qualifications, Certified Experience and Assessment Tests). All applicants for the programme must provide evidence that they have prior Mathematics and Computing module experience (e.g., via academic transcripts or recognised certification) as demonstrated in one mathematics/statistics module and one computing module or statement of purpose must specify numerical and computing work experience. 

NCI also operates a prior experiential learning policy where graduates with lower, or no formal qualifications, currently working in a relevant field, may be considered for the programme. 

Applicants must also be able to have their own laptop with the minimum required specification that will be communicated to each applicant through both the admissions and marketing departments. 


Module Content & Assessment

Indicative Content
Understanding Business Processes
Processes Everywhere; Ingredients of a Business Process; Business Process Management Lifecycle;
Identifying Business Processes
Context of Process Identification; Definition of a Process Architecture; Process Selection
Business Process Modelling I
Process Decomposition; Introduction to BPM
Business Process Modelling II
Branching and Merging; Handling Events; Handling Exceptions
Identifying Automation Processes
Identifying Types of Automation; What to Automate?; Identify Process Requirements; Identify Benefits of Automation
Designing Automation Processes
Understanding the Process Definition Document; Object Model Diagram
Foundations of Robotic Process Automation (RPA)
What is RPA?; Why RPA?; Advantages and Disadvantages of RPA; RPA compared with BPMN; RPA Tools
Intelligent Agents
What are (intelligent) agent?; The basic properties of agents; To use agents or not; Abstract agent architecture
Simple Agents
Reflex Agents; Goal Oriented Agents; Utility Function; Rational Agents
Knowledge Agents
Planning; BDI Architecture; Reasoning and Belie
Learning Agents
Pre-trained Networks; Evaluation Functions; Reinforcement Learning
RPA Deployment and Testing
Testing; Going into Production; Monitoring; Security; Scaling
Assessment Breakdown%


Full Time

Assessment Type: Formative Assessment % of total: Non-Marked
Assessment Date: n/a Outcome addressed: 1,2,3,4
Non-Marked: Yes
Assessment Description:
Formative assessment will be provided on the in-class individual or group activities. Feedback will be provided in written or oral format, or on-line through Moodle. In addition, in class discussions will be undertaken as part of the practical approach to learning.
Assessment Type: Project % of total: 100
Assessment Date: n/a Outcome addressed: 1,2,3,4
Non-Marked: No
Assessment Description:
Learners will provide a detailed description of one business process of their choice. Learners will have to (1) determine and justify using principles of intelligent agents that this business process can be automated; (2) model the business process using BPMN; (3) describe the process using the Process Definition Document (PDD); (4) implement the process in a RPA tool; and (5) discuss the advantages and disadvantages of the proposed implementation.
No End of Module Assessment
No Workplace Assessment
Reassessment Requirement
Coursework Only
This module is reassessed solely on the basis of re-submitted coursework. There is no repeat written examination.

NCIRL reserves the right to alter the nature and timings of assessment


Module Workload

Module Target Workload Hours 0 Hours

Module Resources

Recommended Book Resources
  • Marlon Dumas,Marcello La Rosa,Jan Mendling,Hajo A. Reijers. (2019), Fundamentals of Business Process Management, Springer, p.527, [ISBN: 978-3662585856].
  • Tom Taulli. (2020), The Robotic Process Automation Handbook, Apress, p.344, [ISBN: 978-1484257289].
  • Stuart Russell,Peter Norvig. (2019), Artificial Intelligence, Pearson Higher Education, p.1136, [ISBN: 978-0134610993].
  • Nandan Mullakara,Arun Kumar Asokan. (2020), Robotic Process Automation Projects, [ISBN: 978-1839217357].
Supplementary Book Resources
  • Elijah Falode. (2020), The Future of Intelligent Automation, [ISBN: 979-8642979969].
  • Husan Mahey. (2020), Robotic Process Automation with Automation Anywhere, [ISBN: 978-1839215650].
  • Walter Surdak. (2020), The Care and Feeding of Bots, [ISBN: 979-8610003634].
  • Olivier Boissier,Rafael H. Bordini,Jomi Hubner,Alessandro Ricci. (2020), Multi-Agent Oriented Programming, MIT Press, p.264, [ISBN: 978-0262044578].
This module does not have any article/paper resources
This module does not have any other resources
Discussion Note: