Content, progress and pedagogy of the
The module adds to the knowledge obtained in 1st
- Have gained knowledge and experience of how to develop
autonomous solution with advanced sensing, big data, machine
learning, vision and perception technologies.
- Have gained knowledge and experience of how to design
intelligent autonomous systems and networks with related concepts,
theories, methods and tools, based on demand characteristics in
different industry/business contexts.
- Have gained knowledge and experience of how to evaluate the
performance of intelligent autonomous systems and networks in a
dynamic application/commercial environment.
- Be able to analyse the system demand in a real case and specify
- Be able to develop an intelligent autonomous solution with
related technologies, aiming to meet the identified demands.
- Be able to conduct a cost and benefit analysis for the proposed
solution to justify economic feasibility.
- Be able to comprehensively evaluate the performance of
intelligent autonomous systems and networks in a dynamic
- Have the ability to interpret the differences of intelligent
autonomous solutions compared with conventional ones in a specific
context, e.g. autonomous robots, production or transportation
- Have the ability to formulate a project to target and solve an
intelligent autonomous solution in a real case, as well as planning
and conducting such a project with team work.
- Have the ability to estimate and assess the achievement of
logistic and economic objectives in intelligent autonomous
solutions in a specific context.
- Have the ability to analyse the limitations, opportunities, and
the survivability of an intelligent autonomous system/network
against more complex and contested environments.
Type of instruction
The module is carried out as group-based, problem-oriented
project work. The group work is carried out as an independent
work process in which the students themselves organise and
coordinate their workload in collaboration with a supervisor. The
project is carried out in groups with normally no more than 6
Extent and expected workload
Since it is a 15 ECTS project module the expected
workload is 450 hours for the student.
|Name of exam||Intelligent Autonomous Systems|
|Type of exam|
Oral exam based on a project
|Assessment||7-point grading scale|
|Type of grading||External examination|
|Criteria of assessment||The criteria of assessment are stated in the Examination
Policies and Procedures|