Sensors for Autonomous Vehicles - Sligo

Course Overview

This Postgraduate Certificate specialises in Environment Detection and Computer Vision for Advanced Driver Assistance Systems, the underlaying technology of smart and autonomous vehicles. This part-time programme brings together interdisciplinary concepts to provide engineers with the skills required to contribute to the development of the next generation of automotive technology.



This NFQ Level 9, 30 ECTS Credits Postgraduate Certificate has been developed in collaboration with industry and is aimed at Electronic, Computer, Mechanical and Mechatronic Engineers who wish to develop the skills required to design the next generation of technology for smart and autonomous vehicles.



The programme will run over one year part time with 30 credits of taught modules primarily delivered online with some on-campus workshops.



Who Should Apply?

This course is aimed at Electronic, Computer, Mechanical and Mechatronic Engineers who wish to develop the skills required to design the next generation of technology for smart and autonomous vehicles.

Semester Module Details Credits Mandatory / Elective

1 Applied Linear Algebra 05 Mandatory

1 ADAS and Autonomous System Architecture 05 Mandatory

1 Environment Detection 05 Mandatory

2 Multiple View Geometry in Computer Vision 05 Mandatory

2 Automotive System Safety & Cybersecurity 05 Mandatory

2 Applied Statistics and Probability 05 Mandatory

Graduates with a Level 8 Honours Degree 2:1 or above in Electronic Engineering, Mechatronic Engineering, Mechanical Engineering, Computer Science or a related discipline are eligible to apply for this programme. Programming knowledge (Ideally C++) and Level 8 Engineering Maths are pre-requisites to the course. Applicants who do not meet these criteria but have the willingness to address them will be considered.



Candidate interviews and entrance exams will be used to assess suitability for the programme. Graduates who have not obtained this minimum may incorporate other equivalent qualifications and relevant work experience and apply for assessment via the Recognition of Prior Learning (RPL) process. RPL is a process that may allow you to gain admission to a programme or to receive exemptions/ credit for some parts of the programme based on demonstrated learning that you may have achieved through another programme of study or through your work or career. Further information is available at www.atu.ie/recognition-of-prior-learning which our dedicated RPL portal.



In addition, international students, whose first language is not English, will be required to prove their English competency through previous examination results, recognized English language tests such as IELTS (6.5 or equivalent required) and through oral communication skills at interview.

Application Closing Date 14th August 2026

1 year part-time, online.



Recommended Study Hours per week

For part-time online or blended learning, it is recommended that you should try to allow for 5-6 hours per week per 5 credit module.



On-Campus Attendance Requirement

This programme is primarily delivered online with attendance required for some on-campus workshops.

Start Date: September 2026

Careers

Upon completion students will be eligible to pursue a Postgraduate Diploma or Master of Engineering in Connected and Autonomous Vehicles. Students will find employment in Senior Design Positions in Electronic, Mechanical, Mechatronics and Embedded Systems engineering for highly regulated industries.



Although primarily directed at the automotive sector, many of the skills such as Machine Learning, Pattern Detection and Computer Vision are highly sought after for R&D roles in other industries such as the medical, agricultural and high-volume manufacturing industries.