Course Code
SG_ESENS_E09
Zone
Attendance
Part time

Course Summary

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.

College Link

ATU Sligo
College Link > SG_ESENS_E09 - Sensors for Autonomous Vehicles - Sligo

Colleges often have information about the course on their own website, along with other useful information relating to the college. (Note: Not always available)

Career Sectors

This course prepares you for working in the Career Sectors below. Follow the links to get a fuller understanding of the sectors you are preparing for.

Entry Requirements

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 Details

This course has closed for applications for September 2026.

Flexible learning courses are popular, and they fill on a first come, first served basis. There are two major intake periods throughout the academic year, September and January.

For January start courses, applications typically open in October, and for September start courses, applications typically open in February. Closing dates for applications are listed on the individual course webpage.

Start Date: September 2026.

The Student

Career Interests

This course is typically suited for people with the following Career Interests. If these interests do not describe you, this course may prepare you for work you may not find satisfying.

Realist

Realists are usually interested in 'things' - such as buildings, mechanics, equipment, tools, electronics etc. Their primary focus is dealing with these - as in building, fixing, operating or designing them. Involvement in these areas leads to high manual skills, or a fine aptitude for practical design - as found in the various forms of engineering.

Realists like to find practical solutions to problems using tools, technology and skilled work. Realists usually prefer to be active in their work environment, often do most of their work alone, and enjoy taking decisive action with a minimum amount of discussion and paperwork.


Investigative

The Investigative person will usually find a particular area of science to be of interest. They are inclined toward intellectual and analytical activities and enjoy observation and theory. They may prefer thought to action, and enjoy the challenge of solving problems with sophiscticated technology. These types prefer mentally stimulating environments and often pay close attention to developments in their chosen field.


Career Progression

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.

Duration

1 year part-time, online delivery.

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.
Close