This Masters Degree specialises in the design and development of Advanced Driver Assistance Systems, the underlaying technology of smart and autonomous vehicles. This part-time programme brings together interdisciplinary concepts such as computer vision, artificial intelligence, vehicle dynamics and advanced sensor systems to provide current engineers with the skills required to design the next generation of automotive technology.
This NFQ Level 9, 90 ECTS Credits Masters Degree 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 two years part time with 60 credits of taught modules primarily delivered online with some on-campus workshops. This will be followed by a 30-credit industrial research project in the field of Advanced Driver Assistance Systems.
Key Course Information
Study hours: Whether you are studying part-time online, blended or full-time online, it is very important that you allocate enough study time to your online course to stay focused, reduce stress and achieve your goals. 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 to your studies.
Live Lectures: Live lectures normally take place between 6pm and 10pm, Monday to Thursday but this may vary depending on the availability of specific lecturers. If the Live Classroom scheduled times for the live online lectures do not suit you, recordings will be made available through Moodle.
Application Closing Date : 18th August 2023
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, C++ or Python) 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.
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.
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.
|Academic Year 2023/24 Fees||
Total Programme Fees:
Fees per annum:
To help make the payment of fees more manageable for students who are self-funding their studies, tuition fees can be paid through payment instalment plans at ATU Sligo. For further information on instalment plans, please visit our Fees and Funding webpage.
If you apply and are approved for an online course at ATU Sligo, you will be required to pay a non-refundable deposit of €250 to secure your place. Your deposit will then be credited against the course fees once you are registered as a student. Students at ATU Sligo are also eligible to claim tax relief at the standard rate for tuition fees.
For further information and guidance about Fees and Funding for online and part-time courses at ATU Sligo, click here.
If you are seeking to take your exams online, and you meet the eligibility criteria (overseas students and those with extenuating circumstances), an additional examinations fee will apply. For further information, please visit our Examinations webpage.
|Applied Linear Algebra||05|
|ADAS and Autonomous System Architecture||05|
|Multiple View Geometry in Computer Vision||05|
|Automotive System Safety & Cybersecurity||05|
|Applied Statistics and Probability||05|
|Vehicle Dynamics and Control||05|
|Modelling, Simulation and Test Methods for Advanced Driver Assistance Systems||05|
|MEng CAV Research Dissertation||30|