Engineering - Connected & Autonomous Vehicles - Sligo
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.
Applied Linear Algebra 05
ADAS and Autonomous System Architecture 05
Environment Detection 05
Multiple View Geometry in Computer Vision 05
Automotive System Safety & Cybersecurity 05
Applied Statistics and Probability 05
Research Methods 05
Machine Learning 05
Vehicle Dynamics and Control 05
Modelling, Simulation and Test Methods for Advanced Driver Assistance Systems 05
Connected Vehicles 05
Sensor Fusion 05
MEng CAV Research Dissertation 30
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.
Applications for online programmes are accepted on the atu sligo website.
All programmes advertised will run subject to sufficient student numbers.
ATU sligo online has two intakes per year, the main one being in September with a smaller listing of programmes for January. For confirmation on start dates check www.itsligo.ie/online
For September, applications open from 1st February each year. Closing date for receipt of applications is 31st august.
For January, applications open from 1st November each year. Closing date for applications is mid-January.
The online application form requires personal details, previous qualifications, professional accreditations, employment history and a personal statement. We recommend collating all the necessary paperwork i.e. Transcripts of previous qualifications, academic certificates before you submit an application.
Once submitted, our admissions team will contact you to confirm eligibility and request copies of any previous qualifications.
Academic staff review every application and approve eligible candidates for the programme.
Admissions team will notify you if you are accepted onto the course and will request deposit to confirm your place.
Places are limited, so please apply early.
2.5 years part-time, online.
Total cost of the MEng in Connected and Autonomous Vehicles is €11,000
Contact the college for the next start date.
Post Course Info
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.