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Institute of Technology Sligo

Sensors for Autonomous Vehicles

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.

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.

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.

Duration

1 year part time online.

Number of credits

Careers or further progression

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.

Further enquiries

Shane Gilroy : gilroy.shane@itsligo.ie

Admissions Office
T: 353 (0) 71 931 8510
E: admissions@itsligo.ie

Subjects taught

Semester 1
Title Credits
Applied Linear Algebra 05
ADAS and Autonomous System Architecture 05
Environment Detection 05

Semester 2
Title Credits
Multiple View Geometry in Computer Vision 05
Automotive System Safety & Cybersecurity 05
Applied Statistics and Probability 05

Application date

Application Closing Date: 30th August 2019.

*New Common Points Scale
The new Leaving Certificate Common Points Scale from 2017 is not directly comparable with the scale that was in existence from 1992 to 2016.

Applicants should list their CAO course choices in genuine order of preference and they will be offered the course highest up on their list that they are deemed eligible for, if any.

Course fee

This programme is funded under the Springboard initiative. If you are unemployed, you may be entitled to free fees for this programme under this initiative. If this programme is funded you will find it and be able to submit an application on the Springboard site at www.springboardcourses.ie

Total: 4,500
Per 5 Credit Module: 750

Springboard Fees
Fee 4,000
Free for those classified as unemployed.
Fee for employed participants 400 (10% of fees).

Enrolment and start dates

Contact the college for the next start date.

Application Weblink

Course web page

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