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Key Info

  • Course CodeCR_KARIN_9
  • Field of StudyComputing,Computer Science
  • Type of CourseMasters Degree
  • Type of QualificationMaster of Science
  • Type of Study Part time Online
  • Application Closing Date10th September 2020
  • DurationFull time: One Academic Year. Online: 24 months
  • Level9
  • LocationCIT Bishopstown Campus

 

PDF Brochure >>

 

This programme will run subject to sufficient student numbers. Where a programme cannot proceed, applicants will be contacted and advised on alternative study options.

An Information session will take place early September 2020 from 5.30pm to 7.00pm at the CIT Bishopstown Campus (date to be confirmed). Institute staff will be in attendance to offer career guidance and assistance.

Students should note that Fees quoted relate to the academic year 2019-2020 only and are subject to change on an annual basis. Except where stated, course fees cover the cost of tuition only.

Course fees must be paid before attending lectures.

For more information on Fees, please visit fees/students

 

Course Fee
  • Full-time Mode of Study: EU Students: €6,500*
    Per semester fee instalments are possible, please contact the CIT Fees Office (fees@cit.ie) if this is your preferred payment option.
  • Online Mode of Study: €7,500 in total.
    Three instalments of €2,500 are possible, please contact the CIT Fees Office (fees@cit.ie) if this is your preferred payment option.
  • Non-EU Students: Please click here for information

*Union of Students in Ireland (USI) Levy
The USI membership levy of €7.00 has been introduced as a result of a referendum where students opted to affiliate to the national Students’ Union. This levy must be paid before the start of Semester 1.


Course duration

Two separate deliveries of this programme are offered; full-time on-campus by day and part-time online by night. ​


Full-time:

  • 1 academic year (2 semesters, September to June)
  • No. of weeks per semester: 13
  • No. of timetable hours/week: 18
  • Which days: Monday – Friday

Online:
This is a two-year part-time programme taught over 24 months (4 semesters). The programme is delivered and accessed fully online using state of the art Cloud based technologies. Lectures are delivered online by night, streamed live over the Internet and recorded to facilitate easy playback to students. This offers great flexibility for students who can access lectures and labs anytime, anywhere on any device that has a web browser.

 

Overview

Artificial intelligence (AI) is a field of computer science that enables computers and machines to perform tasks normally requiring human intelligence. Its many applications range from chess-playing robots and autonomous cars to speech, image, and language processing, robotic manufacturing, and surveillance systems. In the twenty-first century, AI has experienced a resurgence following concurrent advances in computer power, large amounts of data, and theoretical understanding. AI techniques have now become an essential part of the technology industry, helping to solve many challenging problems in computer science.

 

This master’s programme provides a technical deep-dive into the area of AI. It aims to produce AI engineers with a highly relevant skillset in AI topics. Students will learn how to use and develop intelligent computer systems that can learn from experience, recognise patterns in vast amounts of data and reason strategically in complex decision-making situations. The programme content will deliver a comprehensive range of topics integral to the study of AI. These include machine learning, deep learning, natural language processing, optimisation, and big data processing to name but a few.

 

The programme contains challenging and interesting modules delivered by lecturers who are experts in AI. Students will be presented with opportunities to work on industry focused projects and research opportunities linked to the domain expertise of each lecturer. Staff in the Department of Computer Science have built an excellent national and international record in the application of AI and Machine Learning research in sectors ranging from renewable energy to life science. Research funding has been provided by Science Foundation Ireland, Enterprise Ireland, Irish Research Council, Health Research Board, and the European Commission.


ECTS Credits: 60


Award: Master of Science in Information Security (Level 9 on the National Framework of Qualifications).

Further Information >>

 

 

Entry to the MSc in Artificial Intelligence will require a minimum of a Level 8 honours degree in Computer Science, Engineering, Computing or an honours degree in a cognate discipline. As this is an expert level programme, it is essential for applicants to have a strong proficiency in mathematics, including statistics, and an advanced level of coding competency in a modern highlevel computer programming language such as Python or Java.

 

Applicants who do not meet the above criteria will be considered on a case by case basis. Please see the Recognition of Prior Learning (RPL) page or visit www.cit.ie/rpl for further details.

 

  • Online application is open for course (online delivery) commencing 11th September 2020.

  • Please note that applicants will be required to pay an acceptance fee of €500 online if a place on a course is offered. This fee is deductible from the overall course fee.

  • Note: You will not be charged for applying for the programme by clicking the 'apply now' button, you are only asked to pay an acceptance fee if a place is offered to you and you wish to accept it.

  • Please attach and upload any documents such as transcripts, CV, other details relevant to the application.

  • Delivery of this programme is subject to sufficient number of applicants. Eligible candidates will be considered on a first come first served basis.

     

Online Delivery

Apply Online >>

 

 

All modules are worth 5 credits (ECTS) unless otherwise noted.

 

Semester 1 (Autumn)

Type

Credits

Practical Machine Learning Mandatory 5
Knowledge Representation Mandatory 5
Metaheuristic Optimisation Mandatory 5
Big Data Processing Mandatory 5
Research Practice & Ethics Mandatory 5
Natural Language Processing Elective 5
Recommender Systems Elective 5
AI for Sustainability Elective 5
Computer Simulation & Analysis Elective 5
Free Choice Module Elective 5

 

 

 

Semester 2 (Spring)

Type

Credits

Deep Learning Mandatory 5
Decision Analytics Mandatory 5
Research Project Mandatory

15

Robotics & Autonomous Systems Elective 5
Planning and Scheduling Elective 5
Fraud and Anomaly Detection Elective 5
Free Choice Module Elective 5

 

 

Module Details >>

 

 

 

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