Course Details

Course Code(s):
CTARINUDAD
Available:
Part-Time
Intake:
Autumn/Fall
Course Start Date:
September
Duration:
14 Weeks
Award:
Certificate
Qualification:
NFQ Level 8 Special Purpose Award
Faculty: Science and Engineering
Course Type: Taught, Professional/Flexible, Online
Fees: For Information on Fees, see section below.

Contact(s):

Name: SEFLC
Address: Science & Engineering Flexible Learning Centre Email: seflc@ul.ie
Name: Professor Pepijn van de Ven
Address: Dept. of Electronic & Computer Engineering Email: pepijn.VandeVen@ul.ie Telephone: +353 61 202925
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Brief Description

The Certificate in Artificial Intelligence is a preparatory course for entry to the MSc in Artificial Intelligence.

Successful completion of the Certificate will lead to the award of a Certificate in Artificial Intelligence (Special Purpose Award, Level 8, 12 ECT credits).

Click Here for the course flyer

To find out more about the MSc in Artificial Intelligence visit the programme page.

(M) Microcreds available:

Modules listed within the Programme Content with an (M) beside them are MicroCreds and can be taken independently.

Run in the Autumn semester, this 14-week course aims to equip students for the masters programme in AI.

Participants must complete the preparatory Certificate in Artificial Intelligence to the equivalent of a 2nd class honours level to be eligible for entry to the Masters, regardless of their prior qualifications or experience. The 12 credits gained by completing the two Certificate modules will count towards the 90 credits of the MSc in Artificial Intelligence.

For Whom

This programme is aimed at existing information technology professionals and those migrating from associated disciplines with an interest in and aptitude for transitioning into the area of AI.

For those seeking entry to the MSc in Artificial Intelligence programme

Delivery

The programme is delivered completely online, primarily via on-line lectures, supported with tutorials and assignments. Assessment is largely based on assignments and project work with a practical rather than theoretical focus.

Expected study time is 15-20 hours per week/module.

CE4021 - Introduction To Scientific Computing For AI (M)

An introduction to the core mathematics and core programming skills required in machine learning. Using a number of E-tivities you will hone your Python coding skills as well as your knowledge and skills in Calculus, Linear Algebra and Probability Theory as the three core areas of mathematics that underpin machine learning.

CE4031 - Introduction To Deep Learning And Frameworks   

A sneak preview of the exciting possibilities that modern machine learning offers, introducing you to the core methods used in machine learning and state-of-the-art networks, such as Convolutional Neural Networks.

 

For more detail on the modules see the Book of Modules. Please note that our Book of Modules reports time allocation based on 13 teaching weeks. Hence the information under ‘Hours per week’ in the book of modules is not reflective of expected time commitment on our 7-week modules, which is 15-20 hours per week.

 

Note: as a preparatory programme for the masters, the same entry requirements apply.

Category 1: The principal entry requirement is a Level 8 honours degree, at minimum second class  honours (NFQ or other internationally recognised equivalent), in a relevant engineering, computing, mathematics, science or technology discipline.

Category 2: Applicants who possess a Level 8 Honours degree in other disciplines, which have a significant mathematics and computing element, will also be considered.

Category 3: Applicants who possess a Level 8 honours degree at minimum second class honours in a non-numerate discipline and have a minimum of three years experiential learning in an appropriate  computing discipline may also be considered. A decision on the suitability and relevance of their experiential learning will be made by the University of Limerick.

Category 4: Applicants who do not meet any of the minimum educational requirements but have:

at least seven years work experience in a relevant computing or engineering environment

and/or

are in a senior or supervisory role in a company engaged in activities relevant to the subject matter of the  programme; may be considered under the University of Limerick policy that allows for the Recognition of Prior Learning (both formal and informal/experiential learning), non-accredited personal and professional education; industry-accredited certifications; and work-based training.

 

What to include in your application:

  • Scanned original copies of your Award Certificates/Full Transcripts for examinations mentioned on your application form
  • For Irish/EU applicants– Award certificate with overall award or Final Transcript
  • Non- EU applicants - Award certificate with overall award and Final Transcript
  • Graduates of UL need only provide us with their UL Student ID number.
  • If your qualifications have been obtained in a country where English is an official language this will suffice
  • If this is not available, the following additional documents must be provided:
  • English translation of your qualification(s)/transcripts AND
  • English language competency certificate
  • Please click here for Further Information on English Language Requirements
  •  A copy of your birth cert or passport
  •  Applicants in Categories 2 to 4 will need to upload a CV* and if applicable other relevant documentation to support their application, such professional certificates, supporting statements, etc.
  • Applicants in Category 4 will need to complete the RPL (Recognition of Prior Learning) form and submit it with their application.

*Please Note: Preferred CV format to have Educational detail before Employment detail

EU fees: €2,475 

Non-EU fees: €3,675

Further information on fees and payment of fees is available from the Student Fees Office website. All fee related queries should be directed to the Student Fees Office - Phone: +353 61 213 007 or email student.fees.office@ul.ie.

Please click here for information on funding and scholarships.