Certificate in AI and Emerging Technologies (Certificate, L7, 10 ECTS) (Middle East)

Introduction to Artificial Intelligence

History and evolution of AI

Myths, capabilities, and limitations of AI

Commodisation of AI and mainstream tool adoption

Key terminology: AI, machine learning, generative AI, LLMs, automation

Foundations of AI and Generative AI

How modern AI systems work (conceptual overview)

Generative AI: what it is, what it can do, and common use cases

Natural Language Processing (NLP) and conversational AI

Evaluating AI outputs: accuracy, reliability, and “hallucinations”

AI Tools and Practical Application

Survey of widely used AI tools and professional applications

Using AI for writing, planning, summarising, ideation, and productivity

Strengths/limitations of tools and selecting the right tool for the task

Responsible use in professional contexts (safe inputs, data awareness)

Prompting and Human-AI Interaction

Prompting fundamentals and structured prompting techniques

Iteration, role prompts, constraints, tone/style control

Building and using prompt libraries

Evaluating outputs for relevance, bias, and quality

AI-Enabled Automation

What automation is and how AI supports it

Examples of AI-assisted automation in everyday tools

Benefits and risks of automation (accuracy, over-reliance, human oversight)

Understanding where automation works well and where it does not

Ethics and Social Impact of AI

Understanding AI biases and fairness in algorithms.

Ethical dilemmas in AI and automation (e.g., job displacement, surveillance).

Privacy concerns in the digital age.

AI Safety & Data Protection

Understanding legal implications of Artificial Intelligence

Data protection implications (GDPR)

Regulatory Frameworks both at Irish and EU level

Introduction to Machine Learning

Basic machine learning concepts: supervised vs. unsupervised learning.

Everyday examples of machine learning in digital tools

Strengths and limitations of machine-learning systems

Risks, bias, and responsible use considerations

Practical examples of machine learning in real-world applications.

AI in Everyday Life

The impact of AI on industries like healthcare, finance, retail, and education. AI in entertainment: content recommendation, personalised experiences.

AI in smart homes and IoT (Internet of Things).

Digital transformation, AI adoption and the Future of Work

Introduction to digital transformation

AI adoption: opportunities, limitations, common challenges

Impact on roles, skills, and professional practice

Future workforce: AI literacy, data literacy, digital communication, critical thinking

Minimum Entry Requirements

· Mature applicants (i.e. over 23 years), or

· Leaving Certificate Grade O6 at ordinary level in five subjects (two of these subjects must be Mathematics and a language – English or Irish), or

· QQI Level 5 – Full award with a minimum of eight modules, or

· Recognition of Prior Learning

Modules are delivered over 12 weeks in an online learning format.

• The module will be delivered in an online approach; over a period of 12 weeks as follows;

  Online classes 2 hours one evening per week from 7pm-9.30 pm (Gulf Standard Time)

Each 5 credits will normally equate to approximately 100 Total Learning Hours. Total Learning Hours includes the time you spend in class (lectures, tutorials, practical elements) and the time you spend completing work outside of college. The balance between these two varies by discipline, and by level of study. You should bear in mind that the workload will increase at particular times e.g. when assignments are due.

Assessment is continuous and practice-focused.

€1,000 ( €300 euro funding available to Middle East GAA Members)

Applications will close on 16th February 2026 at 5pm.

Places are allocated on a first come first served basis

Programme run subject to viable numbers