Advanced Artificial Intelligence (SUSA)

What Will I Learn?

Key learning outcomes include the ability to:

• Build deep knowledge of advanced AI technologies such as deep learning, generative AI, reinforcement learning, evaluation methodologies, optimisation, AI systems and their deployment etc.
• Evaluate trade-offs involving complexity, interpretability, scalability, robustness, and generalisability of AI models
• Proficiently apply AI to real-world problems in various domains 

Students will select several option modules from applications of AI in different sectors such as health, audio and speech, time-series from sensor devices, recommender systems, human-computer interaction etc. and learn to apply the advanced AI techniques in different application areas, including:

• The potential and limitations of different advanced AI technologies and understand the techniques appropriate for different applications
• How to apply the AI technologies in an ethical and responsible way
• how to communicate the insights from data and the AI techniques to executives and understand how to interpret the AI results correctly

The third trimester offers three options:

• Internship: Gain practical experience in industry.
• Dissertation: Conduct in-depth research under academic guidance.
• AI Project: Apply AI techniques to a specific problem.

Please note that internship placements and dissertation opportunities are competitive and not guaranteed.

Student profile

Ireland's vibrant tech industry, coupled with the growing demand for AI expertise, offers exciting career prospects for our MSc in Advanced AI graduates. From cutting-edge research roles in academia to high-demand industry positions, there is a wide range of possibilities. AI careers are highly sought after with opportunities for advancement. 

Our MSc programme equips graduates to excel in diverse roles, including data science, data analysis, business intelligence, machine learning engineering, AI ethics, and AI product management. This course is also a stepping stone for PhD research.

Modules

Core modules

• Foundations of Deep Learning
• Applied AI in Vision & Imaging
• Responsible Artificial Intelligence
• Advanced ML (AAI)
• Optimisation
• AI and Ethics
• Advanced Generative AI & LLMS
• ML System Deployment

Options

• Human-Centred AI
• Artificial/Human Intelligence
• AI for Time Series
• Intro. to Quantum Computing

Options

• Optimization Algorithms
• Recommender Systems
• AI for Health
• Agentic AI
• Speech and Audio
• Quantum Machine Learning
• Information Visualisation (Blended Delivery)
• AI & Digital Cultural Heritage
• Bayesian Analysis (online)
• Extremes for Climate