Advanced Artificial Intelligence

Key learning outcomes include:

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

Our diverse range of modules and assessments ensures a comprehensive and engaging learning experience, preparing you for a  career in the field of AI.

Please note that the modules listed are subject to change and are not guaranteed by UCD. Modules marked * are new modules - details to come later.

Core modules

• Advanced Machine Learning
• Deep Learning
• AI for Computer Vision *
• Trustworthy and Responsible AI *
• Optimisation
• Generative AI: Language Models
• Artificial Intelligence Ethics *
• Machine Learning System Deployment *

Option modules

• Artificial/Human Intelligence
• Human Centered AI
• Intro. to Quantum Computing
• AI for Time Series *
• AI for Health *
• Speech and Audio
• Quantum Machine Learning
• Recommender Systems 
• Maths of Machine Learning
• Information Visualisation

Our one-year, full-time MSc in Advanced AI is delivered on-campus at UCD.

The programme spans three trimesters, beginning in September and concluding in August. To earn the MSc degree, students must accumulate 90 ECTS credits.

You will learn the cutting-edge technologies through the core modules in the first and second trimesters and select from a wide range of application modules to accumulate a total of 60 credits. 

The third trimester offers three options:

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

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

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.

Students entering this programme are expected to have a 2:1 honours bachelor's degree, or its international equivalent, in Computer Science or Computer/Electronic Engineering or Informatics or Artificial Intelligence or Mathematics or Physics. In addition, the student must meet all of the below requirements:

• The applicant must have taken at least one module on Machine learning, artificial intelligence, data science or data mining.
• The applicant must have completed a module with a significant programming component in at least one of the following: C, C++, C#, Java, Python or R. Alternatively, a module on algorithms or data structures or software engineering with a programming focus can also be considered.
• The applicant is expected to have a strong background in mathematics with one or more modules covering some of the following subjects/topics: calculus (differentiation and integration), linear algebra (vectors and multi-dimensional matrices), discrete mathematics and mathematical reasoning (e.g. induction and reasoning, graph theoretic models, proofs), and probability.

Alternatively, applicants can also enter this programme if they have a 2:2 honours bachelor’s degree and have at least 2 years of industry experience working on AI (machine learning, deep learning, computer vision, natural language processing, optimisation) or data science applications. In this case, the students need not satisfy the requirement of having done modules on AI, programming and basic mathematics.

Applicants whose first language is not English must also demonstrate English language proficiency of IELTS 6.5 with not less than 6.0 in any strand, or equivalent 5.

No Garda vetting, health screening, fitness to practise is required.

Full Time option suitable for:

Domestic(EEA) applicants: Yes
International (Non EU) applicants: Yes