Artificial Intelligence and Machine Learning - MSc Programme content
Expand your career prospect with this one-year, full time Master’s in Artificial Intelligence and Machine Learning.
Application closing date 12th March
Application closing date 12th March
Key information
EU fees per year
€8,500
Non-EU fees per year
€21,500
NFQ Level
NFQ Level 9 Major
Duration
One year
Attendance
Full-time
Programme type
Taught
Delivery
In-person
Start date
September
Award
Masters (MSc)
Application end date
12 March 2027
Key information
- Complete full-time over one year
- Delivered on campus
- Modules taught during autumn and spring semesters
- Submit dissertation or Learning Project at the end of summer semester
You will learn through a blend of
- Lectures, workshops, and hands-on activities
- Reflective practice and guided research
- Regular feedback from faculty and peers
Programme content
Core modules
- Introduction to Data Engineering and Machine Learning (CE4051) covers mathematical and coding skills essential to developing machine learning applications in Python and introduces more advanced machine learning topics.
- Evolutionary Computation and Humanoid Robotics (CS6271) introduces Evolutionary Algorithms and delves into specific algorithms, including Genetic Programming, Grammatical Evolution and more.
- Text Analytics and Natural Language Processing (EE6041) provides a practical knowledge of text analysis techniques and Natural Language Processing.
- Artificial Intelligence for Games (CS4096) provides a foundation in the principles and applications of Artificial Intelligence methods as applied to Games and Game Development.
- Machine Vision (CE6021) the aim of this module is to allow the student to gain a detailed insight into image formation, formats and processing necessary so computers can use machine vision technologies.
Books and journal articles needed for the course will be available online through the UL Glucksman Library.
For more information on each module, you can search the faculty, school and module code on UL’s Book of Modules.
Core modules
- Artificial Intelligence and Machine Learning (CE6012) the module covers what it is we mean by learning from data and using patterns in data to learn from it as long as we have enough data from which to learn. We will look at how to learn from data, using basic techniques and trialling them on data sets, we will look a algorithms to make or learning better.
- Deep Reinforcement Learning (CS6482) provides fundamental knowledge and techniques necessary to understand/develop/use Deep Reinforcement Learning.
- Probabilistic and Explainable AI (CS6462) introduces probabilistic programming and defines probabilistic AI models and inference algorithms.
- Theory and Practice of Advanced AI Ecosystems (CS5024) prepares students to understand and use a wealth of new technologies relevant to the production and use of Artificial Intelligence.
- Research Methods and Project Specification (ED5073) helps students to specify a project and demonstrate research skills.
Books and journal articles needed for the course will be available online through the UL Glucksman Library.
For more information on each module, you can search the faculty, school and module code on UL’s Book of Modules.
Core module
- Artificial Intelligence and Machine Learning Project (CS6143) enables students to research, analyse and present a project based on a chosen topic or problem.
Books and journal articles needed for the course will be available online through the UL Glucksman Library.
For more information on each module, you can search the faculty, school and module code on UL’s Book of Modules.
