Postgraduate Certificate in Large Language Models
Course Overview
The Postgraduate Certificate in Large Language Models is a 10-credit, level 9 conversion programme devised to provide up-skilling/re-skilling opportunities for numerate graduates. The programme is aimed at IT professionals with competent programming skills wishing to develop their skills in AI and Large Language models.
What makes this course different
Fundamentals of Large Language Models
Develop a solid understanding of the fundamentals of Large Language Models (LLMs) and explore their practical applications across various domains.
Fine-tune and augment LLMs
Learn how to fine-tune and augment LLMs to improve performance, enhance contextual relevance, and enable effective data retrieval
Understanding the Industry
Large Language Models (LLMs) are truly disruptive technologies, poised to transform virtually every sector. For IT professionals, understanding these advancements is essential to staying relevant and competitive in a rapidly evolving landscape.
Career Opportunities
The demand for IT professionals with AI expertise is growing rapidly, as these technologies are set to reshape many existing roles. DKIT is committed to equipping participants with an accredited qualification that employers can trust as a credible and objective measure of knowledge in this fast-evolving field.
In PluralSite’s 2025 Skills Report, they find: “50% of companies give strong preference to job candidates with AI skills”.
Course Delivery and Modules
The course will be delivered online over the course of two semesters, from September to May.
Two evening lectures will be delivered each week during each semester.
Modules will be delivered in Python. Good Python programming skills will be required to access material and achieve the Learning Outcomes.
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Year One
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- Module 1: Introduction to Large Language Models
- Module 2: Retrieval-Augmented Generation (RAG) & Information Retrieval
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Fees and Funding
EU Fees: TBC
International Fee: TBC
Fees
TBC
TBC
Entry Requirements
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This standard minimum entry requirements is a 2.2 Honours Degree (NFQ Level 8) or equivalent in STEM (Science, Technology, Engineering, and Mathematics), who have substantial technical competencies and strong programming skills. A good grounding in Maths will be required to access material related to Machine Learning. |
How To Apply
To register your interest for this course Click Here
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Disclaimer: All module titles are subject to change and for indicative purposes only. All courses are delivered subject to demand and timetables are subject to change. Elective Module options will only run subject to student numbers. The relevant Department will determine the viability of each elective module option proceeding depending on the number of students who choose that option. Students will be offered alternative elective modules on their programme should their preferred elective option not be proceeding. Award Options for Common Entry Programmes: The relevant Department will determine the viability of each award option proceeding depending on the number of students who choose either option. If the numbers for one of the Award options exceed available places, students for this option will be selected based on Academic Merit (highest grades).
