On this NFQ Level 9 programme, you’ll explore natural language processing frameworks to understand their core features and usability. You’ll design code to implement solutions to a range of NLP-related problems in your workplace and learn how to use the right technologies, frameworks, and platforms to build natural language processing solutions that work well.
NLP skills are in high demand right across. For example, businesses need NLP to understand customer feedback, monitor brand reputation, and analyze social media interactions. In healthcare, NLP can be used to extract insights from electronic health records and medical literature.
The skills you’ll acquire from this Professional Diploma in NLP are transferable to various job roles. Here are a few examples:
– Data Scientist – In this role, you’ll use NLP to extract insights from text data and build predictive models. You’ll work with large datasets and use statistical methods to find patterns in the data.
– Machine Learning Engineer – As a machine learning engineer, you’ll work on developing algorithms that enable machines to learn from text data. You’ll collaborate with data scientists and software engineers to build and deploy NLP models.
– Computational Linguist – In this role, you’ll work on developing and improving NLP algorithms. You’ll use your understanding of human language to improve the accuracy of NLP models and make them more efficient.
All lectures will be recorded. Live sessions will be at a time suitable to the student group. Online content should be accessed daily. Approx 13 hours per week, which breaks down as:
- 2hrs online classes
- 2hrs e-moderated groups
- 9 hrs self-study, as a guide.
Course Director Profiles
Dr Arash Joorabchi is a lecturer in the Department of Electronic & Computer Engineering at the University of Limerick. Dr Joorabchi’s main research areas are Text Analytics and Natural Language Processing. He has worked on various research and industry-related projects in Health Informatics, Dialog Systems, and Digital Libraries.
Prof Patrick Denny is in the Department of Electronic and Computer Engineering at the University of Limerick and is an adjunct professor of engineering at the University of Galway. He has extensive industrial and academic experience with over 20 years of automotive engineering experience internationally as a senior engineer designing and developing radiofrequency and imaging systems for BMW, Daimler, Land Rover, Ford, VW, Audi, Volvo and other major car companies. Prof Denny has founded several conferences, working groups and standards bodies and has an extensive portfolio of patents, products and publications. His experience includes imaging systems, sensing, industrialisation, artificial intelligence and computer vision.
Dr Pepijn van de Ven is a Senior Lecturer in Artificial Intelligence and Machine Learning and a Course Director for UL’s MSc in Artificial Intelligence (AI), an industry-driven, fast-paced masters to upskill Ireland’s workforce in the use of Artificial Intelligence.
Funding Eligibility
Applicants must be working in a private or commercial semi-state organisation registered in the Republic of Ireland to avail of the grant-aided fees. As a government-funded training network, we can only support those meeting these criteria.
Applicants who do not meet our funding criteria may in some cases be able to apply directly to the college and pay the full fee of €3,500 if there are places available. Contact us for more information.
Academic Eligibility
Applicants are normally expected to hold a primary honours degree in a related discipline, (minimum H2.2).
Alternative Entry Route:
In accordance with the University’s policy on the Recognition of Prior Learning candidates who do not meet the minimum entry criteria may be considered. These candidates will be required to submit a portfolio to demonstrate their technical and/or management experience. An interview with the course admission team is also required to ensure candidates have the experience, motivation, and ability to complete and benefit from this course.
English Language Requirements:
Applicants who do not have English as their first language may satisfy English Language requirements if your qualifications have been obtained in a country where English is an official language this will suffice.
If this is not available, the following additional documents must be provided:
- English translation of your qualification(s)/transcripts
AND
- English language competency certificate
Fees
Full Course fee per annum: €3,500
Skillnet grant per annum: €700
Student fee per annum: €2,800*
*Part-funded fees are only available to eligible applicants.
Click “Apply now” and attach your updated CV to be assessed for funding eligibility.
Alternatively, email info@ictskillnet.ie with the below information:
– Subject line “Professional Diploma in Natural Language Processing”
– Current Employer
– Current Highest NFQ
– Attach your CV
The University of Limerick has sole discretion and is the final arbiter on who will participate. Making an application is not a guarantee of selection. Applications are treated in strictest confidence.
Semester 1:
Introduction to Natural Language Processing:
This module introduces you to the world of Natural Language Processing (NLP). We cover the fundamentals of statistical NLP and its techniques and applications with a foundational approach.
Information Retrieval
This module offers an overview of the fields of Information Retrieval, Information Extraction, and Semantic Web. The module will cover a blend of fundamental concepts and current tools, techniques, and technologies used in modern information retrieval systems.
Semester 2:
Advanced Natural Language Processing
This module covers advanced-level topics in natural language processing, focusing on deep learning-based approaches. These include text classification, synthetic parsing, part-of-speech tagging, named-entity recognition, coreference resolution, and machine translation. You will be taken through neural network architectures, including convolutional neural networks, recurrent neural networks, to long short-term memory networks (LSTMs).
Natural Language Understanding:
This module explores the field of Natural Language Understanding and related topics, including sentiment analysis, relation extraction, natural language inference, semantic parsing, question answering, language generation, and large language models like ChatGPT and conversational agents.
Both Semesters:
Future Focused Professional Portfolio 1 & 2:
In the first module, you will be led through a series of talks about the future of technology, the future of markets, and the future of society as a whole. You’ll work collaboratively to identify key trends impacting your role and organisation. You’ll also build a professional network and use it to reach out to key thought leaders in this area.
The second module will provide you with an opportunity to demonstrate independent and self-determined learning through the creation of your own individual portfolio. Your portfolio includes various activities that will show how you’ve improved your reflective practice, how well you’ve used discipline-specific knowledge in different situations, and how you’ve led a discussion about the future of your field.
What programmes/platforms will we be using?
- Python language to design and develop a wide range of NLP solutions using a variety of ML/NLP libraries and frameworks.
- Platforms such as NLTK, scikit-learn, spaCy, TextBlob, Gensim, PyTorch, Keras, Tensorflow, Hugging Face Model Hub, Google Colab and GitLab.
How are learners assessed on this programme?
There are no terminal exams on this programme. Assessment will be continuous; you will be asked to prepare a media plan that will be developed for your chosen company. Assessment consists of continuous assignments and quizzes.
Student testimonial: Michaela Dillon
Michaela Dillon completed the MSc. in Artificial Intelligence with the University of Limerick. ‘The decision to embark on the course was to expand my knowledge and thus be open to other opportunities for employment; since technology, and the skills required, are constantly evolving’.
‘The NLP modules MN5002 and MN5162 were incredibly interesting primarily because there has been such a massive increase regarding AI in the news while we were working on these modules’.
