Natural Language Processing - Professional Diploma - UL@Work

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.

Stack your learning with Microcreds:
Not quite ready to commit to a full professional diploma? Consider trying a microcredential. You can stack your microcred credits towards a professional diploma at a later date. Modules listed within the Programme Content with an (M) beside them are MicroCreds and can be taken independently.

The principal entry requirement is a Level 8 honours degree, at minimum second class honours (NFQ or other internationally recognised equivalent), in a relevant engineering, computing, mathematics, science or technology discipline.

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. Applicants from other disciplines who have a relevant mathematics and computing element in their primary degree will also be considered. Applicants who possess an honours u/g degree, minimum second-class, or equivalent in a non-numerate discipline and have a minimum of 3 years experiential learning in an appropriate computing discipline will be considered. English Language Requirements, right to shortlist, interview, and RPL policy will apply.

What to include with your application:

• Qualification transcripts and certificates
• A copy of your birth certificate or passport
• A copy of your CV
• 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
• Please click here for Further Information on English Language Requirements

Guidelines on Completing your Application

• To ensure a speedy assessment of your application, please upload the above documents with your application form – your application cannot be assessed until relevant documentation is uploaded

• Please title appropriately any documents you are uploading with the application form, for example "Supporting Statement", "Undergraduate Transcript", "Postgraduate Transcript", "English Language Certificate" etc.

International students can find more information on eligibility requirements here.