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Course Details

Course Code(s):
PDNALPTPAD
Available:
Part-Time
Intake:
Autumn/Fall
Course Start Date:
September
Duration:
1 Year, Part-Time
Award:
Professional Diploma
Qualification:
NFQ Level 9 Minor Award
Faculty: Electronic & Computer Engineering, Science and Engineering
Course Type: Taught, Professional/Flexible, Online
Fees: For Information on Fees, see section below.

Contact(s):

Name: Dr Arash Joorabchi
Address: Department of Electronic & Computer Engineering Email: Arash.Joorabchi@ul.ie

Read instructions on how to apply

for more information or to be notified when applications are open.

Brief Description

Acquire in-demand skills and enhance your career opportunities with UL’s one-year, part-time Professional Diploma in Natural Language Processing (NLP).  

Delivered part-time and entirely online, it equips learners with foundational and advanced skills in statistical NLP techniques used in real-world systems like chatbots, grammar checkers, sentiment analysis, and text classification.  

With a combination of practical assignments and expert-led instruction, participants gain a robust understanding of the computational and linguistic methods required to translate natural language into actionable data. 

Ideal for graduates in computing, engineering, mathematics, science, or technology disciplines, as well as professionals with quantitative backgrounds looking to pivot into NLP and AI-driven language applications.  

This programme will earn 30 ECTS credits towards a Flexible Masters Pathway, allowing students to combine Postgraduate awards to achieve a Master’s over time. 

During this programme, you will:  

  • Learn key techniques used in natural language processing, like text analysis, spelling correction, and sentiment detection. 

  • Build practical skills by creating tools such as chatbots and text classifiers 

  • Gain hands-on experience with real-world applications of NLP. 

  • Learn how to design code and implement solutions to a range of NLP-related problems in your workplace and to build natural language processing solutions that work well. 

Key information: 

  • Complete part-time over one year  

  • Delivered online 

  • Modules taught during autumn and spring semesters 

  • Approx. 12 weeks per semester 

  • Modules with (M) beside them can be taken as independent micro-credential  

You will learn through a blend of:  

  • Lectures, workshops, and hands-on activities  

  • Reflective practice and guided research  

  • Regular feedback from faculty and peers  

Part-time considerations:  

  • Designed for working professionals  

  • Evening or recorded lectures  

  • Additional prep and group work time  

  • Timetable provided after registration 

Year 1  

Autumn Semester 

  • introduces students to the fields of Information Retrieval, Information Extraction, and Semantic Web. 

  • enables students to identify key trends affecting their role and organisation and build a professional network. 

Spring Semester 

  • covers advanced-level topics in natural language processing, focusing on deep learning-based approaches. 

  • explores the field of Natural Language Understanding and related topics. 

  • enables students to demonstrate independent and self-determined learning through the creation of an individual portfolio. 

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  

  • Applicants should hold a bachelor’s degree ( Level 8) with at least a second-class honour, grade 2 (2:2) in a relevant engineering, computing, mathematics, science or technology discipline. 

  • The university may shortlist and invite you to an interview.  

Other Entry Considerations: 

We encourage you to apply even if you don’t meet the standard entry requirements, as long as you can show that you have the knowledge, skills, and experience needed for the programme. 

At UL, we value all kinds of learning and support different ways to qualify through our Recognition of Prior Learning (RPL) policy. 

International students:   

For details on country-specific qualifications visit postgraduate entry requirements for international students. 

Checklist of documents:    

  • *Academic transcripts and certificates
    • UL graduates only need to provide their student ID.
  • Copy of your birth certificate or passport
  • English translation of your qualifications and transcripts
  • Copy of your CV 

English Language: 

Guidelines on Completing your Application   

  • To make sure we can review your application quickly, please:
    • Upload all documents. Your application can’t be reviewed until we have all the documents on the checklist. 
    • Title the documents you are uploading. For example, "Personal Statement", "Undergraduate Transcript", "Postgraduate Transcript", "English Language Certificate" etc. 
  • *If you are waiting to graduate, submit your application with the documents you have to date, you don’t need to have finished final exams before applying. 

EU - €5,250

Please note that international study visas are only available to students studying full-time in Ireland. This programme does not qualify for a study visa. 

Annual fees are billed by semester. Once registered, students may be eligible to apply for a monthly payment plan.  

Further information on fees and payment of fees is available from the Student Fees Office website. All fee related queries should be directed to the Student Fees Office (Phone: +353 61 213 007 or email student.fees.office@ul.ie). 


Funding  

Find further information on funding and scholarships.

 

This course can lead to the following sectors and careers:  

  • AI/Machine Learning engineer
  • Data scientist
  • Computational linguist
  • NLP engineer
  • Software development and engineering
  • Technical leadership
  • Technical team member 

Still Curious?  

The team regularly host and take part in webinars to support future students. If you would like to learn more or ask questions at an online information session, click below.     

Online Information Sessions