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During this module, you will: 

• Learn how to process and analyse text data using key NLP methods such as tokenisation, stemming, lemmatisation, and sentence segmentation.
• Build foundational knowledge of string similarity, n-gram language models, and spelling correction using tools like regular expressions and statistical modelling.
• Apply core NLP techniques to classify text and analyse sentiment, using tools like Naïve Bayes classifiers and sentiment lexicons.
• Explore  NLP libraries and cloud platforms including NLTK, spaCy, TextBlob  to understand real-world applications. 

Key Information

This micro-credential will be delivered online over 6 weeks. 

You will be assessed using continuous skill-based assignments with no final exam.  

Part-time considerations:      

• Designed for working professionals      

• Evening or recorded lectures      

• Additional prep and group work time      

• Timetable provided after registration 

Module Prerequisite:

We use the Python programming language in this course. You do not need to be a professional Python programmer, but you do need to be familiar with the general programming concepts and their implementation in Python, examples of these include:   

• Data types, variables, numbers, strings 

• Numeral Operators, Booleans 

• Data structures, lists, tuples, sets, dictionaries, arrays 

• If…else statements 

• While loops, For loops 

• Functions 

• Classes and objects   

If you do have some coding experience in Python and are familiar with these topics then this course could be a good fit for you. Otherwise, learning Python and NLP at the same time could be too challenging. 

To help you to be successful on this course: 

• Applicants should hold a bachelor’s degree ( Level 8) with at least a second class honours, grade 2 (2:2) in a cognitive discipline.  

• If applicants have a lower result or an unrelated qualification, they may be considered on a case-by-case basis if they can provide evidence of one or more years of post-degree industrial experience in Computer Science/IT/Computer Engineering or related disciplines. (Recognised Prior Learning). 

Guidelines for your applications: 

• When applying, be sure to include the Module Code MN5001. We can’t process your application without it. You can apply for more than one module using the same application.  

• By applying, you confirm that you meet the entry requirements and can take part in the course and its assessments.  

• This course will go ahead if it meets minimum enrolment number.  

• Completing this module doesn’t guarantee you a place in a full programme. If you want to apply for a full programme, you must meet the specific entry requirements for that programme. 

EU - €1,292

Non-EU - €1,292

Further information on fees and payment of fees is available from the 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).  

Other funding  

Find further information on funding and scholarships.

This micro-credential can lead to the following sectors and careers: 

• Data science and artificial intelligence roles, including NLP and machine learning engineering 

• Technology and software development roles focused on language-based applications 

• Research and academic roles in linguistics, cognitive science or computational linguistics 

• Marketing analytics, customer experience, or content moderation roles that benefit from language analysis tools