Data Science & Analytics - Cork / Online

The growth in the field of Data Science and Analytics has been enormous in recent years, with a growing demand for practitioners in a variety of industries.

With the ever-increasing growth in data generation and collection, industries now rely heavily on appropriate analyses. Consequently, data science and analytics have become a core component of both the public and private sectors that seek to gain a competitive advantage.



MTU’s new part-time Postgraduate Certificate in Data Science & Analytics, delivered by the Department of Mathematics in collaboration with the Department of Computer Science, aims to develop highly skilled and competent graduates in the core competencies in Data Science and Analytics. The programme blends three themes – Data Science, Statistics and Computer Science - across two semesters. There are significant opportunities throughout for learners to apply their theoretical knowledge and develop problem-solving skills through practical work, with opportunities to apply learnings from the programme to authentic problems in the field.



Graduates of this programme will be positioned to match the growing needs of Irish and international industries, particularly in the technology and 'Big Data’ space, seeking to gain a competitive advantage from data interrogation. Graduates will be able to apply the transferable skills obtained in their previous undergraduate degree to newly acquired knowledge, skills and competences from this programme.



Developed with extensive industry engagement, the programme has been designed to address skills needs as identified by the Southwest Regional Skills Forum. It builds on the success of MTU’s MSc and HDipSc programmes in Data Science & Analytics. Graduates of those programmes have been extremely successful in employment, with industry experts frequently praising their quality.



Award

Postgraduate Certificate in Data Science & Analytics

The part-time PG Cert in Data Science & Analytics will run over two semesters, from September to June.

The part-time PG Cert in Data Science & Analytics will run over two semesters, from September to June. Each semester accrues 15 ECTS credits.



The Semester 1 schedule consists of three taught modules (each 5 credits). The learner acquires a foundation in Statistics & Probability and programming, with the third module being the signature module DATA9009 Data Science Principles.



Semester Schedules



Semester 1



DATA9009 Data Science Principles (5 ECTS)

This module will provide the learner with an overview of the key themes, methods and technologies in the field of data science and analytics. An emphasis will be placed both on the real-world practical and the technical aspects of data science.



Programming Module: For academic year 2025/26, the programming module will be STAT8010 Introduction to R for Data Science (5 ECTS)

In this module, students will learn how to clean, manipulate and visualise real-world data using the statistical software package R. Students will also learn how to create reproducible documentation/presentations and interactive dashboards/applications using R.



STAT9012 Statistics & Probability (5 ECTS)

This module explores the application of statistics and probability distributions to real-world problems. It focuses on developing skills in data visualisation, probability theory and distributions. Learners will also build knowledge, skills, and competence in sampling theory and hypothesis testing using both parametric and non-parametric methods.



Semester 2

STAT9005 Time Series Analysis (5 ECTS)

This module provides learners with the necessary tools to develop and critically evaluate time series models. Using programming tools, data will be manipulated and readied for analysis including making the data a time series object. Time series analysis of univariate and multivariate problems are considered. These techniques will enable the learner to create short and medium term forecasting models.



STAT9004 Regression Analysis (5 ECTS)

In this module, the learner will study statistical techniques, with particular emphasis on linear models. Statistical analytical software will be used in the labs.



STAT9013 Data Mining and Statistical Modelling (5 ECTS)

Learners will develop a comprehensive knowledge of applied modelling, data mining, model evaluation, and data pre-processing. Tools such as segmentation and key case studies will be presented. Consideration is given to generative AI in this course.



Contact Hours

Semester 1

9-10 contact hours per week. The learner should also expect to invest at least 10-12 hours per week in independent learning (independent study, preparation of coursework, etc.)



Semester 2

9-10 contact hours per week. The learner should also expect to invest at least 10-12 hours per week in independent learning (independent study, preparation of coursework, etc.)

The minimum entry requirements for the MSc, PG Diploma, and PG Certificate are follows:

2.1 (or equivalent) in a Level 8 Honours degree.



Alternatively, graduates with a 2.2 Honours degree will be considered, subject to having three years relevant experience, under MTU’s Recognition of Prior Learning (RPL) Policy.



Non-native speakers of English require a minimum IELTS score of 6.0 to be considered for entry into this postgraduate programme.



Applicants are also required to:



Provide an up-to-date CV with their application.



Supporting documents such as transcripts, certificates, etc.



Submit a 500-word statement detailing motivation for applying for the programme and how it will enable them to meet their career goals.



Any further information which may support their application, for example, information in regard to Higher Level grades in Leaving Certificate (or equivalent) subjects such as Mathematics and Applied Mathematics.



Applicants should also note that they may be requested to attend for interview (online).

1 year, part-time, blended.

Career options

Graduates of this programme will be positioned to match the growing needs of Irish and international industries, particularly in the technology and 'Big Data’ space, seeking to gain competitive advantage from data interrogation. Graduates will be able to apply the transferable skills obtained in their previous undergraduate degree to newly acquired knowledge, skills and competences from this programme.



Developed with extensive industry engagement, the programme has been designed to address skills needs as identified by the Southwest Regional Skills Forum. It builds on the success of MTU’s MSc and HDipSc programmes in Data Science & Analytics. Graduates of those programmes have been extremely successful in employment, with industry experts frequently praising their quality.



Progression

While this PG Cert in Data Science & Analytics is a standalone award in its own right, it also provides an access route to MTU’s MSc in Data Science & Analytics.



All modules of the PG Cert are also on the MSc. This means that a learner who completes the PG Cert and then progresses to the MSc has already completed 30 ECTS of the MSc and therefore just has to successfully complete the remaining 60 ECTS of the MSc in order to gain the MSc. Currently, MTU’s MSc in Data Science & Analytics runs in full-time mode only (over 12-15 months) and is not Springboard funded. Depending on demand, we may be in a position to run it part-time in the future.