Data Science & Analytics - Cork

The MSc in Data Science and Analytics at MTU, is a collaboration between the Department of Mathematics and the Department of Computer Science, which aims to develop highly skilled and competent graduates in the rapidly expanding field of Data Science. This collaborative programme provides graduates with a thorough grounding in the theory of Data Science, while allowing graduates to become highly proficient in the technical and practical skills required by employers. The course will equip graduates with the skills to gather, store and process data using advanced techniques such as machine, deep learning and statistical modelling to deliver new insights and knowledge from collected data.

The programme has been designed with industry experts to ensure that in the first two semesters graduates develop core skills in programming, database management, statistical modelling, time series analysis, machine learning, and data visualisation. Students will also learn how to interpret these results to improve business performance. The capstone research project in Semester 3 is a key component of this MSc programme. The project allows the learner to apply the knowledge, skills and competences acquired in the taught modules to research and development applied to a real-world data science problem.

Master of Science in Data Science & Analytics

Subjects taught

The full-time MSc in Data Science & Analytics will run over three semesters, i.e. fifteen months. Each semester accrues 30 credits.

The Semester 1 schedule consists of six taught modules (each five credits). The learner acquires a foundation in Mathematics, Statistics and Computer Science, with the signature module DATA8001 Data Science & Analytics overarching the other five modules of this semester.

Semester 1
Module Code Module Title
DATA8001 Data Science and Analytics
MATH8009 Mathematical Methods and Modelling
DATA8002 Data Management Systems
DATA8003 Unstructured Data & Visualisation
COMP8042 Analytical and Scientific Programming
STAT8006 Applied Stats & Probability

Semester 2
Module Code Module Title
STAT9004 Statistical Data Analysis
DATA9001 Data Visualisation & Analytics
DATA9002 Distributed Data Management
STAT9005 Time Series & Factor Analysis
COMP9060 Applied Machine Learning
MATH9001 Research Methods

In Semester 3, the MSc learner undertakes one capstone project module (DATA9003 Research Project – Data Science) worth 30 credits.

Contact hours
Semester 1
24 contact hours per week. The learner should also expect to invest at least 18 hours per week in independent learning (independent study, preparation of coursework, etc.)

Semester 2
23 contact hours per week. The learner should also expect to invest at least 19 hours per week in independent learning (independent study, preparation of coursework, etc.)

Semester 3
The learner will work full-time on the 30 credit project. Typically, this involves a workload of 42 hours per week, to include meeting with MTU project supervisor.

Entry requirements

The entry requirements for the MSc programme are

2.1 in a Level 8 Honours degree

Alternatively, graduates with a 2.2 Honours degree will be considered, subject to having three years relevant experience. See RPL for further details.

The language of academic instruction as well as administration is English. Non-native speakers of English require a minimum IELTS score of 6.0 to be considered for entry into this postgraduate programme. Appropriate EFL training courses are offered by MTU Cork to applicants who meet the academic programme entry requirements but who need to increase their proficiency in the English language.

Applicants are also required to

Provide an up-to-date CV with their application

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

The application process also includes an interview.

Application dates

Irish/EU Applications: 1st September 2024. Non-EU: 31st May 2024


3 semesters full-time.

Three semesters

Semester 1 – September 2023 to January 2024
Semester 2 – January 2024 to June 2024
Semester 3 – June 2024 to September 2024 OR September 2024 to January 2025

Post Course Info

Career Options
Graduates of this programme will be of high academic and practical standards having gained key knowledge, skills and competences in Data Science, Machine Learning, Statistics, and Computer Science. Graduates will experience first hand the application of their newly developed skills to solving real-life problems.

Our alumni have gone onto a wide variety of roles as data scientists, as well as other technical and leadership roles in high tech industries such as financial services, pharmaceuticals, IT, brewing, consulting, official statistics, retail analytics, data science banking, and many more.

More details
  • Qualification letters


  • Qualifications

    Degree - Masters (Level 9 NFQ)

  • Attendance type

    Full time,Daytime

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    Course provider