MSc in Data Analytics

Semester 1

• Data Architecture (part 1 of 2)
• Statistics
• Programming for Data Analytics
• Research Process for Data Analytics

Semester 2

• Data Architecture (part 2 of 2)
• Data Visualization and Insight
• Time Series Analysis
• Machine Learning
• Ethics in Data Analytics 

Semester 3

• Dissertation

Module Descriptions:

• Data Architecture (10 credits) provides a programming framework that would assist in solving big data problems in a distributed computing environment. 
• Statistics (10 credits) is to build on the fundamental of mathematics and statistics needed for the masters whilst learning how to begin to apply these techniques to real data.
• Data Visualisation and Insight (5 credits) and Insight aims to employ statistical tools to analyse data and communicate meaningful information effectively, accurately and efficiently.
• Programming for Data Analytics (10 credits) introduces the programming tools in Python for Data Analysis that would assist students in subsequent modules of this programme.
• Time series Analysis (5 credits) focuses on the analysis of data taken at regular time intervals, with real data applications in topics such as economics and finance.
• Machine Learning (10 credits) provides the knowledge and the applications of ML algorithms including Neural Networks.
• Research Process for Data Analytic (5 credits) focuses on developing good research practice and prepare students for the research process required for the dissertation.
• Ethics in Data Analytics (5 credits) familiarises students with GDPR and builds awareness of the moral and social responsibility in the field of Data Science.
• Dissertation (30 credits) gives the graduate the ultimate learning experience, the student gets the first-hand experience of what is involved in mastering data analysis, by carrying out a project using real-world data from industry or research to solve data-rich problems.

This course is delivered using a mix of lectures, workshops, labs, tutorials and independent reading, continuous assessment projects etc.

Full-time course is delivered over 3 semesters in 1 year (including summer). The part-time course takes place over 2 years.

These career paths can take place in many different sectors and industries including areas such as research; academia; business; finance; banking; healthcare; pharmaceuticals; commercialism; and technology.

Graduates from MSc in Data Analytics can find Industry roles such as Data Analyst, Data Scientist, Data Engineer, Data Architect, Business Data Analyst, Data Visualisation developer and Statistician.

Please find information on fees and funding here https://www.dkit.ie/study/student-fees-grants-scholarships/fees.html#postgrad

Standard Entry Requirements:

The standard minimum entry requirement is a 2.2 Honours Degree (NFQ Level 8) or equivalent in the area of Mathematics, Statistics, Computing, Engineering, Science or equivalent qualification in a cognate discipline, which included a minimum of 15 credits in Mathematics and Statistics and 10 credits of programming centric modules. The Higher Diploma in Science in Data Analytics Level 8 award is seen as an entry route to this programme.

International Student Entry Requirements:

International applicants must meet the minimum entry requirements for the programme in addition to providing evidence of proficiency in English. The English requirements are as follows:

• Grade B2 equivalent on CEFR (Common European Framework of Reference for Languages) OR have achieved IELTS 6.5 (or internationally-recognised equivalent). Where an applicant demonstrates evidence of having attained his/her Bachelor Degree through
• instruction in the English language, a grade of 6.0 may be accepted for admission to a STEM programme.

Shortlisted candidates may be invited for an interview.

This course is best-suited to:

• Individuals who are numerate, and have good programming skillset; 
• Individuals who like to be a part of cutting-edge technology that works to improve human-machine and machine-machine interactions; 
• Individuals who wish to extend their skillset to a more advanced level in the area of Data Analytics to improve their career prospects or make a career change.

Dr Fiona Lawless (Head of Computing Science and Mathematics)
Phone: +353 42 9370200
Email: fiona.lawless@dkit.ie

Dr Jack McDonnell (Programme Director)
Email: jack.mcdonell@dkit.ie

A Postgraduate Diploma in Science in Data Analytics (60-credit NFQ Level 9 qualification) is awarded following the successful completion of Semesters 1 & 2 of the Master in Science in Data Analytics.

All applicants are advised that advanced numeracy skills and proficiency in programming are essential for success on the MSc in Data Analytics. Students will be assumed to have strong mathematical/ statistical ability and be capable programmers.