Postgraduate Diploma in Science in Data Analytics (Full-Time)

Semester 1

• Data Architecture (10 credits): This module runs for two semesters and provides a programming framework that would assist in solving big data problems in a distributed computing environment.
• Research Process for Data Analytic (5 credits)focuses on developing good research practice and prepare students for the research process required for the dissertation.
• 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.
• 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.

Semester 2

• 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.
• Applied Data Analytics Project (10 credits)Undertake an industry related data-driven project: manage lifecycle stages, ethical and GDPR issues.

This course is typically delivered on-campus and will be delivered in full-time mode

• 16 Weekly Contact Hours (3 days a week)
• 24 Weekly hours - Directed/Independent Study

The Post-Graduate Diploma in Data Analytics aims to address the urgent skills demands - it builds digital skills, develops critical thinking, analytical skills and business acumen in an area highlighted as crucial for the workplace of the future,

“Many of the fastest growing occupations and emerging industries require numeracy, knowledge of scientific and mathematical principles, as well as the ability to generate, understand and analyse empirical data and solve complex problems (UKCES, 2011). These skills make technological breakthroughs possible.”

It will address important issues in various modern Data Infrastructures through Machine learning and is well suited to data enthusiasts who are looking for opportunities across big data industries.

Graduates from the programme will be capable of assisting employers by providing analytical solutions that can give invaluable insights and trends in both public and private business sectors. The proposed programme has been specifically designed to provide local workers with upskilling opportunities, providing local companies with additional appropriately skilled graduates while at the same time improving the employability and mobility of individuals.

The focus on building expert knowledge and analytical skills and applying this to real- industry focused projects – from inception through all aspects of the data-life cycle - means students develop independent thinking and desired work-ready skills.

The following are eligible to apply for courses in 2022/23 academic year (subject to the applicant meeting all requirements, e.g. academic requirements):

• Returners: May apply to all courses if they meet the nationality/visa requirement and residency criteria.
• People in employment: May apply to all courses if they meet the nationality/visa requirement and residency criteria.
• The unemployed or formerly self-employed: All courses are open to these categories of applicants
• Recent Graduates: One-year full-time and two-year part-time ICT Skills Conversion courses are open to recent graduates. However, to participate in an NFQ Level 9 (Post-Graduate) course, 2020 graduates will be required to pay 10% of the course fee (€785.70).

For more information of fees and eligibility criteria, please visit the Springboard+ Website. You may also contact Dr Tim McCormac for more information about Fees for this programme:

DkIT Graduate Office
Unit 13, Regional Development Centre

E. graduatestudies@dkit.ie

T. +353 (0)429370458

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 Technology or equivalent qualification in a cognate discipline, which provided a strong foundation in Mathematics/Statistics and computer applications.

Graduates with strong numerate skills who wish to pursue a career in the expanding area of Data Analytics.

Professionals who wish to develop their Data Analytics and Mining skills to apply them to real problems in their current work domains.

Graduates who enjoy Mathematics and problem-solving with a focus on real-world problems.

Graduates who are interested in developing their advanced statistical and computing skillsets to master areas such as statistical inference and machine learning.

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.mcdonnell@dkit.ie