Data Analytics
This online course will help you analyse and understand the large data sets that are regularly being created via the huge growth in freely available online information. There is an increasing demand for graduates with these valuable skills in a wide range of industries, and currently a shortage of qualified graduates. There are no lectures to attend as the courses are delivered completely online.
| Award Name | Special Purpose Diploma (Level 9 NFQ) |
|---|---|
| NFQ Classification | Special Purpose |
| Awarding Body | National University of Ireland |
| NFQ Level | Level 9 NFQ |
| Award Name | NFQ Classification | Awarding Body | NFQ Level |
|---|---|---|---|
| Special Purpose Diploma (Level 9 NFQ) | Special Purpose | National University of Ireland | Level 9 NFQ |
Duration
1 year part-time online
Entry Requirements
For entry to the Professional Diploma in Data Analytics (LEVEL 9), students must have obtained an undergraduate (NFQ Level 8 ) or masters degree to standard 2:1 in a subject with some quantitative elements.Those with a lesser qualification award and/or no numerate subject degree, but with substantial industry experience related to the area, or relevant professional qualifications, will also be considered on a case by case basis.
Careers / Further progression
Data Analysts are in strong demand from industry; those who are successful in completing the course are highly employable in fields as diverse as pharmaceuticals, finance and insurance, as well as cloud computing. Some examples of prospective employers include:
ICT companies (e.g., Google, eBay, Meta, Amazon, Paddy Power)
The pharmaceutical industry (e.g., Janssen, MSD, GSK)
The financial services industry (e.g., Bank of Ireland, AXA, EY, Accenture, Deloitte)
Students who perform well on the Professional Diploma may apply to progress to our online MSc Data Analytics
Further information
NEXT INTAKE: 2024/2025 September.
ProfDip Data Analytics (F057) Part Time
EU/NONEU fee per credit - € 209.6
***Fees are subject to change
These programmes are paid per credit. Further information is available on the UCD Fees website.
How to apply?
The following entry routes are available:
Professional Diploma Data Analytics PT (F057)
Duration 1 Years
Attend Part Time
Deadline Rolling*
* Courses will remain open until such time as all places have been filled, therefore early application is advised
ProfDip Data Analytics
Graduate Taught (level 9 nfq, credits 20)
Students will be given videos, online demonstrations, and interactive games to enhance their learning, with regular feedback and interaction with course tutors. This provides flexibility to students who can learn wherever they like at a pace that suits them. Students will attend a UCD exam centre at the end of each trimester for exams.
For detailed information about the programme see: programme website or email dataanalyticsonline@ucd.ie with any queries.
There is a huge ongoing growth in demand for graduates with these valuable skills in a wide range of industries, and currently a shortage of qualified graduates.
Students will be given videos, online demonstrations, and interactive games to enhance their learning, with regular feedback and interaction via course tutors through the UCD website.
Who should apply?
Part Time option suitable for:
Domestic(EEA) applicants: Yes
International (Non EEA) applicants currently residing outside of the EEA Region. Yes
Stage 1 - Core
Inference for Data Analytics (online)STAT30280
Introduction to Data Analytics (Online)STAT40720
Data Programming with R (Online)STAT40730
Statistical Machine Learning (online)STAT40750
Related Programmes
MSc Data Analytics PT
F084 - MSc in Data Analytics (This Professional Diploma is identical in semesters one and two to the MSc, at which point the Professional Diploma ends and the MSc continues for a further 7 semesters/terms)
F140 - Mathematics for Data Analytics and Statistics (Foundation programme to equip those without the necessary mathematical background with these skills)
Demonstrate in-depth knowledge of the key skills required by a practicing data analyst, including data collection methods, statistical method development, knowledge and application of machine learning techniques
Ability to present technical material at a level appropriate for any audience
Proficiency in several data science programming languages including R, python, SAS, and C
The ability to create scientific visualisations to explore, summarise, and interpret complex datasets
Approach problems in an analytical, precise and rigorous way
Model a broad variety of real-world problems in a statistical framework
Laura Barnes
UCD School of Mathematics and Statistics
email: laura.barnes@ucd.ie
or dataanalyticsonline@ucd.ie
https://www.ucd.ie/mathstat/study/graduatestudy/dataanalytics/