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Data Analytics

This 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. This is an exceedingly valuable skill and in strong demand from employers. We see Data Analytics as a subject at the crossroads between statistics and computer science, and our Online Professional Diploma and Online MSc contain elements of both. We will give you the tools to apply these advanced skills to maximum effect in any work-related environment. There are no lectures to attend. 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

The Online MSc in Data Analytics covers 18 5-credit modules, two per semester over 9 semesters or 3 years, of which the Online Professional Diploma in Data Analytics covers the first 4. This first year is designed to introduce you to statistical and mathematical concepts in Data Analytics and Data Mining, and to get you started on programming with data. The second year is split between understanding the theory behind statistical and mathematical models for data via predictive analytics, and dealing with data sets at scale using Python and multivariate techniques. The final year covers some advanced methods Monte Carlo, Bayesian analysis, time series data, and complex stochastic models. A provisional list of topics is as follows:
•Intro to Data Analytics and Advanced Data Analytics (covering the main statistical and computational techniques)
•Computing modules on: Monte Carlo, R, C, Java, Python and SAS
•Statistics modules: Predictive Analytics, Multivariate Analysis, Time Series, Stochastic models.

For more information download the course brochure from the course webpage (link available below)

Entry requirements

For entry to the Professional Diploma in Data Analytics (LEVEL 9), students must have obtained an undergraduate or masters degree to standard 2:1 in a subject with some quantitative elements.

Those without this requirement but with substantial industry experience related to the area, or relevant professional qualifications, will also be considered on a case by case basis.

A rough guide to the mathematics we expect you to know on entry is available here: Self Assessment Quiz


Professional Diploma Data Analytics PT (F057)
Duration 1 Years
Attendance: Part Time

Number of credits


Careers or 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. Prospective employers include any company that requires detailed, robust analysis of data sets; some examples include:

• ICT companies (e.g. Google, eBay, Facebook, Amazon, Paddy Power),
• The pharmaceutical industry (e.g. Jansen, Merck, 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 transfer to out online MSc Data Analytics.

Further enquiries

Contact Name: Simon Williams
Contact Number: +353 (0)1 716 2580

Subjects taught

The Online Professional Diploma in Data Analytics covers 4 5-credit modules. These modules are designed to introduce you to statistical and mathematical concepts in Data Analytics and Data Mining, and to get you started on programming with data.

Stage 1 - Core
STAT30280 Adv Data Analytics (online)
STAT40720 Introduction to Data Analytics (Online)
STAT40730 Data Programming with R (Online)
STAT40750 Data Mining (Online)


ProfDip Data Analytics
Graduate Taught (level 9 nfq, credits 20)

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)

Application date

Deadline: Rolling *
* Courses will remain open until such time as all places have been filled, therefore early application is advised.

Enrolment and start dates

Next Intake: 2017/2018 September

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