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Overview
Data Analytics Students at University College Dublin 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
Career
- 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:
Get more details
Visit official programme websiteProgramme Structure
Courses included:
- Data Analytics
- Multivariate Analysis
- Predictive Analytics
- Bayesian Analysis
- Machine Learning & AI
Key information
Duration
- Part-time
- 36 months
Start dates & application deadlines
- StartingApply anytime.
More details
- Applications are assessed on a rolling basis and courses will close once they are filled.
Language
English
IELTS 6.5
TOEFL® IBT 90
Credits
90 ECTS
Delivered
Online
Disciplines
Data Science & Big DataAcademic requirements
GPA Upper Second Class
English requirements
IELTS 6.5
TOEFL® IBT 90
Other requirements
General requirements
- Students must have obtained an NFQ Level 8 undergraduate degree in a numerate subject to standard 2:1.
- Those with a lesser qualification award and/or no numerate subject degree, but with equivalent experience in industry, or relevant professional qualifications, will also be considered on a case-by-case basis. All applications are considered individually.
Tuition Fee
To alway see correct tuition fees
-
International
4020 EUR/yearTuition FeeBased on the tuition of 134 EUR per credit during 36 months. -
EU/EEA
4020 EUR/yearTuition FeeBased on the tuition of 134 EUR per credit during 36 months.
Funding
Studyportals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.
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