Data Analytics

ProfDip Data Analytics
Academic Year 2020/2021
Graduate Taught (level 9 nfq, credits 20)

The MSc and Professional Diploma in Data Analytics from the UCD School of Mathematics and Statistics will help you to analyse and understand the large data sets that are being created via the huge growth in online information. The value of these data sets is being increasingly recognised in business circles, with many companies seeking to recruit individuals with skills in data analytics to extract the valuable insights contained therein. Data Analytics is at the crossroads between statistics and computer science, and our courses contain elements of both. We will give you the tools to apply advanced skills from these fields to maximum effect in any work-related, "big data", environment. There are no lectures to attend as the courses are delivered completely online. Students will attend UCD at the end of each semester for exams.

For detailed information about the programme see: programme website.

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

Programme Outcomes
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.

Demonstrate strong proficiency in computational methods, including computer programming and scientific visualization

Model real-world problems in a statistical framework

Use the language of logic to reason correctly and make deductions

Approach problems in an analytical, precise and rigorous way

Ability to present technical material at a level appropriate for the audience

Ability to present technical material at a level appropriate for the audience

Approach problems in an analytical, precise and rigorous way

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.

Demonstrate strong proficiency in computational methods, including computer programming and scientific visualization

Model real-world problems in a statistical framework

Use the language of logic to reason correctly and make deductions

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.

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
Adv Data Analytics (online)
STAT30280
Introduction to Data Analytics (Online)
STAT40720
Data Programming with R (Online)
STAT40730
Statistical Machine Learning (online)
STAT40750

Credits

20

Duration

1 year part-time

Fees

ProfDip Data Analytics (F057) Part Time
EU/NONEU fee per credit - € 182.8

***Fees are subject to change

Tuition fee information is available on the UCD Fees website.

Enrolment dates

Next Intake: 2020/2021 September

Post Course Info

Careers & Employability
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., Janssen, 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.

More details
  • Qualification letters

    Prof Dip

  • Attendance type

    Part time

  • Apply to

    Course provider