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Data Analytics

MSc Data Analytics
Academic Year 2020/2021
Graduate Taught (level 9 nfq, credits 90)
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 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

More detailed information about the programme is available on the programme 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

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. The Applications Committee will have to assess all the modules taken during an applicant's degree and individual results to check suitability. A rough guide to the mathematics we expect you to know on entry is available here: Self Assessment Quiz

An alternative entry route to the MSc is to enroll in the 20 credit Professional Diploma in Data Analytics and gain a grade point average of 3.08 or higher in the modules that make up this progamme (the Professional Diploma is made up of the first 2 semesters / first 4 modules, of the MSc programme).

Duration

3 Years Part-Time.

Number of credits

90

Careers or further progression

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)

Further enquiries

Contact Number: +353 (0)1 716 2452

Subjects taught

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.

Stage 1 - Option
Adv Data Analytics (online)
STAT30280
Introduction to Data Analytics (Online)
STAT40720
Data Programming with R (Online)
STAT40730
Multivariate Analysis (Online)
STAT40740
Statistical Machine Learning (online)
STAT40750
Data Prog with C (online)
STAT40780
Predictive Analytics I (online
STAT40790
Data Prog with Python (online)
STAT40800
Stochastic Models (online)
STAT40810
Monte Carlo (online)
STAT40820
Adv Data Prog with R (online)
STAT40830
Data Prog with SAS (online)
STAT40840
Bayesian Analysis (online)
STAT40850
Time Series (online)
STAT40860
Adv Bayesian Analysis (online)
STAT40950
Stat Network Analysis (online)
STAT40960
Machine Learning & AI (online)
STAT40970

Comment

Vision and Values Statement
This programme is aimed at students who wish to develop a career or further studies in data analytics and related disciplines. We encourage our students to have a passion for analysing large data sets, and to be autonomous learners who have a creative and critical approach to data analytics. We aim to provide a learning environment that will encourage students to constructively solve data problems in real-world situations, using a variety of software, and to tailor such solutions to individual data sets as they arise. Online learning is a key feature of the programme, and we provide online videos and discussion boards, always backed-up by individual feedback from lecturers and tutors. At the most advanced levels of the programme, students are encouraged and expected to use and apply cutting-edge techniques from the latest research in their work. As a result of this approach to learning, the modules are assessed using a variety of tools including online assessment, individual project work to examine software-based skills, and written examinations to test mathematical ability.

Related Programmes
Professional Diploma Data Analytics PT

F057 - Professional Diploma 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

How to apply?
The following entry routes are available:
MSc Data Analytics PT (F084)

Duration
3 Years

Attendance
Part Time

Deadline
Rolling *

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

Course fee

MSc Data Analytics (F084) Part Time
EU/NONEU fee per credit - € 134.8

***Fees are subject to change

Tuition fee information is available on the UCD Fees website.

Enrolment and start dates

Next Intake: 2020/2021 September

Remember to mention gradireland when contacting institutions!