24/08/2017

28/08/2017

Data analytics/science is the science of extracting insight from large amounts of raw data in order to enable better understanding of the processes that created it and so help in analysis, theory exploration and decision making. Similar techniques can be applied in the natural science, social science and business domains.

In recent years the falling cost of digital storage, the increasing move towards online information processing and other related technological developments have made it possible to collect massive amounts of data about natural phenomena (e.g. the climate, DNA) and human behaviour (e.g. social studies, business customers, clients, users and associated processes). Data analytics/science is the science of extracting insight from large amounts of raw data in order to enable better understanding of the processes that created it and so help in analysis, theory exploration and decision making. Similar techniques can be applied in the natural science, social science and business domains.

This inter-disciplinary course is designed for students with a level 8 degree in any relevant subject to give them the knowledge and skills to collect, process, analyse and visualise data in order to extract useful information, explore statistical patterns, test hypotheses, and explore the implications of models. Students will gain skills in programming, statistics and databases, followed by an advanced module on statistical machine learning. The course includes material on the social and ethical consequences of the use of data and the implications for business and government. A case study module highlights the use of data analytics in applications such as crime pattern analysis, house price prediction, modelling of epidemics and the analysis of textual data. A capstone project requires students to implement their acquired knowledge in a practical real-world application.

The objective of this course is to prepare students for the expanding Data Analytics job market.

A level 8 degree in any subject with some mathematical content.

Data analytics/science is the science of extracting insight from large amounts of raw data in order to enable better understanding of the processes that created it and so help in analysis, theory exploration and decision making. Similar techniques can be applied in the natural science, social science and business domains.

The Data Analytics programme is a new, purpose-designed course which has been carefully designed to address industry needs. The course is a collaboration between Departments of Mathematics & Statistics, Computer Science and the National Centre for Geocomputation.
This inter-disciplinary course gives students the knowledge and skills to collect, process, analyse and visualise data in order to extract useful information, explore statistical patterns, test hypotheses, and explore the implications of models. Students will gain skills in programming, statistics and databases, followed by an advanced module on statistical machine learning. The course includes material on the social and ethical consequences of the use of data and the implications for business and government. A case study module highlights the use of data analytics in applications such as crime pattern analysis, house price prediction, modelling of epidemics and the analysis of textual data. A capstone project requires students to implement their acquired knowledge in a practical real-world application. A work placement module provides experience in putting the skills learned into practice.

Semester 1 modules:
Programming for data analytics
R for data analytics
Statistical methods for data science
Databases

Semester 2 modules:
Statistical machine learning
Case studies in data science & analytics
Data analytics project
Critical data studies
Topics in data analytics
Placements preparation

The Higher Diploma in Data Analytics is a one-year full-time programme for students who already have a level 8 qualification in a subject other than computer science or statistics. No previous knowledge of computing or statistics is required. Students will learn how to deal with the increasing quantities of data available in today’s world. They will gain skills in programming, statistics and databases, explore case studies and complete a significant data analytics project. Placement preparation is also provided.

In partnership with the Placement office and the Careers Development Centre on campus, the programme includes preparation for placement including CV writing, interview skills, team project work, project management and evaluation.

The Data Analytics jobs market is expanding in Ireland. Jobs are available in any industry or sector that collects data, ranging from IT, to Healthcare, Finance, Food science and Travel.

Campus/Classroom

Campus/Classroom

Catherine Hurley

Department of Mathematics and Statistics, Logic House, South Campus, Maynooth University, Maynooth, Co. Kildare

01-7083914

catherine.hurley@nuim.ie

Maynooth University has mechanisms to allow entry to applicants who do not meet the normal requirements, but who are, for other reasons, deserving of admission. Admission may be based on the applicants experience or other non- accredited learning. Other applicants with educational qualifications close in equivalence to the expected requirements may also be admitted.

To complete your online application, you must upload a copy of the parchment and/or transcript of your degree, if this was taken at a university other than the National University of Ireland Maynooth (Maynooth University). These must show the grade achieved and the date of conferral.

Applicants must be available to start the course on 28th August 2017.

http://www.maynoothuniversity.ie/mathematics-and-statistics/springboard