Higher Diploma in Data Analytics

Maynooth University (HDDSA)
Key Programme Details
Award

Higher Diploma

NFQ Level

Level 8 About NFQ

Delivery Method

Online, Classroom, Blended

Mode

Full Time

ECTS Credits

60

Department

Department of Mathematics and Statistics

General Information
Contact

Rafael de Andrade Moral

Email

datasciencepgrad@mu.ie

Phone

017083914

Address

Department of Mathematics and Statistics
Maynooth University
Maynooth, Co. Kildare

Role

Programme Coordinator

Important Dates
Application Deadline

01/09/2020

Start Date

07/09/2020

End Date

11/06/2021

About this Course

***Extended Application Deadline until Monday 31st August***
Graduates with Data Science skills are in short supply and the skill set is in high demand. Moreover, the Data Analytics jobs market is expanding in Ireland. Data Analytics skills are needed in many activities, such as weather forecasting, scientific research, insurance calculations, stock market prediction, quality control, banking, among others. This is why jobs are available in any industry or sector that collects data, ranging from IT to Healthcare, Finance, Food science, Governmental Bodies, and Travel.

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 understand the implications of models.

Objectives

Upon completion of the course, students will be able to
- understand key concepts in Data Science and Analytics
- extract insight from large datasets
- read and write code in different programming languages to analyse different types of datasets
- produce and interpret meaningful data visualisations
- carry out data analysis and report on findings

Entry Requirements

A level 8 degree in any subject with some mathematical content. Applicants can also apply via Recognition of Prior Experiential Learning.

Long Description

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 and social sciences, and business domains.

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 course has strong links with industry and includes a guest lecture series with a range of speakers from companies renowned for driving advances in data analytics in their respective industries. It also includes a work placement preparation module, so as to provide career readiness to the students.

Why Choose This Course

The Higher Diploma in Data Analytics at Maynooth University, funded under the Springboard+ initiative, will provide graduates with the skillset needed to extract valuable insights from large amounts of data, enabling strategic planning and data-driven decision making.
This Higher Diploma will produce graduates who have the knowledge and skills to collect, process, analyse and visualise data in order to extract useful information, explore statistical patterns, test hypotheses, and understand the implications of models.
This is a one-year full-time programme for students who have completed a Level 8 degree in any relevant subject with some mathematical content. There is also the potential to enter this programme through recognition of prior experiential learning (RPEL). Graduates of this programme will typically find employment all across the ICT sector, but the skills developed over the course of this programme are transferable to many careers and working environments across all sectors of the economy.

Career Opportunities

Graduates with Data Science skills are in short supply and the skill set is in high demand. Moreover, the Data Analytics jobs market is expanding in Ireland. Data Analytics skills are needed in many activities, such as weather forecasting, scientific research, insurance calculations, stock market prediction, quality control, banking, among others. This is why jobs are available in any industry or sector that collects data, ranging from IT to Healthcare, Finance, Food science, Governmental Bodies, and Travel.

Timetable Info

First 3 weeks: approx. 30 hours per week
Remainder: between 15 and 20 hours per week

Delivery Location

Primarily on campus at Maynooth University but this course will have extended online elements due to the ongoing Covid-19 crisis.

Delivery Notes

Blended
Lectures and labs/practical sessions

Admissions Contact Details
Contact Person

Rafael de Andrade Moral

Phone

017083914

Email

datasciencepgrad@mu.ie

RPL Information

Applicants also have the opportunity to apply through Recognition of Prior Experiential Learning. Please visit https://www.maynoothuniversity.ie/graduate-studies/recognising-professional-experience for further information and to download the RPEL form for inclusion in your application.

Application Procedures

Please upload the following documentation along with your application submission:

- Degree certificate and final transcript. Applicants looking to apply via RPEL can indicate this in their application, and should upload a completed RPEL form with their application submission. You do not need to include a PAC Number in this form.
- Proof of applicant category, e.g proof of employment, proof of DEASP payment, etc.
- Proof of nationality (unless in receipt of a DEASP payment)
- Evidence that you have been resident in an EU/EEA/Swiss state for three of the last five years (unless in receipt of a DEASP payment)

Media
Higher Diploma in Data Analytics | Maynooth University

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