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Master of Science (MSc) in Data Analytics

  • Overview
  • Course Content
  • Structure
  • Career Opportunities
  • Fees
  • Next Steps

Overview

 
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With increased availability of information about customer preferences and actions, production processes and supply chains, there is growing recognition of the economic returns from the use of big data and analytics. The Government’s Action Plan for Jobs 2013 sets out seven ‘disruptive reforms’ being prioritised with major potential to have a significant impact on job creation, to support enterprises or where Ireland can profit from a natural advantage or opportunity that presents itself in the economy.

One of these goals is to make Ireland a leading country in Europe for big data. This programme accommodates a wide audience of learners whose specific interests in data analytics may be either technically focused or business focused.

Either full time or part time, the programme is designed to facilitate learners with a statistics/computing/technology background who wish to upskill in this new and emerging area of Data Analytics. It will also be of interest to learners who have completed their undergraduate degree and wish to specialise in this area. It may be their preference to take the theory and practical modules only and not complete the dissertation. 

 Aims and Objectives

This is an innovative programme with an integrated delivery from end‐to‐end covering a wide range of data analytics topics. The programme aims to develop learners' knowledge of the theory and practice of Data Analytics necessary for them to secure employment and perform at postgraduate level in the areas of ICT /Data Analytics in a broad range of commercial, industrial and public sector environments. Graduates will have an in-depth knowledge of the practical and theoretical aspects of data analytics. The programme enables and supports learners in developing critical analytical skills and in applying theoretical concepts to the practice of data analytics.

The programme incorporates Personal & Professional Development (PPD) within modules to enhance the student’s employability, which will enable them to integrate seamlessly into an organisation by addressing skills such as leadership, self‐management and teamwork that are essential in the area of Data Analytics. It also comprises a Research Methods module integrated into the applied data analytics modules, focusing on literature review, research technique, and their application to real life situations, data sets and how applied research and entrepreneurship are linked. These modules will inform the learner’s Dissertation, which requires the production of an artefact.

The specific programme aims are as follows:

1. To enable learners to develop expert knowledge and analytical skills in current and developing areas of analysis statistics, and machine learning.
2. To provide learners with a deep and systematic knowledge of business and technical strategies for data analytics and the subsequent skills to implement solutions in these areas.
3. To facilitate the development by the learner of applied skills that are directly complementary and relevant to the workplace.
4. To identify and develop autonomous learning skills for the learner.
5. To develop in the learner a deep and systematic understanding of current issues of research and analysis
6. To enable the learner to identify, develop and apply detailed analytical, creative, problem solving and research skills.
7. Provide the learner with a comprehensive platform for career development, innovation and further study.

Entry Requirements

The minimum entry requirements for the MSc in Data Analytics are:

A minimum Second Class Level 8 Honours Degree (2.2) in a cognate discipline from a recognised third level institution or equivalent. 

In addition, for applicants whose first language is not English and who have not undertaken their undergraduate degree through English the following is required:

The minimum requirement for a non-native English speaker is greater or equal to B2+ in the Common European Framework of Reference for Languages for admission. Non‐EU applicants, residents outside Ireland/EU, must apply directly to the International Admissions Office at DBS. 

Course Content

The Master of Science (MSc) in Data Analytics has the following content:

Stage 1

Stage 2

Programming for Data Analysis, Processing and Visualisation

Statistics for Data Analytics

Data Storage Solutions for Data Analytics

Data Mining

Machine Learning

Applied Research Process for Data Analytics

Data Visualisation

Dissertation

 

Assessment Methods

The MSc in Data Analytics is an academic programme informed by the clinical and academic experience of the lecturers. Assessment is approached creatively with a range of assessment strategies including essay writing, in-class presentation, graded group dissertation and examination, module depending.

Instructions and guidelines for all assessment are clearly communicated to students.

Structure

The programme is structured in two sequential stages. Stage 1 is a taught component, contributing 60 credits. Stage 2 is a supervised dissertation, contributing 30 credits. The dissertation provides students with the opportunity to critically review the literature in any part of the taught syllabus.

Full-time

For full-time students, the taught component consists of six modules. Successful completion of the taught component stage allows you to move on to the dissertation stage.

Part-time

For part-time students, delivery of the programme is structured over four taught semesters. During each semester, students are typically required to attend lectures on two evenings per week and occasional weekend workshops

The course has six key components:

1. Class room lectures

2. Case Based learning

3. Practical Skills Sessions

4. Workshops

5. Tutorials

6. Individual and Group work

 

Career Opportunities

There is a global shortage of the skilled professionals required to fill direct high-end jobs in this area and the report, Assessing the Demand for Big Data and Analytics Skills, identifies measures to build up the Big Data and analytics talent pool in Ireland over the period up to 2020 in line with enterprise demand. The 21,000 potential job opportunities for skilled professionals could arise under the report’s high growth scenario, from both expansion and replacement demand in the period up to 2020 - comprising 3,630 for deep analytical roles and 17,470 for big data savvy roles.

Role types that may be suitable for graduates include:

Data Analysts/Engineers

Data Analytics Manager

Software Engineers

Hadoop Developers

 

 

Fees

The course fees for the next academic year are €8,900 for one year, and €5,500 per annum for two years for EU students. This covers the cost of tuition, registration and examinations.

Click here to view international fees. 

You can contact our Admissions Team who would be happy to discuss the options available for you.

Please note also that there is tax relief for Irish income tax payers at the standard rate of 20% on all fees exceeding €1,500 and up to €7,000. 

All QQI accredited programmes of education and training of 3 months or longer duration offered by Dublin Business School (DBS) are covered by arrangements under section 65 (4) (b) of the Qualifications and Quality Assurance (Education and Training) Act 2012 whereby in the event that DBS ceases to provide the programme, for any reason, after learners have started on that programme, Kaplan Inc., as guarantor, will refund the moneys most recently paid by or for the learner.   More details are included in the terms and conditions of learner admission to DBS (http://www.dbs.ie/terms-and-conditions) and on programme handbooks provided at induction.

Improve your employability

All of our postgraduate courses offer strong links with industry and the professional world and often carry accreditation from professional bodies. By choosing to study at postgraduate level, not only do you gain valuable skills and experience but you also demonstrate your determination to succeed in a chosen career. Far from being a postponement to employment, postgraduate study can help you progress further and faster in your chosen career. And, if you're not certain what direction you would like your future to take, further study can provide a secure and structured space to help you find out through exploring your strengths and interests.

Get your foot on the career ladder

A large number of our postgraduate programmes include a work placement option, giving you the opportunity to gain vocational experience, make valuable contacts and gain transferable skills. It is also worth considering that some postgraduate qualifications are essential requirements to getting on the career ladder.

Gain skills for success

During your undergraduate degree you will have developed a strong foundation of transferable skills. Postgraduate study will build on this base, giving you the opportunity to put these highly valuable skills in to practice. You will also gain invaluable practical working examples that you can go on to use at interview to set you apart from other candidates.

Visit Us

Open days are a great way to help you make your decision about DBS and learn more about the Master of Science (MSc) in Data Analytics. As well as experiencing our outstanding facilities, you'll have the opportunity to receive personalised advice from academics from your subject area, meet current postgraduate students and also have your questions answered on general subjects such as entry requirements, student support and the admissions process.

As this is an extremely specialised area of study advanced entry to any stage of the programme is not permitted.

Eligible applicants must hold a related science/technology/computing/business/finance degree (level 8, 2.2 or higher) granted by an institution recognised in the country where it operates. Advice on equivalence of overseas awards will be obtained from the NARIC Ireland and/or NARIC UK which provides advice on the academic recognition of a foreign qualification by comparing it, where possible, to a major award at a certain level on the Irish National Framework of Qualifications (NFQ).

Further Requirements are as follows:

1. A completed application form

2. Primary source verified degrees and transcripts

3. Copies of any other supporting material, such as results of exams, honours, awards, etc.

4. Evidence of proficiency in English Language, in cases where the language of instruction during the undergraduate studies was not English.

5. If English is not the applicant’s first language, and s/he has not undertaken a previous degree taught in English, and has no mechanism of demonstrating their level of English, he or she must sit and obtain greater or equal to B2+ in the Common European Framework of Reference for Languages or an equivalent test and scores as approved by DBS.

6. Test certificates should be dated within the last two years to be considered valid.

7. Students must have access to a suitable computer and broadband access to the internet.

In the unlikely event that the programme is oversubscribed by qualified applicants at any time, places will be given to those who applied first.

Students with Disabilities


Dublin Business School welcomes students with disabilities onto the MSc in Data Analytics, but asks that they consider their future career in the area relative to the requirements of working in the area. The College employs a Disabilities Coordinator based in the Student Services Department and appropriate supports in relation to teaching and assessment are put in place. The Library also offers a wide range of supports to learners with disabilities.
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Course overview

COURSE OVERVIEW 2018

Awarding Body: 
Quality & Qualifications Ireland (QQI)
QQI AWARD LOGO (1)
Award: Masters Degree
NFQ Level: Level 9
Award Title: Master of Science (MSc) in Data Analytics
Award Type: Major
Duration: 
Full-time: 1 year 
Part-time: 2 years

Contact Us

We are now accepting applications for programmes taking place in 2018. Contact our admissions team for more information

Email: admissions@dbs.ie
Phone: 01 417 7500
Opening times:
Monday to Friday
8:45am to 5:15pm

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