Applied Data Science & Analytics / Eolaíocht Sonraí Fheidhmeach ┐ Anailísíocht

The minimum entry requirement is a Second Class Honours Grade 2 (GPA 2.5 or equivalent), in a NFQ Level 8 Degree in Computing, Science, Engineering, Business with IT, or equivalent qualification.

The acceptance of candidates with Third Class Honours degrees and appropriate work experience and industrial certification on this course will be allowed provided there is evidence that the candidate can cope with the learning objectives of the course.

Applicants will be requested to submit the following information to enable us score and rank applicants in order of merit

  • A Curriculum Vitae
  • Copy of your level 8 award, transcripts for each year showing modules studied and classification of the award.  Where transcripts are not in English, you must provide a copy of the original language documents and certified English translations.
  • You will also be asked to answer five questions relating to your experience in working with data, statistics, interest in the course etc. We will email the template for completion on receipt of your online application.
  • If English is not your first language you will need to provide evidence of your English language proficiency as detailed on our website.  Applicants for this programme should have a minimum IELTS (Academic Version) English Proficiency of 6.5 overall (or equivalent).

GradIreland badge indicating shortlisting for course of the year

 

Since its launch in 2010, TU Dublin’s MSc in Applied Data Science and Analytics has run part-time and fully online, the first in Europe to do so at its inception. This immersive and transformative 2-year MSc is designed to accelerate your career in data science while fitting with a busy schedule.

Key Points

  • Geared towards professionals
  • High completion rates
  • High likelihood of peer-reviewed publications from course work
  • International network of students
  • Alumni network working in senior data science roles

The course has gained a significant reputation for its high quality, practical approach and relevance to industry contexts. Modules are designed around a data science methodology, allowing integrated coursework that emphasises both mathematical rigour, and data science models that generate actionable insights.

It is ideal for individuals working with, or with access to, data in a real context that allows project work to bring relevance to their day job. The course has attracted cohorts of students that are highly motivated and work to a high standard. It was shortlisted for Grad Ireland’s Post Grad of the Year awards a number of times. Enrolment numbers are kept small to maintain the quality of the course.

While 83% of our graduates live in Ireland, we have had graduates complete the MSc from Canada, Germany, Greece, India, Malta, Netherlands, South Africa, Thailand, UK, USA and Zimbabwe. The average age of participants is 38, evidencing a teaching practice and delivery mode that successfully targets continuing education and lifelong learning. The majority of students have some experience working with data and are looking to upskill by acquiring a deeper theoretical understanding and practical experience of working in a data science discipline.

Graduates are working as data scientists across a variety of industry sectors and companies including Ericsson, IBM, Microsoft, PayPal, Intel, O2, Vodafone, Aer Lingus, Ryanair, Emirate Airlines, Dublin Airport Authority, GlaxoSmithKline, Mallon Technologies, Bank of Scotland, Arvato Finance Solutions, Sky Ireland, Eir, VHI Healthcare, United Healthcare Group, Accenture, SAP, FBD Insurance, Deutsche Bank, Ulster Bank, IBM and many others. Those working in the public sector included employees with MABS, GMS Payments Board, Dun Laoghaire – Rathdown Public Library Service, Dublin City Council, Intelligent Transport Systems, Higher Education Institutions and An Garda Síochána.

The course focuses on the knowledge and skills to select, apply and evaluate data science and big data analytics techniques to discover knowledge that can add value to a company. Students will gain both an in-depth theoretical understanding and practical hands-on experience, including implementing novel and emerging techniques. Participants will be kept abreast of current research and state of the art in data science-related topics. Details of the modules are given below.

For further detailed information in relation to this course, please see the dedicated programme website here.

 

IT Requirements: A HIGH spec (i.e. able to run Win 10, an AV solution and Office comfortably. Be able to use Wi-fi and camera to attend online classes, use other hardware intensive software such as Adobe Cloud Premium suite, Visual Studio, AutoCAD, ProEng, so needs high RAM, larger SSD, Graphics acceleration, etc.)

Please search for the TU Dublin offer on the HEA website www.heanet.ie/store

 

Graduates from this programme are equipped for employment in sectors where data analysis is a critical component, such as the insurance, retail, pharmaceutical, biotechnology, business, travel, telecommunication, government, and intelligence sectors.

Following successful completion of this course, graduates have taken up data analytics jobs with Accenture, SAP, FBD Insurance, Deutsche Bank, IBM, Eircom, Emirate airlines and PayPal, while one graduate has started his own analytics consultancy firm. Many students registered on this stream were already working in data analytics, or aim to start a data analytics function with their current employer.

Former students come from a variety of industry sectors and companies including:

  • Ericsson
  • IBM
  • Microsoft
  • PayPal
  • Intel
  • O2
  • Vodafone
  • Aer Lingus
  • Ryanair
  • Dublin Airport Authority
  • GlaxoSmithKline
  • Mallon Technologies
  • Bank of Scotland
  • Arvato Finance Solutions
  • Samba Financial Group (India)
  • Sky Ireland
  • VHI Healthcare
  • United Healthcare Group
  • Nathean Technologies
  • Compass Informatics 
  • MTT

Year 1 Semester 1

  • Business Intelligence
  • Data Mining Algorithms

Year 1 Semester 2

  • Data Pre-processing and Exploration
  • Data Science Applications

Year 2 Semester 3

Electives :

  • Text Mining and Web Content Mining
  • Geospatial Data Mining and Knowledge Discovery
  • Programming for Big Data
  • Statistics
  • Multimedia Mining

* Two electives must be selected

Year 2 Semester 4

  • MSc Research Project
  • Online Year 1: Tuesday and Wednesday 6pm-10pm.
  • Online Year 2: Wednesday and Thursday 6pm-10pm.

All classes are recorded

**Please note that class timetables and modes of delivery are indicative and may be subject to change, depending on public health advice**

Click here to apply 

Closing date 18th June. Programmes will remain open for applications beyond this date, subject to availability.

See here for further info on how to make an application https://www.tudublin.ie/study/part-time/how-to-apply/ 

My job involves a lot of complex analysis, and because of the practical nature of the course I have learned how to make complex analytics more consumable to a wider audience. As a student, I was really busy, but on projects that were interesting to me. I use the analytics and documentation skills I learned on the course every day.
The course teaches students how to clearly present a problem, and using analytics better understand the problem. This is a key skill in industry as it helps shape better solutions and better products. I have now a broader knowledge base and am better prepared when asking questions around analytics and the desire for more understanding of how a product is used.

The key differentiating factor is this course is that it's delivered remotely, so this made it ideal for me as a working mum. I was able to get an education and all the support I needed without having to sacrifice family time. When I was studying, my husband had to travel, and we have a young family. The remote nature of the course really worked for both my family needs and my educational needs. Even though the course was remote, we still had a great connection online with everyone in the class. When I couldn’t make the lecture, the recordings were uploaded straight away, and I had access to the material the following morning. I would certainly recommend this course

Niambh Scullion
Graduate of Master of Science in Computing (Applied Data Science & Analytics)

TU Code

TU253R

Level

Level 9

Award

Master of Science

Duration

2 years

Course Type

Postgraduate

Mode of Study

Part Time

Method of Delivery

Online

Commencement Date

September 2021

Location

Blanchardstown

Fees

€4,250 per year

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