Master of Science in Data Science (CARLOW)

Institute of Technology, Carlow (CW_KCDAT_M)
Key Programme Details
Award

Major

NFQ Level

Level 9 About NFQ

Delivery Method

Classroom

Mode

Part Time

ECTS Credits

90

General Information
Contact

Geraldine Cawley

Email

springboard@itcarlow.ie

Phone

059 9175288

Address

Faculty of Lifelong Learning
Institute of Technology Carlow
Kilkenny Road
Carlow
R93 V960

Role

Springboard Administrator

Important Dates
Application Deadline

31/08/2021

Start Date

22/09/2021

End Date

31/08/2022

About this Course

This exciting MSc in Data Science NFQ Level 9 programme provides students with a comprehensive knowledge base and skillset to fulfil and succeed in a variety of roles within data science driven organisations. The programme is designed to meet current industry needs and provides students with a thorough theoretical and practical grounding in the analysis and utilisation of large data sets, together with experience of conducting data science development projects, thereby preparing graduates for positions of responsibility in the Big Data and IT industries.
As well as studying a range of taught modules reflecting the state-of-the-art and the expertise of our internationally respected academic staff, students will undertake a significant research and/or programming project to further enhance their skillset from the creation of a project proposal to the delivery and deployment of a significant data science project.
This innovative programme additionally will build on participants' professional and personal skills in areas such as presentation, communication and soft skills as well as data science development, integration and critical thinking around the design, implementation and deployment of data science solutions and systems in industry.
The aim of this programme is to provide students with an understanding and ability to critically evaluate and utilise data science, analytics and the associated processes, systems, algorithms, technologies and insights garnered, ethically, in appropriate contexts. The programme also focuses on current research in data science and enables students to review, critically assess and expand on this research.

Entry Requirements

Successful candidates must have either:
1) A second class honours level 8 primary degree (or equivalent) in Computer or Mathematical Sciences.
Or
2) A second class honours level 8 primary degree (or equivalent) with a strong numerate content (e.g. Engineering, Finance, Physics, Bioscience or Economics). In such cases the programme team must be satisfied that the numerate content is sufficient for entry to the programme and that applicants have an aggregate grade of a second class honours in appropriate modules.
Applicants who do not meet the above standard entry requirements will also be considered if they have an undergraduate degree (at Level 7 or higher) and a minimum of 5 years verifiable relevant industrial experience.
Applicants who do not have a primary degree will only be considered with a minimum of 10 years verifiable relevant industrial experience.

Long Description

This exciting MSc in Data Science NFQ Level 9 programme provides students with a comprehensive knowledge base and skillset to fulfil and succeed in a variety of roles within data science driven organisations. The programme is designed to meet current industry needs and provides students with a thorough theoretical and practical grounding in the analysis and utilisation of large data sets, together with experience of conducting data science development projects, thereby preparing graduates for positions of responsibility in the Big Data and IT industries.
As well as studying a range of taught modules reflecting the state-of-the-art and the expertise of our internationally respected academic staff, students will undertake a significant research and/or programming project to further enhance their skillset from the creation of a project proposal to the delivery and deployment of a significant data science project.
This innovative programme additionally will build on participants' professional and personal skills in areas such as presentation, communication and soft skills as well as data science development, integration and critical thinking around the design, implementation and deployment of data science solutions and systems in industry.
The aim of this programme is to provide students with an understanding and ability to critically evaluate and utilise data science, analytics and the associated processes, systems, algorithms, technologies and insights garnered, ethically, in appropriate contexts. The programme also focuses on current research in data science and enables students to review, critically assess and expand on this research.

Timetable Info

Classes for this course take place in the classroom during the DAYTIME on a part-time basis.
Timetable to be confirmed

Delivery Location

Institute of Technology Carlow
Kilkenny Road
Carlow
R93 V960

Delivery Notes

Classes for this course take place in the classroom during the DAYTIME on a part-time basis.

Application Procedures

Apply online at www.springboardcourses.ie

To complete your application process YOU MUST email Springboard@itcarlow.ie with the following
(1) A scanned copy of your EU Passport, or a scanned copy of your non-EU Passport with a copy of your Stamp 4 visa. You are not required to provide a copy of your Public Services Card to verify ID.
(2) A copy of your Curriculum Vitae.
(3) A copy of your Level 7 Degree/ Major Award or highest other qualification. Translated if not in English
(4) A scanned copy of a recent payslip if employed showing your PPSN, or a scanned copy of a recent payment slip if in receipt of Jobseekers Allowance/ benefit, or a copy of a recent Bank Statement showing receipt of a different, eligible, Department of Employment Affairs & Social Protection, or a letter from your Accountant confirming that are Self-employed, or an Affidavit signed by you and the appropriate third-party confirming that you are a Homemaker.

Please note: When sending jpgs they must be attachments to your email, -not jpgs within emails.