Higher Diploma in Science in Computing (Data Analytics) - ICT SKILLS/SPRINGBOARD+Online conversion course for graduates of Level 8 programmes. Applications now open for January 2020 start.
Discipline: Computer Science and Applied Physics
Location: Galway - Dublin Road
NFQ Level: 8
Programme Duration: Two years
Mode of Study: Online delivery
Entry Requirements: Level 8 Honours Degree (or equivalent if earned outside the EU - see www.qqi.ie).
A 10% contribution (750 Euros) is required from Employed applicants. Free to Unemployed applicants.
- You are a Level 8 Graduate from a non-computing background who wishes to enter into a career in computing.
- The aim of the course is to provide you with a broad knowledge of computing, with a specialisation in data analytics.
- This will enable you to apply data analysis techniques to the topics in your original degree.
- It will also provide you with a foundation on which you can develop your skills in the more traditional areas of computing.
- This course is Fully Online.
The course covers such skills as automating manual spreadsheet-oriented data analysis processes, converting large data sets into actionable information, and creating web-based dashboards for visualising data.
The subjects undertaken are as follows:
- Data Representation and Querying [5 credits at Level 8] In this module students will investigate and operate the protocols, standards and architectures used in representing and querying the data that exists across the internet.
- Programming and Scripting [10 credits at Level 8] An in-depth introduction to computer programming and scripting.
- Fundamentals of Data Analysis [5 credits at Level 8] In this module, students learn about the basics of data analysis and its underlying mathematical concepts.
- Computer Architecture and Technology Convergence [5 credits at Level 8] This module covers the basic principle of traditional computer design and highlights current trends in mobile and pervasive computing architectures.
- Computational Thinking with Algorithms [5 credits at Level 8] This module provides detail of algorithm design and the computational problem solving process using programming libraries and application programming interfaces (APIs).
- Programming for Data Analysis [10 credits at Level 8] In this module, students develop their programming skills towards the effective use of data analysis libraries and software.
- Object Oriented Software Development [5 credits at Level 8] This module provides an introduction to programming (using an Object-Oriented approach) and assumes little or no previous experience in programming.
- Machine Learning and Statistics [5 credits at Level 8] A practical look at the most popular algorithms used in machine learning and the analysis of stochastic processes.
- Web Applications Development [5 credits at Level 8] This module is focused on the development of practical skills in the area of web applications.
- Advanced Databases [5 credits at Level 8] This module presents the theory and practice relating to advanced database applications in areas such as Enterprise Data Management, and in the management and storage of non-relational data.
- Work Placement/ Project [5 credits at Level 8] Work placement is undertaken only by Unemployed applicants, otherwise a Project is undertaken. Such candidates will be assigned a dedicated academic supervisor for the duration of the project.
Data Analytics / Data Science is a growing area of employment, with significant future growth also anticipated.
This is well established in various national skills bulletins (e.g. Expert Group on Future Skills Needs).
A sufficient result on this course would qualify students to undertake Level 9 (Master) programmes.
To apply go to www.springboardcourses.ie
To complete your application process you must email firstname.lastname@example.org the following:
- A scanned copy of your EU Passport, or a scanned copy of your non-EU Passport with a copy of your Stamp 4 visa.
- A copy of your Curriculum Vitae.
- A copy of your Level 8 Degree/ Major Award or highest other qualification. Translated if not in English.
- One of the following:
- 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.
When sending jpgs they must be attachments to your email, -not jpgs within emails. Documents sent as ZIP files cannot be accepted - please send as individual documents.
Online. It is anticipated that a number of optional on-campus workshops at GMIT Galway campus may take place each term.
Students (employed or unemployed) can complete the course over 12 months (full-time) or 18 to 24 Months (part-time). The definition of full-time or part-time refers to the number of credits undertaken in one academic year, not to attendance as in either mode the course is fully online.
Part-time Mode: (January 2020 – May 2021): (18 months, can be extended to 24 months)
- Semester 1 (Jan 2020 - May 2020): [20 credits]
- Semester 2 (Sep -2020 Dec 2020): [20 credits]
- Semester 3 (Jan 2020- May 2021): [20 credits]
Full-time Mode: (January 2020 – May 2021): (12 months)
- Semester 1 (Jan 2020 - May 2020): [30 credits]
Semester 2 (Sep -2020 Dec 2020): [30 credits]
RPL applications will be considered from those holding a Level 7 who have significant work experience which would match the learning outcomes of a Level 8.
The Springboard+ Programme is operated by the Higher Education Authority on behalf of the Department of Education and Skills and is co-funded by the Irish Government and the European Union under the Euroepan Structural and Investment Funds Programme 2014-2020.
Graduate and Professional Development
Tel: +353 (0)91 742328
Springboard+ is co-funded by the Government of Ireland and the European Social Fund as part of the ESF programme for employability, inclusion and learning 2014-2020