This Certificate in Data Preparation and Visualisation micro credential is designed in response to industry feedback for the provision of accredited professional development opportunities for those working in IT or technical roles.
Extensive exploratory data analysis and proper data preparation are a crucial first step in any data analysis process. The aim of this micro credential Certificate programme is to provide the learner with an in-depth understanding of the rationale for data exploration and the methods used to explore data programmatically with Python, a high level, low barrier, programming language.
The student also learns the importance of feature selection and dimensionality reduction and the bias-variance trade-off, the importance of the correct encoding of data and the usefulness of feature engineering as a means of representing complex functional relationships to machine learning models. The module also deals with the theory and application of data visualisation methods and transmission media, tailored for diverse audiences.
By incorporating basic programming skills in a hands-on practical integrated manner enables the learner’s ability to program but also reinforces the inseparable nature of programming within the field of Data analytics. This module also includes what is essentially an embedded ‘bootcamp’ of basic programming concepts to ensure a level playing field for all learners (facilitated through the use of a low entry barrier language: Python).
On completion of the programme learners should have knowledge, skill and competence in:
In addition to the core programme content, learners will develop a range of transversal development skills which will include; critical analysis, advanced evaluation, problem solving and communication skills.
For September 2025 the course will be offered on an evening/weekend blended learning basis through Springboard+. Typically learners will attend two evenings per week (online) plus 1-2 Saturdays (on campus).
All students will be introduced to the CCT online learning environment as part of the induction to the programme and will have access to further support as required.
Online activities can include live or pre-recorded lectures, independent learning and assessment activities such as research tasks, discussion forums, simulations, quizzes and e-portfolio work along with online group activities such as live classes, group project work, virtual labs and tutorials. Completing the online elements of the programme each week is essential to successfully complete the programme. On campus activities can include small group tutorials, labs, project supervision, problem solving case studies, library research and seminars.
Assessment is 100% continuous assessment and will comprise of three assignments to be completed throughout and at the end of each semester. Industry initiated real-world problems are used as the context for planning and designing assessment solutions, as well as being an aid for problem solving sessions. Summative assessment is a blend of integrated assessment and module specific assessment utilising both group and individual work, while formative assessment is pipelined into module delivery and feedback, so as not to add to the assessment burden of students.
The direct entry route to the Certificate in Data Preparation and Visualisation requires applicants to evidence numerate, technical and analytical ability to a minimum of NFQ level 8 standard.
The following are accepted as appropriate evidence for direct entry:
a. An NFQ Level 8 major award, or higher, in the discipline areas of ICT/Computing, Business, Science or Engineering or cognate discipline
or
b. An NFQ Level 8 major award, along with relevant experience in the area of Data Analytics and/or professional certification, may also be considered
In both scenarios presented above, applicants will also be required to evidence ability in the application of mathematical concepts such as algebra, or spreadsheet analysis and formulas, database knowledge, for example, to a level 8 standard. This is essential to demonstrate applicants numerate, technical and analytical ability required to ensure capacity for the extent of mathematical and technical content related to the programme.
This programme is designed for individuals who have previous knowledge in computing, analytics or similar through professional experience and/or educational qualifications. This programme is not suitable for individuals with only basic computer literacy.
Applicants whose first language isn’t English must demonstrate a minimum competency in the English Language of CEFR B2+.
Applications are also welcome from individuals who do not meet the standard entry requirements but wish to apply for entry based on prior learning (RPL) or prior experiential learning (RPEL). The College will thoroughly assess applications received through RPL and RPEL to ensure that candidates are able to evidence learning to an appropriate standard – normally the framework level equivalent to the direct entry qualifications requirement and demonstrate potential to succeed and benefit from the programme. Applications submitted on this basis will be assessed in line with the College RPL policy.
All applications for admission onto this programme should include:
Those who are in employment/working :
For eligible applicants who are currently in employment/working 50% of the tuition fees will be covered by the HEA through Springboard+ and the remaining 50% is payable by the student or their employer.
The Course Tuition Fee is €840 so €420 euro is payable by the student or their employer
Recent Graduates:
2024 Graduates who will have successfully completed a relevant level 8 Degree programme before September will be eligible to apply for the funded course. 50% of the tuition fees for the full-time course will be covered by the HEA through Springboard+ and the remaining 50% is payable by the student or their employer.
The Course Tuition Fee is €840 so €420 euro is payable by the student
Those who are unemployed, formerly self-employed and ‘Returners’:
The Springboard+ funded course is free for eligible applicants who are unemployed, formerly self-employed or who are classified by Springboard+ as ‘Returners’ or ‘Homemakers’.
Further information:
Please see this link on the Springboard Courses website for more detail on funding eligibility and also this link on the Springboard Courses website detailing documents that are acceptable as evidence of eligibility.
Application for this Micro credential Certificate in Data Preparation and Visualisation will open on June 3rd via the Springboard Courses website.
We are hosting a number of events in the lead up to the next academic year to give prospective students the opportunity to find out more about their course and the College. At the moment these events are virtual and you can pre-register here.
You can also book a one to one appointment with an Admissions Advisor in person or online via Zoom by email.
All QQI accredited programmes of education and training of 3 months or longer duration are covered by arrangements under section 65 (4) of the Qualifications and Quality Assurance (Education and Training) Act 2012 whereby, in the event of the provider ceasing to provide the programme for any reason, enrolled learners may transfer to a similar programme at another provider, or, in the event that this is not practicable, the fees most recently paid will be refunded.
