QQI Level 8 Higher Diploma in Science in Data Analytics
Classroom - Daytime
Information and communication (including ICT)
Springboard+ Admissions DepartmentEmail Phone
Dublin Business School, 13 Aungier St.
Dublin Business School in conjunction with Microsoft Ireland, their Partner Network and other relevant industry partners have developed an intensive full-time Level 8 Graduate Conversion programme leading to a Higher Diploma in Science in Data Analytics award.
Ireland is likely to face an average increase in demand for high-level ICT skills of around 5% a year out to 2018 with the employment of ICT professionals anticipated to rise to just over 91,000.
This programme is commencing in March 2019 and will be full-time for one Academic year, which incorporates a credit-bearing industry based work placement.
Full schedule details will be confirmed closer to the start date.
The Higher Diploma in Science in Data Analytics will provide graduates with the theoretical and practical skills required to meet the demands of industry. The proposed programme will enable learners to apply those transferable skills developed as part of their original degree to specific IT and Data Analytics areas.
The current and projected skills shortages are increasing the demand for graduates with a skillset that embeds new technologies with existing established core computing skills. Use and implementation of technologies are changing fast and therefore so are the demand for specific technology skills. A strong core technology education will form a good basis upon which skills in the current and future cutting edge technologies can be built.
Course content will include:
• Databases and business applications
• Programming essentials
• Statistics for data analytics
• Data warehousing and business intelligence
• Programming for big data
• Tools for data analytics
This programme aims to provide graduates with the aforementioned skills, knowledge and competences in the area of data analytics.
In semester 1, participants will undertake a broad immersive set of modules which includes databases and business applications, programming, statistics for data analytics, data warehousing and business intelligence, programming for big data and tools for data analytics.
In semester 2, participants are equipped to take data visualization and communications, data and web mining, advanced data analytics and a credit-bearing industry based work placement.
The overall aim of the programme is to provide graduates with the underpinning academic knowledge to enhance their educational and employment opportunities and to achieve the award of a Higher Diploma in Science in Data Analytics.
In addition, a feature of the programme is the opportunity for the learner to engage in an industry related work placement if suitable. The plaement provides the participants to apply and demonstrate the learning and skills that have been developed in the taught element of the programme. This element provides learners with relevant work experience with an industry partner for a minimum period of three months. In addition to acquiring new skills, learners will apply and reinforce the knowledge and practical skills they have acquired during the taught element of the programme.
Specific skills that the proposed programme is preparing participants for include:
• Demonstrate a detailed knowledge and understanding of the methods and technologies for acquiring, interpreting and analysing big data
• Have knowledge of relevant statistical, mathematical and business tools employed to solve problems involving big data sets
• To be able to formulate and test hypotheses and experiments in the field of data analytics
• Critically interpret data analytical skills and technologies with a view to application in new circumstances
• Apply the scientific enquiry method to solve problems related to the data science field
• Act effectively both as an individual and a team member in a supervised work environment demonstrating technical and social proficiency in the manipulation of materials and the use of appropriate technologies
People with skills that marry business acumen, with the technical aspects of data analytics will be in high demand across industry sectors.
The programme is designed to embed various transferable skills across all modules. Skills such as teamwork, troubleshooting, communication, problem solving, reflective thinking and analytical reasoning are embedded throughout the programme.
Typically students will attend two evenings per week and some Saturday attendance is required per semester.
People in the following categories are eligible to apply for courses in the 2018/19 academic year (subject to the applicant meeting all residency and nationality/visa requirements and any academic requirements):
Returners (Formerly referred to as Homemakers)
Courses are fully funded for these applicants. They may apply to all courses if they meet the nationality/visa requirement and residency criteria. Course specific criteria may also apply.
People in employment
Please note that under the Springboard+ 2018 initiative, 90% of the fees are covered by HEA and 10% of the fees are payable to the college for this category of applicants. They may apply to all courses if they meet the nationality/visa requirement and residency criteria. These fees can be paid by either the applicant or their employer, should the employer sponsor the applicant. Should you require a company sponsorship form for invoicing please let us know.
Therefore the below fees will be applied to your application(s), should your application be successful, for the following course:
Higher Diploma in Science in Data Analytics - Course fee is €7,250, of which you pay 10% = €725
NOTE: These fees must be paid prior to enrolling on your Springboard+ programme.
The unemployed or formerly self-employed
Should the applicant receive the relevant Social welfare payments as listed by Springboard+, or fall under the Returner category above, this programme will be fully funded.
To be considered for admission to this programme, applicants must hold a Primary Honours Degree (level 8) in a cognate discipline from a recognised third level institution or equivalent qualification. Candidates will ideally be able to demonstrate technical or mathematical problem solving skills as part of previous programme learning. Typically holders of more technical, numerate degrees are likely to gain a higher ranking in any order of merit in selection for the programme.
Recognition of Prior Learning (RPL)
Learners may also access this course on the basis of recognition of prior learning or by assessment of prior experiential learning/informal learning. The process is implemented within the relevant school, by the relevant Head of School/Department or nominee and is overseen by the Registrar. For this particular programme applicants will be considered on a case by case basis based on their educational record, work experience, their ability to demonstrate technical or mathematics.