Post Graduate Diploma in Science in Business Data Analytics (Autumn 2022)

About this Course

The Postgraduate Diploma in Science in Business Data Analytics is designed to meet a skills shortage of data analysts and related occupations, both here in Ireland and internationally. This programme will be offered as a 60 credit, NFQ Level 9 blended learning programme where students will engage in a variety of face-to-face and online environments. This is a flexible, blended learning programme for those with busy lives. Average weekly class times are 10 hours. Live webinars, face-to-face tutorials and laboratory tasks are scheduled in the evenings and on Saturdays.

Business analytics, technology and data science are the three pillars of knowledge underpinning the programme. The field of data analytics intersects these knowledge domains and the programme design reflects this.

The programme also includes a work placement or work-based project elective that allows students to synthesise the knowledge, skills and know-how developed in the earlier modules. The aim is to prepare a talented, highly-qualified cohort of work-ready graduates through the deployment of a carefully crafted range of targeted academic and industry-focused activities.

We have partnered with the Analytics Institute, Ireland's professional membership organisation for the data science and analytics industry. The Analytics Institute will coordinate work placements and work-based projects for students with its 120+ member organisations.

Objectives

On completion of the programme, students will be able to:

1. Demonstrate a critical understanding of the increasingly impactful role played by analytics across a wide range of sectors within a modern economy
2. Display mastery of essential analytics, technical and investigative skills, and demonstrate a capacity for self-improvement through learning new and more advanced skills of this nature
3. Identify and deploy a range of instruments to present and explain complex ideas and influence different audiences while being cognisant of their specific needs and requirements
4. Demonstrate a creative and imaginative skill set by analysing problems within a real-world or simulated setting and designing, testing, reflecting, reviewing and producing optimal solutions
5. Collaborate professionally within cross-functional, multi-discipline teams and provide advice and leadership where necessary and as appropriate to deliver impactful analytics output
6. Assimilate knowledge, ideas and concepts from related, complex analytics domains, thereby developing a wider and deeper understanding of the domain
7. Reflect on technologies, select optimal tools and apply analytics and related knowledge disciplines in the formulation and construction of solutions to complex problems
8. Improve personal performance through a combination of considered self-reflection and self-analysis, respond professionally to feedback and have the capacity to deliver open and constructive feedback to others
9. Make and justify informed scientific-based decisions, paying particular regard to balancing creativity, logic and evidence while recognising and addressing other constraints
10. Demonstrate knowledge of relevant research methodologies and apply this knowledge ethically when tackling complex challenges relevant to the analytics domain

Entry Requirements

Students on this programme will originate from directly cognate disciplines including computer science, mathematics, statistics, engineering and technology. Applicants from partially cognate disciplines such as finance, accounting, business etc. may be accepted as determined by the Programme Director following evaluation against established criteria.

A minimum grade of Lower Second-Class Honours 2.2, or equivalent, in an honours bachelor's degree at NFQ Level 8.

English Language Proficiency
An applicant whose first language/primary mode of expression is not English will be required to produce evidence of English competence. The required proficiency level is B2+ or higher in the Common European Framework of Reference for Languages (CEFR).

Mathematical Proficiency
The programme requires students to have good numerical and statistical skills. As candidates can come from a diverse range of disciplines, essential foundational mathematics and statistics concepts will be introduced in the two-week orientation programme. Online learning resources will also be provided to learners in mathematics or programming should they require after they complete the orientation programme.

Application Deadline

• 5th July 2022

Start Date

• 19th September 2022

End Date

• 31st July 2023