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What will I learn?

This technically-oriented course hones quantitative and computer techniques to assist students in exploring management issues and supporting decision-making within a business context

Exposure to and practice of the latest cutting-edge quantitative analysis techniques used within this specific branch of applied mathematics

Development of the necessary computer software skills and an understanding of the theory and practice of applied information systems, as required in consultancy and business

The ability to develop new software solutions and implement mathematical and quantitative techniques in order to make effective business decisions and boost performance

How will I benefit?

Students will not only be provided with vital business analysis tools but also given the chance to apply them by engaging with leading companies over the duration of the course, raising their employability in the eyes of recruiters

  1. Access to current research into all aspects of decision and management science, including Project Management, Simulation, Multi-criteria Decision Making and Spatial Decision Support Systems
  2. A thorough grounding in a science employed within a wide range of organisations and industries, including banks, management consultancies, the public sector and the engineering industry
  3. Successful completion of the course has seen many graduates go on to work for such companies as Accenture, Goldman Sachs, IBM and Intel.

Curriculum

Students complete 6 core modules, including a 15-credit Capstone project during the summer, and 5 option modules. Some options may be assigned at admission time based on students' previous studies. Options listed below are indicative and are offered subject to faculty availability.

In the summer term, the Capstone project involves full-time work on a real analytics problem, generally with a top Dublin-based analytics employer. It is generally mathematically complex with a computer-programming element and a consulting aspect. 

Semester 1Semester 2Summer Term

Module options

Module options

Module options

Note: option modules listed are indicative of what has been delivered in previous years. What is offered each academic year is subject to change.

The MSc Business Analytics programme gives students a thorough theoretical and practical business analytics education: qualitative, quantitative, computational, and data-oriented analytics techniques, and how these techniques add value and fit into business practice. It aims to give graduates the skills to work in analytics roles in business and progress quickly to leadership positions (Purpose).

A central part of the programme's vision is that analytics methods promise improved insight, decision-making, and outcomes in industry, business, and the public and non-profit sectors. The programme aims to give students both the technical and soft knowledge and skills required to deliver on this promise (education and subject/discipline/professional values). Faculty aim to provide transformational learning, to create
a growth mindset in students, and to create an environment in which students are empowered to question and discuss. UCD Smurfit provides high-quality supports and facilities. Students experience a diverse environment (age, gender, nationality, background), both within their class and between the full-time and part-time classes (the nature of the learning environment for students).

The programme is based on: (1) core taught content (foundations and applications); (2) taught specialisations; and (3) independent research work. Content is delivered through a combination of lectures, seminars, tutorials, practical sessions, online and autonomous learning, with a major independent supervised real-world business analytics project. Assessment is through a blend of continuous assessment and end-of-year exams. Continuous assessment includes both individual and group work, and both formative and summative assessment. There is also a blend of technical/quantitative deliverables and written/discursive deliverables (key approaches to teaching, learning and assessment).

On successful completion of the programme students should be able to:

Programme Goal 1: Informed Thinkers: Our graduates will be knowledgeable in the field of business analytic supported by a strong research foundation, thought leadership, and richly varied learning experiences.

Programme Goal 2: Critical and Analytical Judgement: Our graduates will have developed their analytical competence, reflective capacity and critical thinking, enabling them to apply judgement, to act with integrity and to work with others to make sound, socially responsible decisions.

Programme Goal 3: Agility and a Development Mind set: Our graduates will understand and continually work on their capacitive including communication, collaboration, creativity and critical thinking.

Programme Goal 4: Ambition for Action and Contribution: Our graduates will be able to talk about, apply and act upon what they know and have the ambition and courage to collaborate, solve problems and contribute to business and society.

Use descriptive, predictive, and prescriptive analytics methods to achieve understanding, prediction, and optimisation in the context of business based on deep knowledge of qualitative, quantitative, computational and data-oriented analytics (PG1).

Carry out business analytics projects from beginning to end, including: stakeholder consultation, business analysis and collaborative refinement from ill-defined to well-defined problems; data gathering and processing; core analytics methods; and professional-quality communication of results (PG1).

Map from any analytical business problem to an appropriate analytics approach to solving it, and be capable of explaining its advantages and limitations (PG2).

Understand the decision-making process in business its trade-offs and limitations and how analytics methods fit into it (PG2). 

Stay informed concerning cutting-edge analytical methods through reading appropriate literature and learning new tools and techniques on an ongoing basis (PG3).

Work with client management, and peers; take account of and take advantage of differing strengths and styles within analytics teams and among other stakeholders in analytics projects; translate between the technical language of analytics and language appropriate to clients and management (PG3).

Understand and explain the range of situation within business and in the wider world of public sector and non-profit organisations where analytical methods can add value (PG4).

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