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Business Analytics

Overview
The increase in the volume, variety, and velocity of data creates opportunities for businesses to improve decision making and develop new data driven products and services. MSc Business Analytics has been developed to meet the demand for qualified professionals, who possess the necessary expertise to realise end-to-end business analytics solutions and are equipped to utilise data for business decision-making purposes.

The programme is built around the three core areas needed to succeed in analytics: business knowledge, statistics, and computing. This includes modules focusing on the application of analytics in core business functions such as marketing and human resources, as well as modules focusing on developing and applying technical skills such as advanced analytics and machine learning, data management, and data driven decision making. In total, students will study eight modules in addition to pre-course training and a final dissertation project. The dissertation project will involve the application of the business, technical, and statistical skills learnt during the taught modules.

The programme will include an induction course, where pre-course training in key statistics and computer skills will ensure students from a range of backgrounds have the necessary skills to undertake the course.

Business Analytics highlights
Industry Links
•Developed by staff with industry and academic backgrounds, the course is tailored towards the key skills required to succeed in a business analytics role.

Career Development
•Industry reports show a global shortage for data scientists. Students will learn to use cutting edge and industry standard tools and techniques to enable career development.

World Class Facilities
•The MSc Business Analytics is taught in the landscaped setting of Riddell Hall which features excellent facilities, including a dedicated computer lab with the latest analytics software.

Student Experience
•Students will learn how to use state-of the-art, industry standard software over the duration of the programme. This includes software such as R, SAS, KNIME, and Tableau.

Learning and Teaching
Teaching Methods
Tools and techniques learned in the classroom context will be used to address business problems. This will involve a mix of teaching methods to enable students to build the technical and business expertise required for a successful career in analytics. This includes methods such as computer/software practical demonstrations and training, lectures, tutorials, seminars, problem-centred techniques such as national and international case studies, non-book media (videos and podcasts), individual research, oral presentations, group projects, online discussion forums, industry visits and practitioner workshops. Specific details are provided in the programme specification, including details on assessments.

Entry requirements

Entrance requirements
Graduate
Normally a 2.1 Honours degree or equivalent qualification acceptable to the University in any discipline to include one module in a quantitative area. Relevant employment experience in a quantitative area may be considered in lieu of a module in a quantitative area and will be considered on a case-by-case basis.

International Students
For information on international qualification equivalents, please check the specific information for your country.

English Language Requirements
Evidence of an IELTS* score of 6.5, with not less than 5.5 in any component, or an equivalent qualification acceptable to the University is required. *Taken within the last 2 years.

International students wishing to apply to Queen's University Belfast (and for whom English is not their first language), must be able to demonstrate their proficiency in English in order to benefit fully from their course of study or research. Non-EEA nationals must also satisfy UK Visas and Immigration (UKVI) immigration requirements for English language for visa purposes.

For more information on English Language requirements for EEA and non-EEA nationals see: www.qub.ac.uk/EnglishLanguageReqs.

If you need to improve your English language skills before you enter this degree programme, INTO Queen's University Belfast offers a range of English language courses. These intensive and flexible courses are designed to improve your English ability for admission to this degree.
•Academic English: an intensive English language and study skills course for successful university study at degree level
•Pre-sessional English: a short intensive academic English course for students starting a degree programme at Queen's University Belfast and who need to improve their English.

Duration

1 year full-time.

Careers or further progression

Career Prospects
Introduction
The MSc Business Analytics will appeal to students who intend to pursue a career in a business analytics related field, such as data science, business intelligence, consultancy, informatics, or decision intelligence

Further enquiries

Dr. Byron Graham 
Programme Director
Queen's Management School
With a background in industry and academia, Dr Graham specialises in helping businesses to gain benefits from the effective use of data for decision making and new products and processes. Dr Graham has industry experience in a major healthcare trust, where he specialised in healthcare informatics. He has also worked in data science consultancy for a big 4 firm. Dr Graham has industry expertise in data science across multiple sectors including healthcare, the legal industry, financial services, and retail. His current research focuses on the application of machine learning and other data science approaches to solve business problems.

Subjects taught

Semester 1
Statistics for Business
Data Management
Advanced Analytics and Machine Learning
Data Driven Decision Making

Semester 2
Artificial Intelligence in Business and Society
Human Resources Analytics
Marketing Analytics
Operations Management

Semester 3
Dissertation

Assessment method

Assessments will focus on both theory and practical application of business analytics, including the use of data to gain business insights, the development of analytics solutions, essays and group work. It is anticipated that students will have approximately 30 hours direct academic contact time (drawing on methods outlined above) per module. In addition to the direct teaching hours per module, each student will normally be expected to spend approximately 120 hours on individual study time plus time for assessment completion, per module.

Application date

How to Apply
Apply using our online Postgraduate Applications Portal go.qub.ac.uk/pgapply and follow the step-by-step instructions on how to apply.

Please note: Applications for this course, received after 30th June may not be accepted. A deposit will be required to secure a place.

Enrolment and start dates

Entry year: 2019

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