| Entry Requirements |
Expand+The minimum entry requirements for the MSc in Data Analytics are:
A minimum Second Class Level 8 Honours Degree (2.2) in a cognate discipline from a recognised third level institution or equivalent.
In addition, for applicants whose first lang...
Hide-The minimum entry requirements for the MSc in Data Analytics are:
A minimum Second Class Level 8 Honours Degree (2.2) in a cognate discipline from a recognised third level institution or equivalent.
In addition, for applicants whose first language is not English and who have not undertaken their undergraduate degree through English the following is required:
The minimum requirement for a non-native English speaker is greater or equal to B2+ in the Common European Framework of Reference for Languages for admission. Non?EU applicants, residents outside Ireland/EU, must apply directly to the International Admissions Office at DBS.
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| Course Content |
Expand+Given the rapid growth in internet data usage, the shift to cloud computing, and the rate at which Irish businesses integrate data and analytics into their daily operations, Data Analytics is an identifiable discipline with a breadth and depth of con...
Hide-Given the rapid growth in internet data usage, the shift to cloud computing, and the rate at which Irish businesses integrate data and analytics into their daily operations, Data Analytics is an identifiable discipline with a breadth and depth of content that encompasses many of the subfields (e.g. software development, machine learning, data visualisation that form the modern AI ecosystem).
The programme aims to respond to the ever-growing demand across industries for data analytics specialists involving skills in technology, programming for data analytics, data analysis with related context, graph technology considered to be effective means to empower the development of sophisticated AI applications. Additionally, the programme learning outcomes focus on the learner’s ability to meet requirements and deliver against business intelligence goals of organisations they will work in and allow for all of these outcomes to be demonstrated from an academic perspective but also to have a portfolio piece of work that can be shared with current or prospective employers.
Either full time or part time, the programme is designed to facilitate learners with computer science/data science/ technology/general science/ mathematics/statistics or related background who wish to upskill in this new and emerging area of Data Analytics. It will also be of interest to learners who have completed their undergraduate degree and wish to specialise in this area.
The specific programme aims are as follows:
• Enable learners to develop expert knowledge of current and developing analytics skills related to the development and use of analysis and statistics.
• Provide learners with a deep and systematic knowledge of business and technical strategies for data analytics and the subsequent skills to implement solutions in these areas.
• Facilitate the learner’s ability to develop applied data analytics skills relevant to the workplace.
• Identify and develop autonomous learning skills appropriate to develop specialisms in the field of analytics.
• Develop in learners a deep and systematic understanding of current issues of research and analysis relating to the field of data analytics.
• Empower learners as they identify, develop and apply detailed analytical, creative, problem solving in research scenarios relating to data analytics.
• Provide the learner with a comprehensive platform for career development, innovation and further study related to the field of data analytics.
• Respond ethically and informatively to address any emerging trends and wicked problems that may arise due to the growing needs of industry.
• Apply advanced theoretical and methodological knowledge to address a problem domain related to the field of data analytics creating an applied solution.
Structure
The full-time programme will be delivered across three semesters comprised of twelve weeks each across nine months. In the part-time mode, the schedule consists of four semesters of twelve weeks across eighteen months.
Semester one lays the groundwork for the programme and encompasses modules that focus on providing a solid and comprehensive understanding of the relevant concepts, a proficiency in the use of programming skills to gather, analyse, process and visualise data, statistics for data analytics and the application of pattern recognition in machine learning.
Semester two builds on this by covering advanced modules in which the knowledge, understanding and skills acquired in the first semester can be employed. Semester two modules offer advanced and applied skills in topics such as data and network mining, databases and data storage, graph, data visualisation including foundations in linguistics, statistical analysis and applications.
Semester three includes an Applied Research Project.
In addition, the programme aims to incorporate advanced transversal skills in each module for the professional development of learners to enhance their employability options. This will enable the learner to integrate seamlessly into an organisation by addressing skills such as leadership, problem solving, teamwork, time management and academic writing that are essential for a Level 9 graduate.
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| Careers or Further Progression |
Expand+Career Opportunities
The rise in employment opportunities in the area of data science is a global trend. Data Science is set up as a priority area of focus in the discipline of ICT for 2018-2023 in particular in automation and digitalisation includi...
Hide-Career Opportunities
The rise in employment opportunities in the area of data science is a global trend. Data Science is set up as a priority area of focus in the discipline of ICT for 2018-2023 in particular in automation and digitalisation including Data Analytics, Management, Robotics and Artificial Intelligence (including Machine Learning), Digital Platforms, Content and Applications etc.
Graduates from Master of Science in Data Analytics programme have the potential to excel in roles such as Data Analyst, Data Scientist, AI Manager, IT Manager, Data Analytics Managers in a wide variety of industries.
Within the Data Analytics space, there is a diversity of jobs requiring various levels of expertise:
Core industry roles include:
Data Analyst
Business Analyst
Data Engineer
BI Analyst
Advanced roles include specialists in:
Data Science
Software / Python Developer
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