The studies in Big Data Analytics give you an in-depth understanding of how to make use of data in order to create insights. This master's degree programme is arranged so that you rapidly gain a broad understanding of the essential concepts of big data analytics; descriptive and predictive modelling, as well as optimization. The programme emphasizes the importance of understanding how to build analytical solutions with production level code.
This programme is intended for people with experience in programming and software development, and a few years of working experience. If you are curious about and comfortable with solving data-related problems by applying logical and mathematically inspired methods, this programme is for you. Big data involves a new type of technology, whereas analytics involves a complete method renewal. As a student you will gain new insights, even after years of working experience. Big Data Analytics is the ultimate refresher course.
What you will learn
- Programming for analytical services
- Data analytics
- Machine learning
- Data engineering
- Data visualization
- Descriptive data mining
- Predictive forecasting
- Automation of prescriptive decisions
- Data science and verification of model results
- Planning and development of analytical solutions
Examples of future positions
Graduates will be able to work with a wide range of tasks in various industries. Positions include development and conventional managerial positions, e.g.:
- Big data analytics developer
- Big data analytics manager
- Data engineer
- Data scientist
- The principal or senior software developer
- Head of analytics
- Head of development
- Senior analyst
Take on real-world challenges
As a student, you will be involved in projects connected to real-world problems that include elements of both group work and individual achievements. The focus on real-world challenges emphasizes disruptive problem solving through analytics service development. Communication and business know-how are emphasized both through data visualization and traditional pitching.
A research-oriented environment
Our research covers a wide range of interests in analytics and machine learning that you as a student can benefit from when pursuing your own domain applications. These include malware detection, text analytics (e.g. content classification), network intrusions detection, Internet of things, object recognition in images and video, and financial analytics.
Specialize according to your own interests
The Master’s thesis project (30 ECTS) consists of a development or research project for a client (e.g. your employer) or a collaboration with Arcada’s researchers, followed by a thesis report. In some cases, this can be part of the student's entrepreneurial activities. You start working towards your thesis project immediately and get to show your capability of systematically performing a project with a practically applied problem as a starting point. Based on the development needs of the client/researcher you then develop the thesis project in close co-operation with your supervisor and contact person at the commissioning company.
A solid foundation for your future career
By participating in this master's degree programme you will significantly broaden your opportunities for career advancement. Big data analytics is a horizontal skill that can be applied in most fields as they increasingly become data-driven.
How to apply
- Please visit the Application pages for all the information on how to apply.
Tuition fees and scholarships
Please note that applicants from countries outside the European Union/EEA are required to pay tuition fees. This master’s degree programme, consisting of 60 ECTS, costs 10 000 euros. In case a student is unable to complete the degree within the given study time, the student needs to pay 4 000 euros per each extra semester until the degree is completed.
No scholarships are offered for master level studies.
You can familiarize yourself with the current curriculum and course offerings below, but be aware that changes to the content may occur for the next academic year.
More education-specific information can also be found at Arcada's digital study guide (External link)