Study plan for Master's degree in big data analytics with awarded qualification Master of Engineering (60 ECTS).

Overall competences

The overall achieved competence after graduating with this Master’s degree is to be able to lead the development of big data analytics services. Big Data Analytics studies gives an in-depth understanding of how to make use of data in order to create insights. The student will acquire state-of-the-art analytics knowledge and advanced practical big data skills from solving real world data problems. Apart from this, an important general competence is to increase the student’s technology leadership ability, as well as, communicative and social competences in English.

Profile

Big Data Analytics studies give an in-depth understanding of how to make use of data in order to create insights. The intended student for these studies is someone with a programming background who wants to understand how to employ machine learning methods reliably in a business or scientific environment. The program is arranged so that a student rapidly gains a broad understanding of the essential concepts of big data analytics, descriptive and predictive modelling, as well as visualisation. The program emphasises the importance of understanding how to build analytical solutions with production level code.

Structure of studies

Please note that Arcada UAS has the right to change names of courses listed in each module below or replace courses within modules. 

Professional Studies (30 ECTS)

The profesional studies gives the student a core knowledge module (30 ects), focusing on the different areas in the big data analytics workflow.

All courses are taught entirely in English.

BIG DATA ANALYTICS (30 ECTS) - Specialised Professional Studies

Core competences

Upon completion of this module, you have specialised problemsolving skills required for developing software for big data analytics problems. You have a broad understanding of how to set up a scientifically valid analytics process. You know how to handle data, employ machine learning methods on the data, visualise data insights, and communicate a solution's value proposition. You can articulate personal and authentic expertise that enhances collaboration and communication in complex settings, preparing you to lead and develop novel approaches. You master the following key competences; big data, analytics process, high-performance computing, machine learning methods, visualisation, and communication data insights.

Introduction to Analytics 5
Machine Learning for Predictive Problems 5
Visual Analytics 5
Machine Learning for Descriptive Problems 5
Big Data Analytics 5
Analytical Service Development 5

RESEARCH SEMINAR AND THESIS (30ECTS) - Specialised Research Studies

Core competences

Upon completion of this module you can define, choose, argue for and adapt specialised concepts, methods and data related to your specialised knowledge about your own area. You can adapt and use them as the basis for your own individual thinking and/or research. You can independently solve demanding problems in a creative way within research and/or innovative operations and thereby develop new knowledge and ways of working. 30 You can apply and integrate knowledge from different areas. You can argue for and follow ethical principles in research.

The study module consists of the following studies

Research Seminar and Thesis 30