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This semester introduces essential topics in BI, covering data warehouses, data mining, and business processes, as well as essential aspects of data management, covering traditional relational technology and new emerging paradigms. It is composed of the following courses.
This semester focuses on basic concepts of distributed systems and BD management, aiming to train students in understanding how data management can scale to large volumes while potentially also dealing with velocity and variety. In particular, NoSQL databases and semantic data management will be at the core of the semester, together with other topics needed in preparation to the specialisations. Students, divided in teams, define and implement their own project, transversal to all courses, potentially ready to be continued as a start-up. The semester consists of the following courses:
Students will attend the summer school organised annually by one partner institution. Presented by leading researchers in the field, it provides students with theoretical and practical skills in the domain. Industrial presentations will allow participants to understand the current product offer.
More information on the summer school can be found in the Summer School page.
Although not mandatory, in order to acquire a first working experience, students are encouraged to participate in summer internships, typically with industrial associated partners, between the end of the summer school and the beginning of the third semester.
This specialisation focuses on scalable data analytics for BI, particularly, on large, heterogeneous, and high-throughput data (i.e., for both data-at-rest and data-in- motion). The theoretical courses enable students to acquire a foundation on large-scale analytics addressing the Volume, Velocity, and Variety challenges. In addition, the seminar on the state-of-the-art scalable analytics and tools, and the project offer practical experience for students to gain expertise in the usage of open-source BD tools. The specialisation consists of the following courses (students must choose two among the first three).
The specialisation focuses on methods, techniques, and tools for the design and analysis of process-aware business information systems, i.e., systems that support business processes in organisations. The objective is that students are able to build complex systems involving processes, humans, and organisations, thus dealing with the Variety and the Value challenges. The specialisation consists of the following courses.
This specialisation focuses on models, algorithms, and technologies related to decision-support systems and massive data analytics. The specialisation covers theoretical foundations such as decision-making in uncertain situations, advanced machine learning, graph management and analytics as well as visualisation and innovation. The specialisation is composed of the following courses.
During the fourth semester, students will put into practice what they have learned during the previous semesters, either in an industrial or a HEI partner. Students are encouraged to devote their master’s thesis to start-up creation. The thesis is evaluated jointly. The thesis work will be considered for submission to scientific conferences.
The closing event of the programme is organised annually by one partner institution. All main partners will participate in the event, associated partners and industrial organisations will be invited to attend. In this event the students will defend their master’s thesis, which will allow all partners to evaluate their skills. The event will also be the ideal place to assess the programme, and to discuss best practices and curriculum evolution. The event will be followed by the graduation ceremony.
Please view the detailed course description.
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