The course comprises of 12-14 weeks of teaching consisting of lectures and exercises.
The lectures will focus on gaining a theoretical and methodological understanding of Big Data processes by reading and discussing relevant literature. In addition, you will be introduced to demonstrations and worked examples of analytics and visualization. Moreover, we will also reflect upon the epistemological, ethical, and political premises and consequences of Big Data practices in different societal sectors.
During the exercises you will work in small groups on hands-on tasks. The problems can revolve around a specific type of analytics or visualization (e.g., exploratory data analysis, classification, clustering), a specific application domain (e.g., marketing, financials, transportation), or a particular challenge of Big Data processes (e.g., handling of personal data). Furthermore, you will practice communicating and presenting your results and reflections during the exercises in order to prepare for the oral exam.
During the course you will learn to apply a number of software tools for analytics and visualization, such as Tableau and R.
Reports are handed in by groups and students are examined as a group and evaluated on the basis of demonstration of fulfilment of the intended learning objectives for the course.
The hand in should be 15 pages + 2 pages per group member. Each group should have 3-5 members.
Duration of the exam: 30 minutes per group incl. assessment and feedback
Form of group exam: Group exam
See Study Guide -> Exams -> Course Exams -> Exam Forms for more information.