Introduction to Data
Faculteit | Gedrags- en MaatschappijWetenschappen |
Jaar | 2021/22 |
Vakcode | SOMINDW01 |
Vaknaam | Introduction to Data |
Niveau(s) | universitaire minor |
Voertaal | Engels |
Periode | semester I a |
ECTS | 7.5 |
Rooster | rooster.rug.nl |
Uitgebreide vaknaam | Introduction to Data | ||||||||
Leerdoelen | The first course of the minor Data Wise is focused on understanding and on the knowledge required to be able to do the projects, work in interdisciplinary teams, and participate in electives that follow later in the minor. More specifically, the learning outcomes are: 1) Understanding data cycles 2) Understanding dimensions of data 3) Evaluate data 4) Understanding scope and nature of skills for data projects 5) Understanding the value and importance of programming and what it entails 6) Applying knowledge by interacting with data-specialists 7) Understand the work needed for sharing, using and transforming data 8) Identify innovative potential of data 9) Being aware of the value of data and of potential opportunities 10) Recognize how frameworks (guidelines, codes, regulations) apply to different data processes 11) Understand and identify ethical issues |
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Omschrijving | The main aim of this course is to get students from diverse backgrounds “on the same page” and to have similar levels of knowledge by introducing them to fundamental concepts surrounding data. At the end of the course, the students will be ready to start their projects and to interact with students from different disciplines in terms of data. In the first four weeks, students will have daily meetings on diverse topics covered in different blocks (several days dedicated to one topic). Block 1: panel-discussion on diverse research into data, data science, and big data that is done at this university and beyond. Block 2: Dynamics of data in a digital society, in which students learn about the prominent role data plays in society, datafication, and data cycles. It also addresses the sociology of technology use. Block 3: Data management, in which students learn how to store data in such a way that in confirms to legal requirements, prevents person identification, but is also findable and usable for others. Block 4: Legal & ethics, in which students get acquainted with rules and regulations surrounding data use and the ethical questions that surround it. Block 5: Data science techniques, in which students get acquainted with the different forms of data that exist and standard tools of data science (programming, visualization, machine learning). Block 6: Business challenges and opportunities, in which students learn about the ways that big data are used in business and innovation. Block 7: Infrastructure, in which students learn what resources (e.g., people, software, hardware) are required to safely and efficiently store and use data. |
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Uren per week | 7 | ||||||||
Onderwijsvorm |
hoorcollege
(Presentations, excursions, discussion) |
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Toetsvorm |
opdrachten
(For all blocks, students write an assignment (pass / fail)) |
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Vaksoort | bachelor | ||||||||
Coördinator | Dr. G. Stulp | ||||||||
Docent(en) | Prof. Dr. J.A. Beaulieu ,prof. dr. M.J. Gijsenberg ,Dr. O.J. Gstrein ,Dr. G. Stulp | ||||||||
Verplichte literatuur |
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Entreevoorwaarden | |||||||||
Opmerkingen | |||||||||
Opgenomen in |
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