Introduction to Data Science

Faculteit Campus Fryslân
Jaar 2019/20
Vakcode CFB007A05
Vaknaam Introduction to Data Science
Niveau(s) bachelor
Voertaal Engels
Periode semester II b
ECTS 5

Uitgebreide vaknaam Introduction to Data Science
Leerdoelen Upon the successful completion of this course, students will be able to:
- Summarise the theory behind data science
- Understand the context of datasets
- Inspect, filter, analyse and visualise datasets
- Integrate and reorganise different datasets
- Hypothesise and forecast observations about datasets
- Apply basic machine learning algorithms to datasets
- Take responsibility on the usage of data (e.g. privacy and security concerns)
- Reason to support decision making
- Judge and criticise their own work
Omschrijving Data Science is a fast-growing field that combines statistics and several fields of IT to provide theoretical and practical tools for exploring and solving data-related problems. Among its possible applications, data science is a powerful tool to support addressing global challenges, as they often involve reasoning based upon diverse and sizeable data. This course aims at developing a minimal set of skills necessary to start applying data science to real-world problems. For that, students are introduced to several topics related to three main components: data retrieval, visualisation and analysis. Also, students learn and apply basic techniques of each component. The basic techniques are practised throughout the course with weekly computer exercises, and the students demonstrate their acquired skills in a non-trivial project for analysing a real-world dataset. Finally, the course also briefly tackles societal and ethical implications related to the studied topics.

Topics on data retrieval include traditional file-based datasets, database technologies, and streaming. Topics on data visualisation include reporting and plotting, qualities of visualisations, translation of statistical measures into visualisation, and visualisation best practices. Topics on data analysis include basic statistical tests, data clustering and machine learning. All data used and analysed are related to the global goals and as encountered / used by corporations, organisations and governments.
Uren per week
Onderwijsvorm nog niet bekend
Toetsvorm nog niet bekend
Vaksoort bachelor
Coördinator D. Feitosa, PhD.
Docent(en) D. Feitosa, PhD.
Entreevoorwaarden Foundation: Introduction to Programming
Skills Lab: Statistics I
Opmerkingen
Opgenomen in
Opleiding Jaar Periode Type
BSc Global Responsibility & Leadership  (Groep B) 1 semester II b verplicht
BSc Global Responsibility & Leadership  (Groep A) 1 semester II b verplicht