Trends in Data Science
Niveau
Master's degree program
Learning outcomes of the courses/module
The participants:
• can describe current thematic trends in the field of data science
• can describe current technological developments in the field of data science
• can discuss current practical questions in the field of data science
• can describe current thematic trends in the field of data science
• can describe current technological developments in the field of data science
• can discuss current practical questions in the field of data science
Prerequisites for the course
No prerequisites
Course content
The content of this course is not fixed but is adapted to the trends currently prevailing. Exemplary topics may include:
- New technologies in the field of big data processing
- Trends in programming languages for data analysis
- New data processing concepts (e.g., data lake)
- New research questions in the field of data science
- New questions arising in data science practice
- New technologies in the field of big data processing
- Trends in programming languages for data analysis
- New data processing concepts (e.g., data lake)
- New research questions in the field of data science
- New questions arising in data science practice
Recommended specialist literature
Aufgrund der Veränderlichkeit der Inhalte werden hier nur beispielhaft einige Web-Quellen angeführt, die derzeit im Bereich Data Science Trends stark vertreten sind:
- Medium (2020): Towards Data Science (Ed. 1), Online, https://towardsdatascience.com/.
- KDNuggets (2020): Knowledge Discovery Nuggets (Ed. 1), Online, https://www.kdnuggets.com/.
- Medium (2020): Towards Data Science (Ed. 1), Online, https://towardsdatascience.com/.
- KDNuggets (2020): Knowledge Discovery Nuggets (Ed. 1), Online, https://www.kdnuggets.com/.
Assessment methods and criteria
Seminar paper
Language
English
Number of ECTS credits awarded
3
Semester hours per week
Planned teaching and learning method
The following methods are used:
- Lecture with discussion
- Interactive workshop
- Lecture with discussion
- Interactive workshop
Semester/trimester in which the course/module is offered
4