A hacking day of Mathematics for Data Science at the Department of Mathematics
BioAfter her Bachelor in Mathematics and MSc in Mathematics for Life Sciences at University of Trento, she is currently a PhD in Mathematics as part of FBK research group of Complex Multilayer Networks, where she also developed her research activity for the MSc. She is studying Network Geometry induced by complex dynamics and new statistical approaches to identify influential nodes in networked systems
- Probability and linear algebra
- Basic knowledge of R Programming language
- A laptop (lecture will be interactive)
During the course we will use Jupyter Notebooks, available on github. For those of you not having Jupyter installed on the laptop, there is Binder unabling you to interact with the notebooks in a live environment!
Intended Learning Outcomes
After successful completion of the module students are familiar with the terminology and basic concepts, definitions and methods of Graph Theory and Network Analysis.
Further, students are able to create, manipulate and plot networks in
- Why do we study Networks?
- Complex Systems
- Network Modeling
- Fundamentals of Graph Theory
- The Laplacian of a Graph
- Random Walks and Graphs
- Network Centrality
- Centrality Measures
- Network Models and Centralities
- Community Detection
- Defining Groups
- Stochastic Block Model
- Current Research at CoMuNe Lab - FBK
Other references are provided in the course material.
- 5 February 2019, 09:30-12:30 @ A210, Povo 1
- 6 February 2019, 09:30-12:30 @ A210, Povo 1
- The participation is free. Please send an email to Prof. Claudio Agostinelli.
- For further information, please contact Prof. Claudio Agostinelli
- Venue: Polo Scientifico e Tecnologico F. Ferrari – Room A210
- Language: English
Course material is publicly available on my-github.