Please note that at the beginning, this course will be online only, then it will switch to offline with the option of online for those who are not able to be present offline. The precise details of this will be discussed with the instructor during the first class.
The increasing volume and nature of big network data sets in the social and natural sciences call for more complex and sophisticated mathematical and statistical tools. In this course we will present the fundamentals of probability theory and statistics, and apply such mathematical and statistical tools to networks. The assessment of the statistical validity of the observed results will be analyzed and, when possible, quantitatively evaluated. Besides the mathematical theory, the course will have a practical approach with home assignments and hands-on classes. During the class all examples and sample codes will be provided in Python and Jupyter notebooks.
Learning activities and teaching methods
Lectures: 12 classes of 100 min. Around 80% of the classes will be theory only. The other 20% will include programming exercises or evaluation of data sets. Therefore, use of a computer will be required during some lectures. Students can form groups and use their own laptops. Instructions on the required software will be provided during the first class.