Official description of the course: here
This is a laboratory and experimental course in the field of Internet traffic measurements. Most of the classes are given in laboratories, with few introductory lessons for each field.
Students will have to setup experiments to run active or passive measurement tools in real networks, and to apply methodologies learned in previous classes, or that will be explained during the course.
Both passive traffic analysers, and active traffic generators will be used to characterise the network and control the load. During the course, students will face lab sessions of increasing complexity, maturing a critical approach and scientific methodology toward the understanding of complex systems such as computer networks are.
Students will be introduced to the data analysis via Machine Learning, and will use modern tools such has Jupyter Notebook for their assignments.
Students will learn how to use Linux systems, how to configure the network, and how to properly use Data Science approaches using Python, and Scikit-learn in particular.