CS7NS4 – Urban Computing
(Semester 1, 5 ECTS) This module aims to provide both a theoretical and practical understanding of urban
computing and associated cyber-physical concepts, principles, challenges and
solutions.
School of Computer Science and Statistics
(Semester 1, 5 ECTS) This module aims to provide both a theoretical and practical understanding of urban
computing and associated cyber-physical concepts, principles, challenges and
solutions.
(Semester 1, 5 ECTS) The first aim of the first part of this module is to give students a grounding in
electronics.
(Semester 1, 5 ECTS) This is a rigorous development of probability theory from an axiomatic foundation, along with some more advanced topics.
(Semester 1, 5 ECTS) Sample Space and Probability: Sets; Probabilistic Models; Conditional Probability; Total Probability.
Theorem and Bayes’ Rule; Independence; Counting.
(Semester 1, 5 ECTS) Wave equation and its solution; Maxwell´s equations; Fourier transform and analysis; vibration; mass-spring-damper systems; numerical methods; simulation software.
(Semester 1, 5 ECTS) The module introduces the basic concepts underlying the communication between nodes connected to the Internet.
(Semester 1, 5 ECTS) Classical multivariate techniques of principal component analysis, clustering, discriminant analysis, k-nearest neighbours, and logistic regression are investigated.
(Semester 1, 5 ECTS) Introduction to Forecasting; ARIMA models, data transformations, seasonality, exponential smoothing and Holt Winters algorithms, performance measures. Use of transformations and differences.
(Semester 1, 5 ECTS) This module aims to provide an opportunity for students to develop their hands on
skills in data analysis.
(Semester 1, 5 ECTS) This module covers a range of topics in probability theory at an introductory level, with a view towards applications. Overall the goal of the module is to let the students gain familiarity with both analytical and simulation-based methods to deal with applied problems in probability.