Computer Science

This course studies networks and communications. It focuses on learning about applications of computer communications and types of data, channels, bit rate and network topologies, LANs, MANs and WANs, broadcast and point-to-point, and synchronous and asynchronous communication. Students also examine connection-oriented and connectionless communication; theoretical capacity of channels (Shannon’s law and the Nyquist relationship); multiplexing; queuing theory; computer communication system architectures; the OSI reference model; and the seven layer model.

This course provides a study on file structures and database management. It examines logical database design, from the relational model to the basic physical level in order to understand and recognize the need for secondary storage media in various use cases. The course also covers the following topics: static and dynamic properties of the relational model; base structures; auxiliary structures; database management systems; storage paradigms. *Previous course work in programming, algorithms, data structures, and computer structure is required. Texts: Cuadra D., Castro E., Iglesias A., Martínez P., Calle J., de Pablo C., Al'Jumaily H., Moreno L., García S., Martínez J.L., Rivero J., Segura I.. Desarrollo de Bases de Datos: casos prácticos desde el análisis a la implementación. 2ª ed.. Ra-Ma. 2013 Elmasri, R. y Navathe, S.. Fundamentals of Database Systems (5ª ed).. The Benjamin/Cummings Publishing Company. 2006 Folk, M. J., Zoellick, B., y Riccardi, G.. File Structures.. Addison Wesley . 1998 Oracle® . SQL*Plus. User's Guide and Reference. http://docs.oracle.com/database/121/SQPUG/E18404-12.pdf. 2013 Oracle® Database. SQL Language Reference. http://docs.oracle.com/database/121/SQLRF/E41329-17.pdf. 2015 Silverschatz, A., Korth, H. F. & Sudarshan, S.. Database System Concepts, 6th ed (also 3rd to 5th). Mc-Graw Hill. 2011 NOTE: Course is the same as CP S 138, but taught in English.

This course covers the human-centered principles of designing and building virtual reality (VR) and augmented reality (AR) applications. Topics: the fundamentals of VR and AR, human perceptions of reality, and the design patterns and guidelines for user interactions within VR/AR applications. Labs provide hands on experience building VR/AR applications applying these interaction principles.

This class covers the fundamental concepts and advanced methodologies of machine learning for imaging and relates those to real-world problems in computer vision and medical image analysis. You will experience different approaches to machine learning including supervised and unsupervised techniques with an emphasis on deep learning methods. Applications include image classification, semantic segmentation, object detection and localisation, and registration. A key objective is to equip you with the skills needed to work in, and conduct research into, image computing and applied machine learning.

Rapid advances in technology and connectivity have led to new opportunities in every aspect of life, from manufacturing, finance and retail, to education, media, and politics. Digital technologies and services profoundly influence our lives and improve our world in countless ways. But these advances also raise challenges. What do our digital footprints reveal, and who is trying to exploit them? How do new technologies offer new opportunities for cybercriminals to steal our data, our money, and our identities, lock us out of our homes, poison our water, and switch off our lights? How does the use of digital media change the nature of democracy and affect trust in democratic systems and established authorities? And what technical, behavioral and legal measures are available to prevent harm and maintain trust in digital systems? This unit explores the risks to security in our super-connected, data-driven world and what can be done to preserve trust in our digital environment.