Computer Science

This course will introduce fundamental concepts and techniques in the content of remote sensing and image processing for Earth observation from space. The course starts by introducing core concepts in remote sensing (describing the processes by which images are captured by sensors mounted on satellite and airborne platforms and key characteristics of the acquired images). Then, fundamental methodologies for processing, analyzing, and visualizing remotely sensed imagery are introduced. Topics include representation of high-dimensional remote sensing images, time domain representations, filtering and enhancement. Practical applications will be provided throughout the course. Participants of this course will gain theoretical and practical knowledge on fundamental concepts and techniques for processing and analysis of remote sensing images acquired by Earth observation satellite and airborne systems.

This is a project-based course where students work in a team to carry out the development and management of a relatively large scale software project, building a piece of software to fulfil the needs of a particular customer. Students put into practice state-of-the-art techniques used in industrial software development to ensure that their team produces software cooperatively, reliably, and on schedule. Each team works on a different project, and receives individual coaching to provide support and advice relevant to their particular project.

In this course, students study the principles of computer networking, analyze and discuss the OSI & TCP/IP models, demonstrate how a network is designed based on specific requirements, and learn basic principles of computer security.

This course focuses on the fundamentals of artificial intelligence and understanding the implications of these techniques in creative processes and in society as a whole. It discusses the intersection of technology, creativity, and culture, and how AI can contribute to these areas. This course examines the potential of AI as a tool for artistic expression and creativity but also the ethical implications of AI, particularly in the context of art, culture and society.

This course introduces the fundamental concepts of problem solving by computing and programming using an imperative programming language. It is and introductory course to computing. Topics include computational thinking and computational problem solving, designing and specifying an algorithm, basic problem formulation and problem solving approaches, program development, coding, testing and debugging, fundamental programming constructs (variables, types, expressions, assignments, functions, control structures, etc.), fundamental data structures (arrays, strings, composite data types), basic sorting, and recursion.

In this course, students complete a long-term individual project in order to demonstrate independence and originality, to plan and organize a large project over a long period, and to put into practice knowledge, skills, and research methods. Students are able to submit an original proposal, or browse from projects proposed by prospective supervisors.

This course introduces students to the core ideas and fundamental concepts behind machine learning. Students learn different machine learning problems and the algorithms that exist to address them. They formulate machine learning problems and machine learning pipelines, apply suitable algorithms to tackle different machine learning tasks, implement machine learning algorithms to solve supervised learning problems, and assess appropriate methodologies to evaluate machine learning algorithms.

This course examines various concepts related to software, system and network security. It covers a range of topics including attacks on privacy and attack surface, static and dynamic analysis of malware, hardware security (trusted computing base, secure boot, and attestation), network security and some hot topics in cryptography including elliptic curve, blockchain and bitcoin.

This course explores industrial practices for working on large, existing, software systems. Students discuss how to successfully design, modify, maintain, and operate the large software systems that form so much of the infrastructure of trade, commerce, communication, and entertainment in the modern world. Students also consider current issues faced by the practicing software engineer, and particularly look at engineering trade-offs in different situations and understand that software engineering problems do not always have right and wrong answers.