The ability to transmit quantum information over long distances will enable implementation of many fascinating quantum communication tasks and provide us with novel capabilities that reach beyond what we can do over classical Internet alone. Examples of such tasks include blind quantum computing, clock synchronization or distributed quantum computing. Quantum cryptography is one family of such tasks with the most famous one being quantum key distribution.

The ability to transmit quantum information over long distances will enable implementation of many fascinating quantum communication tasks and provide us with novel capabilities that reach beyond what we can do over classical Internet alone. Examples of such tasks include blind quantum computing, clock synchronization or distributed quantum computing. Quantum cryptography is one family of such tasks with the most famous one being quantum key distribution.

Introduction to core machine learning models and algorithms for classification, regression, dimensionality reduction and clustering. The course will cover the mathematical foundations behind the most common machine learning algorithms, and their effective use in solving real-world applications. Requires a strong background in mathematics and programming.

Introduction to core machine learning models and algorithms for classification, regression, dimensionality reduction and clustering. The course will cover the mathematical foundations behind the most common machine learning algorithms, and their effective use in solving real-world applications. Requires a strong background in mathematics and programming.

This course covers a range of topics related to cyber security and operations. As each topic could be its own course, they will be presented broadly. The focus is on real-world studies of reverse engineering, exploit analysis, and capability development within the context of computer network operations and attack. The course has a strong emphasis on hands-on exercises and projects. Industry-standard tools such as Ghidra and CVE will be leveraged.

This course covers a range of topics related to cyber security and operations. As each topic could be its own course, they will be presented broadly. The focus is on real-world studies of reverse engineering, exploit analysis, and capability development within the context of computer network operations and attack. The course has a strong emphasis on hands-on exercises and projects. Industry-standard tools such as Ghidra and CVE will be leveraged.

This class trains students to detect and analyze weaknesses and vulnerabilities in target systems as a method of assessing the security of a system. Such techniques have various names, including penetration testing and ethical hacking. We focus on tools and techniques that an attacker would employ but from the perspective of an ethical system administrator. Broad topics include: tools and techniques for penetration testing and attacks, information gathering, social engineering, and defenses.

This class trains students to detect and analyze weaknesses and vulnerabilities in target systems as a method of assessing the security of a system. Such techniques have various names, including penetration testing and ethical hacking. We focus on tools and techniques that an attacker would employ but from the perspective of an ethical system administrator. Broad topics include: tools and techniques for penetration testing and attacks, information gathering, social engineering, and defenses.

This course is intended to cover information retrieval and other information processing activities, from an applied perspective. There will be numerous programming projects and quizzes. Topics will include: search engine construction (document acquisition, processing, indexing, and querying); learning to rank; information retrieval system performance evaluation; classification and clustering; other machine learning information processing tasks; and many more.

This course is intended to cover information retrieval and other information processing activities, from an applied perspective. There will be numerous programming projects and quizzes. Topics will include: search engine construction (document acquisition, processing, indexing, and querying); learning to rank; information retrieval system performance evaluation; classification and clustering; other machine learning information processing tasks; and many more.