Cyber Effects

This course covers a broad range of topics related to cyber security and operations. Our 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 an emphasis on hands-on exercises and projects.

Cyber Effects

This course covers a broad range of topics related to cyber security and operations. Our 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 an emphasis on hands-on exercises and projects.

System Defense and Test

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

System Defense and Test

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

S-NeuralNetwrks:Neurosci to AI

This is a project based course, focusing on the science connecting the field of neural network with human brain mechanism, as well as advancements which are at the front of the field. We start by introducing a few neural network architectures with their learning paradigms, including deep feed-forward and recurrent networks, Hopfield's memory, and Kohonen's self organizing maps.

S-NeuralNetworks:Neurosc to AI

This is a project based course, focusing on the science connecting the field of neural network with human brain mechanism, as well as advancements which are at the front of the field. We start by introducing a few neural network architectures with their learning paradigms, including deep feed-forward and recurrent networks, Hopfield's memory, and Kohonen's self organizing maps.

S-NeuralNetworks:Neurosc to AI

This is a project based course, focusing on the science connecting the field of neural network with human brain mechanism, as well as advancements which are at the front of the field. We start by introducing a few neural network architectures with their learning paradigms, including deep feed-forward and recurrent networks, Hopfield's memory, and Kohonen's self organizing maps.
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