This course is designed for computer science, computer engineering, electrical engineering, and mathematics students interested in understanding, designing, developing, analyzing, and validating elliptic cryptographic algorithms and protocols. The course is targeted to a diverse audience, and generally assumes no more than an undergraduate degree in computer science, electrical or computer engineering, or mathematics.
This is a graduate-level course on data mining. This time, we will specifically focus on neural network, deep learning, NLP, knowledge base, question answering, and text mining.
The purpose of the class is to explore current research topics and technological developments pertaining to the subject of "Cloud Computing."
Java-centric cluster computing: Java Remote Method Invocation; work-stealing; eager scheduling;
system & computational complexity issues; some cluster applications.
Java-centric concurrent programming: Design principles & patterns of concurrent Java programs.
Java's functional programming features
Topics that will be covered: elementary quantum mechanics, quantum information, quantum gates and circuits, quantum circuit complexity, teleportation, quantum cryptography, Shor's quantum algorithm for factoring integers and discrete logarithms, Grover's quantum searching algorithm, lower bounds in quantum computation, quantum error correction, and fault tolerant quantum computation.
Cryptography provides techniques, mechanisms, and tools for private and authenticated communication, and for performing secure and authenticated transactions over the Internet as well as other open networks. It is highly probable that every single bit of information flowing through our networks will have to be either encrypted and decrypted or signed and authenticated in a few years from now.
This course will explore Network Science concepts in the context of social and biological networks. Topics covered include social structure theory, evolution of biological networks, management of Big Data, and visualization of networks.
This course covers advanced topics on information retrieval, web search and mining, and related Internet services. The topics include search engines and advertisements, web crawling, classification, indexing and data serving, ranking and recommendation, user behavior analysis, and online services. This course will also cover system and middleware support for building related large-scale Internet services.