The biomedical signal processing course provides an application-intensive approach to biomedical signal processing and application of mathematical tools.

The computer vision course involves the development of algorithms and software that have the potential to mimic a biological organism's ability to see.

The data mining course provides background information on the design and use of data mining algorithms and applications in data mining on the web, computational biology and various medical applications.

The speech processing and recognition course covers the fundamentals of speech recognition and voice interfacing with machines.

The data compression course examines the theoretical foundation of compression techniques and algorithms for lossy and lossless data compression as well as signal modeling and its extensions to data compression and applications to multimedia data compression.

The database system course examines the principles of the design of systems that can manipulate and retrieve data from large databases using high level formal languages.

The neural networks course examines models of computation that learn tasks from examples of desired input and output behavior for various applications.

The artificial intelligence course focuses on the issues and principles and techniques of artificial intelligence.

The cryptography course focuses on the mathematical concepts and techniques behind modern information encryption and network technologies. Topics include survey of classical and modern encryption techniques and algorithms, encryption theory and foundations, cryptographic and crypto-analysis techniques, one-way functions, pseudo-random function, encryption system modeling, authentication protocols, public-key cryptosystems, notions of security, zero-knowledge proofs, multi-party cryptographic protocols, security policies, legal and ethical issues, practical applications of encryption.

The pattern recognition course describes various methods and techniques that are used in pattern recognition.