Teaching

Deep Neural Network

The subject will focus on basic mathematical concepts for understanding nonlinearity and feedback in neural networks, with examples drawn from both neurobiology and computer science. There will be some discussion of statistical pattern recognition, but less than in the past, because this perspective is now covered in Machine Learning and Neural Networks.

Fuzzy Logic

To master the various fundamental concepts of fuzzy logic and artificial neural networks. This will help you to get sufficient knowledge to analyze and design the various intelligent control systems

Data mining

This course is an introductory course on data mining. It introduces the basic concepts, principles, methods, implementation techniques, and applications of data mining, with a focus on two major data mining functions: (1) pattern discovery and (2) cluster analysis.

Computer Programming II (C/C++ Programming) 

This course introduces the student to object-oriented programming through a study of the concepts of program specification and design, algorithm development, and coding and testing using a modern software development environment. Students learn how to write programs in an object-oriented high-level programming language. The topics covered include the fundamentals of algorithms, flowcharts, problem solving, programming concepts, classes and methods, control structures, arrays, and strings. 

Formal Language and Automata

An introduction to the abstract concepts that are encountered in the process of computing on a machine. This course covers a variety of topics, including finite automata, regular expressions, and formal languages, with a primary focus on context-free and regular grammars. Examining a number of different models of computing, such as recursive functions, universal machines, and Turing machines, helps answer questions about the capabilities of machines, such as what they are capable of and what they are unable to achieve.