Algorithms [Algorithm OSS Practice]
This course is designed to introduce undergraduate students to the fundamental concepts and ideas in computer algorithm. It develops an in-depth understanding of the computational approaches available for solving real-life problems. The prerequisites include adequate experience with programming and knowledge of standard concepts in data structure.
This course is designed to introduce undergraduate students to the fundamental concepts and ideas in artificial intelligence. It develops an in-depth understanding of the computational approaches available for solving real-life problems, including the problem solving by searching, clustering, classification, knowledge discovery, and logical inference.
This course provides graduate students with an introduction to the wide range of algorithms and methodologies in data mining. The science of extracting useful information from large data sets or databases is known as data mining. Data mining is defined from the textbook as the analysis of observational data sets to find unsuspected relationships and to summarize the data in novel ways that are both understand and useful to the data owner.
Advanced Artificial Intelligence
This course is designed to introduce graduate students to the fundamental concepts and ideas for solving real-life problems in terms of the problem search techniques. The textbook provides comprehensive, current, and correct information on problem solving using modern heuristics. It covers classic methods of optimization, including dynamic programming, the simplex method, and gradient techniques, as well as recent innovations such as simulated annealing, tabu search, and evolutionary computation.