Teaching

Introduction to concepts, tools and techniques of machine learning for applications. Selected machine learning algorithms in practical data mining tasks such as classification, regression, and clustering, e.g., association rules, decision trees, linear models, Bayesian learning, support vector machines, artificial neural networks, instance-based learning, probabilistic graphical models, ensemble learning, and c lustering algorithms. Selected applications in data mining and pattern recognition.

Data models and database design using entity relationship model. Database implementation with relational and graph database management systems (DBMS) and query languages. DBMS internals including basic concepts of database storage, indexing, query optimization, and concurrent control. Database application development. Programming Projects.

Contemporary database systems. Emphasis on query processing, design, and implementation of applications in relational (SQL) databases. Introduction to other database models such as XML, object-oriented, and deductive.

The goal of this course is to provide a comprehensive overview of the state-of-the-art in virtual reality technologies and 3D user interfaces. Classroom topics will include display systems, motion tracking, spatial interaction techniques, human factors, and applications Students will learn how to develop virtual reality experiences through hands-on programming assignments using Oculus Quest headsets. Theoretical and practical knowledge will be evaluated through quizzes throughout the semester and applied in a course project.

Techniques and strategies used in operating system design and implementation–managing processes, input/output, memory, scheduling, file systems, and protection.

Survey of concepts and techniques for human-computer interface development. Topics include user-centered design, user interface programming, and usability evaluation.

Students are exposed to current approaches, techniques and best practices for collecting, cleaning and normalizing data, processing, storing, managing, securing and preparing structured and unstructured big data sets for analytics.