Computer Science

This course offers a study of interactive ecosystems. Topics include: human-centered informatics; paradigms, styles, and principles of interaction; design approaches; designing and prototyping of interactive ecosystems; evaluation.

This course covers the basic skills needed to create, examine, appreciate, and understand computational art. It covers basic programming skills in Python, experience using tools for live coding music, creating animations, and hands-on experience using generative AI technologies. Topics include strings, programs as files, semantics, functions; conditionals, Iteration, functions vs methods; lists, dictionaries, sets, reading and writing to files; audio programming, sequencing events in time, randomness, signal processing; animations, graphics, user interaction, performance considerations; and introduction to generative AI, stable Diffusion, and text processing. 

The course covers fundamental engineering and mathematical concepts for understanding the wired network technologies, internet architectures and protocols, and networking programming.

This course examines key theories, concepts and industry methods that are crucial to the user-centered design process.

This course explores digital marketing and search engine positioning including the role of web positioning in digital marketing and the mechanisms of Google. This course also covers Search Engine Optimization (SEO) and web analytics (on-site and off-site).

This course focuses on concepts that enable the integrated application of management, control, and development processes in the software development life cycle. Topics include: modern software development methodologies; software or service initial offer; software configuration management; quality management; feasibility analysis; software projects estimation, planning, analysis, and design techniques; tools to support management, control, and development processes.

This course covers the principles of database systems. Toics include conceptual modeling and data models; logical and physical database design; query languages and query processing; database services, including concurrency, crash recovery, security, and integrity; hands-on DBMS experience. Text: A. Silberschatz, H. Korth, and S. Sudershan, DATABASE SYSTEM CONCEPTS. Assessment: assignments, midterm exam, and final exam.

This course provides computational skill development. It examines computational problem formation and tools for problem solving (Excel and Python). Other topics include decomposition and pattern recognition, abstraction and algorithm design, information utilization and storage (tables and databases), information presentation (data visualization), ethical usage of digital content and technology, and privacy.