Virginia Tech
Dr. Nizamani emphasizes hands-on, project-based learning with accessibility prioritized. Her teaching approach focuses on making complex concepts accessible to all students while preparing them for real-world challenges in computer science.
With 17+ years of experience across teaching, research, and academic service, Dr. Nizamani brings a wealth of knowledge to her courses, integrating cutting-edge research with foundational concepts.
This course develops problem-solving skills using computational thinking. Students learn to analyze problems, design solutions, and implement them effectively.
Credits: 3
Note: This course is part of the "LLM-Ready Graduates" research project, examining responsible integration of AI tools in CS education.
Overview of database management, database system architecture, and database modeling principles. Logical database design. The relational data model, relational algebra and SQL. Storage and indexing.
Prerequisites: CS 3114 with a grade of C or better
Credits: 3
Note: This course uses DBWorkout, a gamified SQL practice tool developed by the HICE Lab.
Senior capstone project course integrating computer science knowledge and skills acquired in previous courses. Team-based approach to solving open-ended computer science problems that address real-world problems in a variety of application areas, including approaches to problem formulation, requirements definition, design, and implementation. Communicating and presenting team results using both written and oral methods.
Prerequisites: CS 2506 & CS 3114 with a minimum grade of P
Credits: 3
Project-based design course in human-computer interaction. Students work in teams on an end-to-end, integrative interface design project drawn from interdisciplinary areas such as virtual reality, augmented reality, embodied cognition, visualization, semiotic engineering, game design, personal information management, mobile computing, design tools, educational technology, and digital democracy.
Prerequisites: CS 3724 and (HIST 2604 or SOC 2604 or STS 2604) and COMM 2084
Credits: 3
Basic principles and techniques in data analytics including data collection, data preprocessing, predictive modeling, descriptive modeling, and privacy and ethical issues.
Prerequisites: STAT 3006 or STAT 4105 or STAT 4705 or CMDA 2006 and (CS 1064 or CS 1114)
Credits: 3
Survey of human-computer interaction concepts, theory, and practice. Covers the basic components of HCI and its interdisciplinary foundations. Emphasizes informed and critical evaluation of computer-based technologies from a user-oriented perspective. Topics include cognitive and social aspects of users, interaction styles, input/output technologies, design guidelines, evaluation methods, participatory design, and communication between users and system developers.
Prerequisites: CS 1114 or CS 1044 or CS 1054 or CS 1064
Credits: 3
Advanced data structures and analysis of data structure and algorithm performance. Sorting, searching, hashing, and advanced tree structures and algorithms. File system organization and access methods.
Prerequisites: CS 2114 (Software Design and Data Structures) with a grade of C or better
Credits: 3