Computer Science, BS
The Bachelor of Science in Computer Science program is designed for students who want to build the future of technology through software engineering, data science, and artificial intelligence. From their very first semester, students work in collaborative teams on real-world projects, applying design thinking, agile software engineering practices, and Scrum methodologies to develop innovative solutions. The curriculum combines a strong foundation in computer science with cutting-edge coursework in Data Science, Artificial Intelligence, Machine Learning, and Deep Learning, preparing graduates for high-demand careers in today’s rapidly evolving tech industry. Students gain hands-on experience using professional tools for project management, version control, collaboration, and software development while building applications and intelligent systems of increasing complexity. The program culminates in an exciting Capstone experience where students design and implement impactful, industry-inspired projects that often integrate AI and data-driven technologies. Beyond the classroom, students actively organize and compete in hackathons, participate in interdisciplinary research and innovation competitions, and engage with a vibrant computing community that emphasizes creativity, leadership, teamwork, and professional growth.
Learning Outcomes for Computer Science Program
The learning outcomes are based on the ABET program outcomes for computer science.
By graduation, students are expected to:
| a. | Be able to apply knowledge of computing and mathematics appropriate to the discipline |
| b. | Be able to analyze a problem, and identify and define the computing requirements appropriate to its solution |
| c. | Be able to design, implement, and evaluate a computer‐based system, process, component, or program to meet desired needs |
| d. | Be able to function effectively on teams to accomplish a common goal |
| e. | Understand professional, ethical, legal, security, and social issues and responsibilities |
| f. | Be able to communicate effectively with a range of audiences |
| g. | Be able to analyze the local and global impact of computing on individuals, organizations, and society |
| h. | Recognize the need for and an ability to engage in continuing professional development |
| i. | Be able to use current techniques, skills, and tools necessary for computing practice |
| CS-j. | Be able to apply mathematical foundations, algorithmic principles, and computer science theory in the modeling and design of computer‐based systems in a way that demonstrates comprehension of the tradeoffs involved in design choices |
| CS-k. | Be able to apply design and development principles in the construction of software systems of varying complexity |
Professional Prep
Computer Science majors develop the technical, collaborative, and problem-solving skills needed to succeed in today’s rapidly evolving technology landscape. The curriculum prepares students for careers in software engineering, artificial intelligence, data science, cybersecurity, cloud computing, and emerging technology fields by combining strong computing fundamentals with hands-on, project-based learning experiences.
Students learn to
- program in multiple languages and apply modern software development paradigms
- design, build, test, and deploy software systems using industry-standard Agile software engineering methodologies
- develop data-driven and AI-powered applications using machine learning, data science, and artificial intelligence techniques
- work with databases, algorithms, operating systems, networking, and cloud-based technologies
- use professional development and collaboration tools for version control, project management, testing, and team coordination
- apply design thinking principles to create innovative, user-centered computing solutions
- collaborate in multidisciplinary teams beginning in their first semester through group projects and applied learning experiences
- participate in internships, hackathons, research projects, and innovation competitions that mirror real-world computing environments
- conduct computing-based research and contribute to interdisciplinary projects involving AI and data analytics
- communicate technical ideas effectively to both technical and non-technical audiences
- evaluate the ethical, legal, security, and societal implications of computing and artificial intelligence technologies
- prepare for technical interviews, professional certifications, and careers in a highly competitive and rapidly changing technology workforce
Faculty
Delaware State University’s Computer Science faculty are dedicated mentors, innovators, and active researchers who work closely with students both inside and outside the classroom. Faculty members bring expertise from a wide range of advanced computing and interdisciplinary fields, creating an engaging learning environment where students are encouraged to explore emerging technologies, contribute to research, and develop solutions to real-world challenges. Students benefit from personalized mentorship, career guidance, and opportunities to collaborate directly with faculty on research projects beginning early in their academic journey.
Research and Experience and Mentorship
Faculty research interests span cutting-edge areas including artificial intelligence, machine learning, computational intelligence, data mining and knowledge discovery, computational biology and bioinformatics, Edge Computing, distributed learning, network optimization, next-generation wireless networks, Edge-AI applications, and interdisciplinary research at the intersection of mathematics, data science, AI, and advanced analytics. Faculty are also engaged in science education research, innovative teaching methodologies, and the development of computational assessment tools that improve learning and student success.
Through faculty-led research initiatives, students have opportunities to participate in interdisciplinary projects involving AI, data science, healthcare, engineering, business, cybersecurity, and scientific computing. Students work alongside faculty on applied research, software development, data analysis, and intelligent systems design while gaining valuable hands-on experience that strengthens both graduate school and career preparation. Many students also present their work at conferences, participate in research competitions and hackathons, and collaborate on innovative projects that connect classroom learning with industry and societal impact.