COURSE CURRICULUM

The Computer Science (CS) graduate course offerings at Texas State University provide a comprehensive and advanced curriculum designed to support students in fields such as artificial intelligence, software engineering, data science, and systems computing. The program includes a mix of foundational, core, and specialized courses, along with research and thesis options. Foundational courses such as programming practicum, data structures, computer architecture, and operating systems help students strengthen essential concepts, although these do not count toward the graduate degree. Advanced courses cover a wide range of topics including machine learning, generative AI, reinforcement learning, data mining, algorithm design, robotics, distributed systems, and computer networks, ensuring students gain both theoretical knowledge and practical skills. Specialized subjects like responsible and trustworthy AI, blockchain technologies, computer security, and green computing address modern challenges in technology and ethics. The curriculum also emphasizes software development through courses in software engineering, quality assurance, and large-scale project development, preparing students for real-world applications. For students interested in research, multiple thesis enrollment courses are available, allowing them to conduct in-depth studies under faculty supervision, while independent study options provide flexibility for specialized interests. Additionally, internship and professional development courses support career readiness, though some are non-credit. Overall, the CS course structure equips students with strong technical expertise, problem-solving abilities, and research experience, preparing them for careers in industry, academia, and advanced technological innovation.