SWE601 – Software Engineering (3 Credit Hours)
Prerequisite: None
This course provides a comprehensive overview of the methodologies and tools used in software development, focusing on key phases such as requirements analysis, design, testing, and maintenance. Students will gain hands-on experience with industry-standard practices and tools, emphasizing the importance of adhering to best practices and established standards in software engineering. The course is designed to prepare students to tackle real-world software development challenges effectively and efficiently.
CSC602 – Advanced Computer Architecture (3 Credit Hours)
Prerequisite: None
This course covers the principles of computer architecture, focusing on the design and analysis of modern computing systems. Key topics include instruction set design, pipelining, memory hierarchies, parallel processing, and advanced architectural techniques used in contemporary processors.
AIM610 – Introduction to Artificial Intelligence (3 Credit Hours)
Prerequisite: None
This course introduces students to the fundamental concepts and techniques in artificial intelligence (AI). It covers a range of topics including search algorithms, knowledge representation, reasoning, learning, and the ethical implications of AI. Through a combination of theoretical study and practical applications, students will develop a strong foundation in AI, preparing them for more advanced topics and specialized areas within the field.
CSC603 – Design and Analysis of Algorithms (3 Credit Hours)
Prerequisite: None
This course provides an in-depth exploration of algorithm design and analysis, emphasizing efficient problem-solving techniques across various computational challenges. Students will study core algorithmic strategies, including sorting, searching, and graph algorithms, while also delving into complexity theory to understand the theoretical limits of computational efficiency. The course equips students with the skills necessary to analyze and implement algorithms that are both effective and efficient for a wide range of applications.
CSC604 – Distributed Operating System Principles (3 Credit Hours)
Prerequisite: None
This course delves into the principles and design of distributed operating systems, providing a comprehensive understanding of how these systems manage resources across multiple computers. Students will explore key topics such as synchronization mechanisms, distributed file systems, and strategies for achieving fault tolerance. The course emphasizes the challenges and solutions associated with ensuring consistency, reliability, and efficiency in a distributed environment.
CYB620 – Network Security (3 Credit Hours)
Prerequisite: None
This course provides an in-depth exploration of the principles and practices of network security, focusing on the latest techniques for defending against network attacks. Students will learn about various security protocols, network architectures, and methodologies for identifying and mitigating threats in networked systems. The course emphasizes practical skills and the application of security strategies in real-world scenarios.
CYB630 – Cybersecurity Risk Management (3 Credit Hours)
Prerequisite: None
This course provides an in-depth exploration of methods for assessing and managing cybersecurity risks within organizations. Students will learn to identify potential threats, evaluate their impact, and develop strategies to mitigate risks while ensuring business continuity. The course covers risk assessment frameworks, compliance requirements, and the role of cybersecurity in corporate governance. Emphasis is placed on applying theoretical concepts to real-world scenarios, enabling students to effectively manage cybersecurity risks in various organizational settings.
AIM620 – Machine Learning (3 Credit Hours)
Prerequisite: None
This course offers a comprehensive introduction to machine learning algorithms and their applications. Students will explore key concepts in supervised and unsupervised learning, as well as advanced topics such as neural networks and deep learning. The course emphasizes both theoretical understanding and practical implementation of machine learning techniques, preparing students to apply these methods to real-world data-driven problems.
DAT620 – Big Data Analytics (3 Credit Hours)
Prerequisite: None
This course provides a comprehensive overview of the methods and technologies used for the analysis and processing of big data. Students will explore the challenges associated with big data and learn how to leverage modern tools and frameworks, such as Hadoop, Spark, and NoSQL databases, to extract insights from large datasets. The course emphasizes both the theoretical aspects of big data analytics and hands-on experience with processing large-scale data in real-world scenarios.
CSC630 – Cutting-Edge Technologies (3 Credit Hours)
Prerequisite: None
This course delves into cutting-edge advancements in artificial intelligence (AI), focusing on the latest research, technologies, and methodologies driving the field forward. Students will explore complex topics such as explainable AI, AI ethics, and AI governance, along with the societal implications of deploying advanced AI systems. The course emphasizes critical thinking and encourages students to engage with ongoing debates about the role of AI in society, ensuring they are well-prepared to contribute to the responsible development and application of AI technologies.
CYB611 – Cryptography (3 Credit Hours)
Prerequisites: None
This course provides a comprehensive introduction to the fundamental algorithms and protocols used in cryptography for securing data. Students will explore the theoretical foundations and practical applications of cryptographic techniques, including symmetric and asymmetric encryption, hashing, digital signatures, and cryptographic protocols. The course emphasizes both the mathematical underpinnings of cryptography and its real-world applications in securing communications, data, and systems.
CSC699 – Capstone Project (3 Credit Hours)
Prerequisites: Core Courses
The Capstone Project is a core course that challenges students to apply their computer science knowledge to solve real-world problems in areas like artificial intelligence, cybersecurity, cloud computing, among others. The course involves significant collaboration with faculty and industry professionals to refine solutions, ensuring they are applicable to current technological challenges.