Computing Systems, Computer Science Master's Degree

Emerging Computing Systems offers learners an exploration into the cutting-edge technologies and trends driving the future of computing, with a particular focus on internet computing systems. This course explores advanced computing topics, providing an in-depth analysis and evaluation of state-of-the-art technologies across nine broad categories: hardware architectures and operating systems, networking and distributed systems, cloud and data centers, system design and integration, security, performance and scalability, system integration, energy efficiency, and emerging technologies. The course will critically examine emerging technologies, their design principles, and their system optimizations and provide insights to the design and optimization of modern computing systems. This course provides a blend of conceptual learning and practical application, allowing students to develop the expertise needed to lead in the evolving computing landscape. Computer Architecture and Systems is a prerequisite for this course.

Formal Languages Overview introduces students to programming language design and theory, focusing on formal semantics and type systems. It covers imperative, functional, and parallel languages, emphasizing techniques for proving language properties and verifying program specifications. Students will differentiate between functional and procedural languages, and explore compiled, interpreted, query, and assembly languages. The course also examines the structure and features of programming languages, including object-oriented programming principles. Learners will understand program correctness, testing, and verification, addressing type correctness. This course prepares students to assess programming languages against business requirements, enhancing software reliability and efficiency. Aimed at those interested in the theoretical underpinnings of programming languages, it equips students with knowledge to make informed decisions in software development and application.

Computer Architecture and Systems offers a comprehensive examination of the design and development of computer systems. Students will explore the evolution of computer architecture, understanding how computers have advanced and changed over time. The course covers different layouts and designs used in both hardware and software solutions, helping students to grasp the complex structures of computer systems. Students will learn how to develop detailed plans for implementing computing solutions that work across various platforms. The course likewise covers how to integrate various devices to ensure they operate and communicate smoothly with each other.

This course builds on foundational knowledge of algorithm design and optimization for efficient resource utilization. It emphasizes benchmarking algorithms, reasoning, and applying Big O notation for performance evaluation. This course will cover how to design, analyze, and implement algorithms to solve complex computational problems, focusing on optimizing performance and enhancing system efficiency. The practical applications in this course involve testing data structures, developing algorithmic solutions, and optimizing algorithm performance through critical analysis and implementation. By integrating computational thinking and engineering principles, this course will present the skills students need to develop and optimize algorithms for real-world software, using benchmarking and profiling tools to measure and enhance performance.

Unix and Linux offers a comprehensive introduction to these operating systems, focusing on essential skills used in system administration and development roles. This course equips students with the ability to employ the most common commands, navigate the Unix/Linux shell, manage files and directories, configure the shell environment, and create shell scripts to automate routine tasks. This hands-on approach prepares students to competently manage and maintain Unix and Linux systems in real-world applications. There are no prerequisites for this course.

Artificial Intelligence and Machine Learning Foundations explores foundational concepts and practical applications of artificial intelligence (AI) and machine learning (ML). It provides students with an understanding of the historical context and evolution of AI and the subsequent growth phases of AI technologies. This course will investigate the computational theories and logical frameworks that have shaped the AI landscape, examining how advancements in hardware have enabled the leap from basic ML to the complexities of deep learning. The course emphasizes the practicalities of AI and ML and gives insights into the critical role of data integrity and the techniques for data wrangling to feed into ML algorithms effectively. In addition to the technical skills, the course incorporates the societal implications of AI and ML, discussing current ethical considerations. This course aims to create a nuanced understanding of AI and ML, preparing students to thoughtfully consider the broader impacts of these technologies. There are no prerequisites for this course.

Mobile and Ubiquitous Design blends in-depth technical knowledge of computing systems like sensors, processors, embedded systems design, communication protocols, and connectivity technologies with user-centered design principles for creating functional and engaging mobile applications. The course will demonstrate how to apply design thinking and UX methods such as user personas, usability testing, and addressing real-world challenges to develop scalable, secure, and ethical solutions that optimize the interplay between various devices. By emphasizing privacy considerations and the ability to adapt across different user environments, this course prepares students to become proficient in analyzing user needs and designing synchronized multi-device systems through mobile apps that effectively meet those requirements.

Governance, Risk, and Compliance provides learners with advanced skills and knowledge to authorize and maintain information systems utilizing various risk management frameworks. The course focuses on the strategic and long-term alignment of an organization's information security program to regulatory requirements and organizational policies. Course topics include compliance and regulatory requirements, data classification and prioritization, security and privacy controls, compliance audits and remediation, and risk management plans.

This course covers topics in designing, analyzing, and managing large-scale software systems. Students will learn various architecture types, how to select and implement appropriate design patterns, and how to build well-structured, reliable, and secure software systems.

In this course, students are equipped to understand, analyze, and implement cloud computing solutions tailored to diverse business needs. The curriculum offers an in-depth look at state-of-the-art cloud technologies, the underlying business trends fueling cloud adoption, and the foundational systems of modern data center computing. Participants will learn to identify and apply various cloud systems to specific business cases, understand the interplay between network systems to form cloud computing environments, and utilize cloud computing models to address infrastructure challenges. A focus on network security enables learners to assess and enhance network security systems, covering cybersecurity principles, perimeter security, authentication, and the creation of secure networks. The course also delves into scalable distributed systems and programming frameworks that facilitate edge computing, illustrating how cloud-based solutions can resolve real-world business problems.