MS in Computer Science Focus Areas | Computer Science

Students earning a master's degree in computer science can choose to select areas from the following list. These are unofficial area categorizations meant to provide guidance to students in selection of courses that align with their interests and career goals.

Data Science and Information Systems

CS 515 - Social Media Data Sci Pipeline

The focus of this course is on applying data science techniques to large-scale social media. The topics covered include large-scale data collection, cleaning, and management, exploratory analysis and measurement techniques, hypothesis testing and statistical modeling, and predictive, real time analytics. Students will build an end-to-end analysis pipeline and use it to answer questions about online events as they occur. The goal of the class is to provide students with a methodological toolbox, the technical skills to make use of these tools, and the experience of using them on real world data. Prerequisite: Undergraduate Operating Systems, Undergraduate Algorithms, Probability with Stat Methods or equivalent. Term offered varies. 3 credits Levels: Graduate
CS 532 - Database Systems

Associations between data elements and data models: entity-relationship, relational and object-oriented. Relational database design techniques. Formal and commercial query languages. Introduction to query processing, transaction management and concurrency control. Prerequisite: Undergraduate Algorithms. Term offered varies. 3 credits Levels: Graduate, Undergraduate
CS 533 - Information Retrieval

Indexing and data structures for storing and searching the index. Boolean, statistical, inference nets and knowledge-based models. Thesaurus construction. Query expansion. Natural language and linguistic techniques. Evaluation. Distributed information retrieval. Information integration and fusion. Dissemination of information. Summaries, themes and reading tours. Hypertext. Internet tools. Intelligent agents. Digital libraries. Prerequisite: Undergraduate Algorithms. Term offered varies. 3 credits. Levels: Graduate, Undergraduate
CS 535 - Introduction To Data Mining

Basic topics of data mining, including data preprocessing, mining association rules, classification rules, clustering rules, post processing, and mining in unstructured data. Prerequisite: Undergraduate Algorithms and Probability & Statistics or equivalent. Term offered varies. 3 credits Levels: Graduate, Undergraduate
CS 536 - Intro to Machine Learning

This course provides a broad introduction to machine learning and its applications. Major topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, support vector machines); computational learning theory (bias/variance tradeoffs, VC theory, large margins); unsupervised learning; semi-supervised learning; reinforcement learning. The course will give students the basic ideas and intuition behind different techniques as well as a more formal understanding of how and why they work. The course will also discuss recent applications of machine learning, such as to data mining, bioinformatics, and information retrieval. Prerequisites: Undergraduate Algorithms, Probability with Statistical Methods. Term offered varies. 3 credits.. Levels: Graduate, Undergraduate
CS 555 - Intro to Visual Info Processin

The course focuses on fundamental topics, including visual information acquisition, representation, description, enhancement, restoration, transformations and compressions, and reconstruction from projections. The second focus is on Computer Science applications, including algorithms developed in applications such as statistical and syntactic pattern recognition, robotic vision, multimedia indexing, visual data mining, and bio-informatics. Prerequisite: Undergraduate Algorithms. Term offered varies. 3 credits Levels: Graduate, Undergraduate
CS 580E - Special Topics
CS 580P - Special Topics

Systems

CS 528 - Computer Networks

Communication protocols and layering, hardware-software infrastructures for networking, MAC protocols, data link protocols, switching, inter- and intra-domain routing, the TCP/IP protocol suite, transport protocols, application layer protocols, local and system area networks, wireless and sensor networks, overlay and virtual networks, client-server and peer-to-peer models, network programming with sockets, protocol design and implementation issues, network security. Prerequisite: Undergraduate Operating Systems. Term offered varies. 3 credits. Levels: Graduate, Undergraduate
CS 551 - Systems Programming

A detailed study of the application program interface of a modern operating system. File operations, concurrency, processes, threads, inter-process communication, synchronization, client-server programming, multi-tier programming. Prerequisite: Undergraduate Operating Systems. Term offered varies. 3 credits Levels: Graduate, Undergraduate
CS 552 - Intro to Cloud Computing

This course will provide students with topics in cloud computing with coverage of core cloud components such as virtualization techniques, distributed systems, cloud service models, and representative cloud computing systems. It will not only include the in-depth study of the fundamental enabling techniques such as server, network, and data storage virtualization, but also provide the demonstration of how these techniques work inside today’s widely-used cloud-based systems such as MapReduce, key-value stores, and Openstack. The course will include weekly assignments in the form of homework, labs, and projects. Prerequisite: Undergraduate Operating Systems. Term offered varies. 3 credits. Levels: Graduate, Undergraduate
CS 555 - Intro to Visual Info Processin

The course focuses on fundamental topics, including visual information acquisition, representation, description, enhancement, restoration, transformations and compressions, and reconstruction from projections. The second focus is on Computer Science applications, including algorithms developed in applications such as statistical and syntactic pattern recognition, robotic vision, multimedia indexing, visual data mining, and bio-informatics. Prerequisite: Undergraduate Algorithms. Term offered varies. 3 credits Levels: Graduate, Undergraduate
CS 557 - Intro To Distributed Systems

Fundamental issues in distributed systems. Distributed synchronization and concurrency control. Distributed process management (scheduling, remote invocation, task forces, load balancing). Protection and security. Robust distributed systems. Case studies. Prerequisite: Undergraduate Operating Systems. Term offered varies. 3 credits Levels: Graduate, Undergraduate
CS 680V - Advanced Special Topics

Wireless Sensors, Mobile Computing and IoT

CS 524 - Intelligent Mobile Robotics

The focus of this course is on intelligent mobile robots that can autonomously operate in indoor environments with limited human guidance. The topics covered in this course include mapping, localization, navigation, planning, reasoning, and human-robot interaction (language-based and vision-based). The students will learn to develop software in Robot Operating System (ROS) on real mobile robots. The goal of this course is to help students learn entry-level algorithms and programming skills that are required to conduct research in the area of intelligent mobile robotics. Prerequisite: Undergraduate Operating Systems and Algorithms. Term offered varies. 3 credits. Levels: Graduate, Undergraduate
CS 526 - Internet of Things

This course covers the applied area of Internet of Things (IoT). IoT are pervasive computing systems consisting of smart sensors embedded in physical environments with many promising applications. IoT challenge many classical approaches to computing and networking. Students will learn about key techniques in IoT through this course. A substantial part of the material will cover wireless sensor networks, embedded operating systems, and network protocols. A variety of different IoT applications will be introduced, including clinical monitoring, structural health monitoring, and industrial process automation. In this course, students will also have an opportunity to obtain hands-on experience on programming embedded devices to sense and communicate. Prerequisite: Either Undergraduate Operating Systems or Advanced Computer Architecture. Term offered varies. 3 credits. Levels: Graduate, Undergraduate
CS 528 - Computer Networks

Communication protocols and layering, hardware-software infrastructures for networking, MAC protocols, data link protocols, switching, inter- and intra-domain routing, the TCP/IP protocol suite, transport protocols, application layer protocols, local and system area networks, wireless and sensor networks, overlay and virtual networks, client-server and peer-to-peer models, network programming with sockets, protocol design and implementation issues, network security. Prerequisite: Undergraduate Operating Systems. Term offered varies. 3 credits. Levels: Graduate, Undergraduate
CS 541 - Game Dev For Mobile Platforms

This course focuses software development for mobile computing platforms, such as smartphones and tablets, with an emphasis on games. Students will develop interactive applications and utilize the wide variety of sensors and networking features available on the platform, along with basic elements of graphics programming and animation. The course also covers the mechanics of distributing software for mobile computing platforms. Both iOS and Android operating systems will be covered. The course will feature a mix of individual and team projects. Prerequisite: Programming with Objects & Data Structures, Java Programming, Undergraduate Algorithms or equivalents. Term offered varies. 3 Credits Levels: Graduate, Undergraduate
CS 551 - Systems Programming

A detailed study of the application program interface of a modern operating system. File operations, concurrency, processes, threads, inter-process communication, synchronization, client-server programming, multi-tier programming. Prerequisite: Undergraduate Operating Systems. Term offered varies. 3 credits Levels: Graduate, Undergraduate

Advanced Programming and Software Design

CS 540 - Adv Topics - Obj Oriented Prog

Object-oriented programming and its concomitant design patterns provide rich abstractions for program development. These programs will eventually execute on real hardware, however. This course will investigate advanced object-oriented techniques and how they interact with hardware and operating system issues. We will ground our topics in C++, but the goal of the course will be to develop understanding that can be applied across languages. We will examine different design techniques for things such as memory management, and explore how and why they differ in performance and robustness. We will also cover idioms such as "Resource Acquisition Is Initialization" (RAII) and how they can be used to provide robust resource management for exceptions (exception safety). We will also devote time to covering generic programming and related topics such as expression templates. This is a growing area that seeks to decouple algorithms and data structures through the use of templates and other meta-programming techniques. These techniques exploit the fact that the C++ template mechanism is a language-within-a-language that is executed at compile-time rather than run-time. Additional topics include dynamic linking for techniques such as "plug-ins", template instantiation mechanisms, template specialization, idioms for memory management, thread-safety issues, thread-safety, C++ reflection. Prerequisites: Undergraduate Operating Systems. Term offered varies. 3 credits. Levels: Graduate
CS 541 - Game Dev For Mobile Platforms

This course focuses software development for mobile computing platforms, such as smartphones and tablets, with an emphasis on games. Students will develop interactive applications and utilize the wide variety of sensors and networking features available on the platform, along with basic elements of graphics programming and animation. The course also covers the mechanics of distributing software for mobile computing platforms. Both iOS and Android operating systems will be covered. The course will feature a mix of individual and team projects. Prerequisite: Programming with Objects & Data Structures, Java Programming, Undergraduate Algorithms or equivalents. Term offered varies. 3 Credits Levels: Graduate, Undergraduate
CS 524 - Intelligent Mobile Robotics

The focus of this course is on intelligent mobile robots that can autonomously operate in indoor environments with limited human guidance. The topics covered in this course include mapping, localization, navigation, planning, reasoning, and human-robot interaction (language-based and vision-based). The students will learn to develop software in Robot Operating System (ROS) on real mobile robots. The goal of this course is to help students learn entry-level algorithms and programming skills that are required to conduct research in the area of intelligent mobile robotics. Prerequisite: Undergraduate Operating Systems and Algorithms. Term offered varies. 3 credits. Levels: Graduate, Undergraduate
CS 545 - Software Engineering

Software engineering practice applied to the life cycle of large software applications and engineering projects. Software project planning and management: risk management, estimation, scheduling, trade studies, CM and SQA. Software development: process model selection, domain analysis, requirements gathering, analysis and design modeling, user interface design, architectural and detailed design, documentation, testing strategies/methods, test plan generation, and reuse. Advanced topics include formal methods and cleanroom software engineering. Requires a major team project. Prerequisite: Undergraduate Algorithms Term offered varies. 3 credits Levels: Graduate, Undergraduate Restrictions: Must be enrolled in one of the following Levels: Permission of Department
CS 552 - Intro to Cloud Computing

This course will provide students with topics in cloud computing with coverage of core cloud components such as virtualization techniques, distributed systems, cloud service models, and representative cloud computing systems. It will not only include the in-depth study of the fundamental enabling techniques such as server, network, and data storage virtualization, but also provide the demonstration of how these techniques work inside today’s widely-used cloud-based systems such as MapReduce, key-value stores, and Openstack. The course will include weekly assignments in the form of homework, labs, and projects. Prerequisite: Undergraduate Operating Systems. Term offered varies. 3 credits. Levels: Graduate, Undergraduate
CS 572 - Compiler Design

Fundamentals of programming language translation. Compiler design concepts. General aspects of lexical analysis and parsing of context-free languages. Grammars and parsing techniques. Syntax-directed translation. Declarations and symbol management. Semantic processing and code generation. Principles, methods and examples of code optimization. Prerequisite: Programming Languages. Term offered varies. 3 credits Levels: Graduate, Undergraduate
CS 576 - Program Models Emerg Platforms

The landscape of computation platforms has changed dramatically in recent years. Computing devices such as Unmanned Aerial Vehicles (UAVs) are on the horizon. Big data processing becomes an indispensable part of numerous applications. Multi-core CPUs are commonly deployed in computer systems. Programming on these emerging platforms remains a challenging task. This course introduces a number of state-of-the-art programming models on these platforms, and further explores the frontier of next-generation programming language design that may potentially impact the future programming practice for emerging platforms. In particular, the course investigates UAV programming, Big Data programming, and multi-core programming, with additional presentations on other platforms on the rise. Applications of these programming models range from high-performance computing, cyber-physical systems, databases, to energy-conscious systems. Prerequisites: Java programming, Computer Architecture or Undergraduate Operating Systems. Term offered varies. 3 credits Levels: Graduate, Undergraduate
CS 560 - Computer Graphics

Concepts, structure, techniques, algorithms for use of modern interactive computer graphics systems. Graphics hardware, software system structure. Techniques and algorithms for basic graphics input-output functions. Matrix techniques for transformations and projections. Techniques for two- and three-dimensional modeling, rendering, animation and visualization. Prerequisites: Undergraduate Algorithms and Linear Algebra. Term offered varies. 3 credits Levels: Graduate, Undergraduate

Core track

CS 520 - Computer Architecture & Organ

Pipelined processors: basic theory, instruction pipelines, multifunction units, dynamic instruction scheduling, branch handling, precise interrupts. Compiler techniques for enhancing ILP. Pipelined vector machines. Superscalar, VLIW and EPIC architectures. High-speed memory system design. Overview of parallel/multiprocessor architectures: SIMD/MIMD systems, interconnection networks, synchronization and cache coherence. Prerequisite: Computer Architecture. Offered every semester when possible. 3 credits Levels: Graduate, Undergraduate
CS 550 - Operating Systems

Advanced topics in operating systems. Process synchronization, linguistic support for concurrency, virtual memory, deadlock theory, robustness, security, mathematical models and correctness of concurrent programs. Treatment of selected topics in distributed and multiprocessor operating systems. Prerequisite: Undergraduate Operating Systems. Offered every semester when possible. 3 credits Levels: Graduate, Undergraduate
CS 571 - Programming Languages

Selected topics in programming languages and alternative programming paradigms. Functional and imperative languages. Logic programming and object-oriented programming paradigms. Languages for concurrent computation. Semantics of programming languages. Prerequisite: Undergraduate Algorithims. Offered every semester when possible. 3 credits Levels: Graduate, Undergraduate
CS 575 - Design & Analysis Comp Algorit