This programming intensive course with its weekly lab component provides an exploration in problem solving for graduate-level courses, using object-oriented programming in a language such as Java.

This course explores introductory data structures including array lists, linked lists, stacks, queues, binary trees, and hash tables. Efficiency of data structure operations is analyzed. Recursion, applications of data structures, and simple analysis of algorithms are covered. Students will be able to select appropriate data structures to integrate into algorithms to solve computational problems.

This course explores advanced abstract data types in depth, such as sets, maps, and graphs, and reproduces their implementation using arrays and dynamically allocated nodes in an object-oriented language. The course also analyzes the performance of the data structures' built-in operations and related algorithms such as sorting, searching, and traversing.

This course introduces students to the Unix shell environment and essential tools.

This course provides the mathematical foundations for graduate-level study in computer science, including such topics as complexity of algorithms, modular arithmetic, induction and proof techniques, graph theory, combinatorics, Boolean algebra, logic circuits, and automata.

This is a foundations course on computer security, covering a comprehensive range of concepts and technologies, including security goals, encryption, penetration testing, software exploitation, reverse engineering, packet sniffing, and secure coding. The final project requires a presentation and technical report where the students will show and describe what they accomplished.

Application of concepts and methods for managing production and service operation. Topics include demand forecasting, aggregate and capacity planning, inventory management, facility layout and location, just-in-time, managing quality, project planning, resource allocation, logistics. Emphasis on decision support.

This course focuses on the manager's role in leading Organization Development and Change to maximize organization and individual effectiveness with a focus on Information Technology. The class explores Organization Development and Change theory, change practices, and discusses considerations a manager will face as a change agent in today's computing ecosystem.

Knowledge of the configuration and management skills needed for successful administration of a database server. The database administrator manages hardware, backup, security, tables and indexes, performance monitoring, query performance and optimization, and transaction performance. This course takes a user through the stages of maximizing the performance of a database server.

This course covers theory and practice of the analysis (mining) of extremely large datasets. With data growing at exponential rates knowledge gathering and exploration techniques are essential for gaining useful intelligence.

An introduction to advanced numerical analysis. Introduction to error analysis, numerical solution of equations, interpolation and approximation, numerical differentiation and integration, matrices, and solution of systems of equations, numerical solution of ordinary and partial differential equations.

The course introduces advanced operating system concepts including distributed, real-time and multi-threaded in addition to reviewing memory management, files, and processes.

This course will cover the fundamentals of Free and Open Source software development. Topics to be addressed include licensing, Linux, typical software development tools, applications, and techniques for managing remote servers.

Principles of object-oriented design and implementation, including object modeling (UML or equivalent), interface design, refactoring and test-driven development. Study of design patterns, including Adaptor, Decorator, Iterator, Abstract Factory, etc. Coverage of implementation tools including IDEs, source-code control and testing.

This course covers social, legal, and ethical issues commonly arising in key areas related to computing technologies.

The course covers basic combinatorial theory including permutations and combinations, the inclusion-exclusion principle and other general counting techniques, partitions, generating functions, recurrence relations, Burnside's Theorem, the cycle index, and Polya's formula.

This course uses Unified Modeling Language and similar notation to model the early software analysis and design phases, from collection of user requirements to determination of class needs through object-oriented design.

This course covers tools for analyzing problems that are mathematically difficult. Discrete event simulation techniques and software tools for simulating processes are covered.

This course will focus on the methods, tools, and technologies for developing software applications for wireless and mobile devices, such as personal digital assistants (PDA) and smart mobile phones.

This course provides an in-depth study of the concepts and methods required for the design and implementation of the presentation layer of a web application. Coursework includes several substantial programming projects.

This course will teach students how to design Rapid Application Development using an integrated development environment such as the .NET framework and methodology. It is designed to support object-oriented programming concepts.

In this course, major types of error-correcting codes, encoding and decoding , and their main properties will be studied. The codes examined will include the Hamming, Golay, BCH, cyclic, quadratic residue, Reed-Solomon, and Reed-Muller codes.

In this course, students examine in depth the problems, methods, and applications of NLP. Topics will include information retrieval, sentiment analysis, machine translation, document classification, and question answering. We will also cover the underlying theory from probability, statistics, and machine learning that are crucial for the field.

This course introduces the formal foundations of cryptography and also investigates some well-known standards and protocols, including private and public key cryptosystems, hashing, digital signatures, RSA, DSS, PGP, and related topics.

Web services are Web-based enterprise applications that use open, XML-based standards and transport protocols to exchange data with calling clients. This course provides the APIs and tools you need to create and deploy interoperable Web services and clients using .NET and Java WSDP.

The course shows how to use Enterprise JavaBeans to develop scalable, portable business systems. The technologies taught in the course include: component models, distributed objects, asynchronous messaging, and component transaction monitors.

This course is concerned with XML and its various component frameworks. The core frameworks to be covered include Document Object Model (DOM), Simple API for XML processing (SAX), the XML Path language (XPath), and XSLT.

Many real-world software systems rely on concurrency for performance and modularity. This programming-intensive course covers analysis, design, implementation, and testing of concurrent software systems.

This course presents a modern discussion of distributed computing systems. Distributed computation, interactive services, collaborative computing, peer-to-peer sharing, and grid/utility computing are just a handful of distributed technologies that go beyond the capabilities of the traditional client/server model by allowing a collection of computers to be leveraged as a collective resource.

This course introduces the fundamentals of computer/network/internet forensics, analysis and investigations.

This course studies the interaction between humans and computer-based systems. The course will provide students with the methods for evaluating, designing, and developing better interfaces between humans and systems.

Server-based web applications and services have become part of everyday life. This programming-intensive course covers analysis, design, implementation, and testing of multi-tiered server-based software systems along with typical tier-specific and technologies.

Students should also have completed COMP 400D or equivalent. This course surveys packet-switched computer networks and attendant communication protocols, using the TCP/IP protocol suite on which the Internet is based as the primary model. We will also study general high-level network issues such as security, authentication, fault tolerance, and congestion.

This course considers the safety, security, reliability, and privacy concerns of the embedded devices and cloud-based resources of the Internet of things. The course discusses methods for addressing these concerns.

This course introduces the fundamental concepts of telecommunication networks. Underlying engineering principles of telephone networks, computer networks and integrated digital networks are discussed.

This course will cover techniques for detecting the unusual usage patterns that typically signal a break-in. The course will also consider differences in detection of local intruders versus intrusion over networks. Finally issues in the prosecution of those breaking in to computers, particularly evidentiary issues are explored.

This course will involve a discussion of the methods and tactics used to keep attackers at bay as well as the mechanisms by which we can identify and potentially stop potential intruders. The course covers topics such as Encryption, authentication, firewalls, NAT/PAT, restricted access policies, intrusion detection and other security frameworks.

This course will explore the wireless standards, authentication issues, common configuration models for commercial versus institution installs and analyze the security concerns associated with this ad-hoc method of networking.

Management of complex, high-speed, heterogeneous computer networks. Device management using SNMP and related protocols. Configuration and use of Network Management Systems. Data-flow management using LARTC and similar tools.

This course will introduce students to computer vulnerabilities at the machine-code level, including viruses, browser vulnerabilities, buffer and heap overflows, return-to-libc attacks and others.

This course will cover advanced concepts in database access and programming including SQL, JDBC, SQLJ, JSP and servlets. Oracle 10g is used for projects.

In this course, large data sets will be leveraged to solve challenging analytics problems. With more samples, analytics can use more complex learning models to automate more feature combinations for more robust model tuning, selection, and validation. Parallel, distributed processing will be performed with Apache Spark and Hadoop.

This course will focus both on presenting general techniques for designing correct and efficient algorithms, as well as on formal methods for proving the correctness and analyzing the complexity of such algorithms.

This course presents key principles underlying the design of modern digital computers. The course introduces quantitative techniques used to guide the design process. It describes CPU performance issues and introduces instruction set architectures. The course then uses a hypothetical computer design, with a simple RISC architecture, to show how modern digital computers are implemented, first using a simple non-pipelined implementation, followed by a higher-performance pipelined implementation.

This course will use a blend of foundational understanding as well as a set of practical tools to gain insight into performance engineering of software. The course introduces techniques to gain performance boost in Java programs and C++ (or C) programs by discussing the use of multiple processors.

The course covers both relational and object databases. Issues of physical storage and use of indexes as well as optimization of queries are discussed. The course also covers transaction processing, concurrency, data warehousing, data mining, and distributed databases.

This course explores how things are made, including: physical design vs. design on non-physical things; rapid prototyping; 3D printing; 2D conceptualization and sketching; modeling.

In this programming intensive course, students will learn effective automation, testing, and use of software metrics through the practices of Test Driven Development and Continuous Deployment.

This course covers the basics of writing a compiler to translate from a simple high-level language to machine code. Topics include lexical analysis, top-down and LR parsing, syntax-directed translation, and code generation and optimization. Students will write a small compiler.

Object-orientation continues to be a dominant approach to software development. This advanced programming-intensive course studies object-oriented analysis, design, and implementation from a design patterns perspective.

The course discusses real-world theory and techniques organizations use to create high-quality software on time. Students work on a large programming team to create plans, review progress, measure quality, and make written and oral analyses of their project.

This course introduces formal language theory, including such topics as finite automata and regular expressions, pushdown automata and context-free grammars, Turing machines, undecidability, and the halting problem.

This course is an introduction to the philosophy and practice of project management. The course involves a student group project to investigate and plan a 'real world' IT project that specifies project objectives, schedules, work breakdown structure, and responsibilities, an written interim report, and a final oral and written report.

Topics include a wide variety of supervised learning methods, both regression and classification, with an emphasis on those that perform well on large feature sets.

This course introduces advanced topics in modern theory and practices in 3-D computer graphics, stressing real-time interactive applications using libraries like OpenGL.

This course presents an algorithmic focus to problems in computational Biology. As such it is built on earlier courses on algorithms and bioinformatics. Current algorithmic approaches, software tools, and scientific literature are discussed.

This course advanced artificial intelligence concepts including theory, search techniques and programming.

Introduces computational methods to understand neural processing in the brain. Levels of representation from low-level, temporally precise neural circuits to systems-level rate-encoded models, to information-theoretic approaches. Emphasis on sensory systems, primarily vision and audition, most readily demonstrating the need for such computational techniques.

Deep learning is part of a broader family of machine learning methods based on artificial neural networks. This course will include key concepts of neural network algorithms as well as their applications in computer vision and natural language processing.

This course is used to introduce emerging topics in computer science that do not yet have a regular course number. Content of the course varies.

This class covers the design of computer science courses through an equity and inclusion lens, and covers evidence-based best practices as applied to specific student concerns. Includes basics of teaching and learning theory and pedagogical techniques, and equity, diversity, and justice concerns.

This class covers grant-proposal development, University compliance regulations, and laboratory and research management.

Independent study for PhD research, for students who have not yet completed the required credit hours.

Dissertation work under the supervision of a faculty member.

Dissertation preparation course, for when student has completed coursework but before student has defended their dissertation proposal. Can be taken only twice during a doctoral student's career at LUC.