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Courses - Spring 2023
CMSC
Computer Science Department Site
CMSC100
Bits and Bytes of Computer and Information Sciences
Credits: 1
Grad Meth: Reg
Restriction: For first time freshmen and first time transfer students.
Cross-listed with: INST101.
Credit only granted for: CMSC100 or INST101.
Students are introduced to the fields (and disciplines) of computer science and information science within a small classroom setting. They will learn to make a successful transition from high school to the university, while exploring study skills, student success plans and research opportunities.
CMSC106
Introduction to C Programming
Credits: 4
Grad Meth: Reg
Prerequisite: MATH115.
Restriction: Must not be in Computer Science program; and must not have completed any courses from CMSC131-499 course range.
Credit only granted for: CMSC106 or CMSC122.
Design and analysis of programs in C. An introduction to computing using structured programming concepts. Intended for students with no or minimal programming experience.
CMSC122
Introduction to Computer Programming via the Web
Credits: 3
Grad Meth: Reg
CORE: IE
GenEd: DSSP
Restriction: Must not have completed any courses from CMSC131-499 course range; and must not be concurrently enrolled in CMSC131.
Credit only granted for: CMSC106, or CMSC122.
Introduction to computer programming in the context of developing full featured dynamic web sites. Uses a problem solving approach to teach basics of program design and implementation using JavaScript; relates these skills to creation of dynamic web sites; then explores both the potential and limits of web-based information sources for use in research. Intended to help relate a student's major to these emerging technologies.
CMSC125
Introduction to Computing
Credits: 3
Grad Meth: Reg
GenEd: DSSP
Prerequisite: Must have completed or be concurrently enrolled in MATH115 or higher.
Restriction: Must not be in the Computer Science program; and must not have completed any courses from CMSC131-499; and must not have completed BMGT302, IMDM127 or INST126.
Introduces you to the computing field as a whole. You will gain skills used across the spectrum of computing majors and learn about the great variety of routes into the various areas of study and employment in technological fields.
CMSC131
Object-Oriented Programming I
Credits: 4
Grad Meth: Reg
Corequisite: MATH140.
Credit only granted for: CMSC131, CMSC133, or IMDM127.
Introduction to programming and computer science. Emphasizes understanding and implementation of applications using object-oriented techniques. Develops skills such as program design and testing as well as implementation of programs using a graphical IDE. Programming done in Java.
CMSC132
Object-Oriented Programming II
Credits: 4
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC131; or must have earned a score of 5 on the A Java AP exam; or must have earned a satisfactory score on the departmental placement exam. And minimum grade of C- in MATH140.
Introduction to use of computers to solve problems using software engineering principles. Design, build, test, and debug medium -size software systems and learn to use relevant tools. Use object-oriented methods to create effective and efficient problem solutions. Use and implement application programming interfaces (APIs). Programming done in Java.
CMSC216
(Perm Req)
Introduction to Computer Systems
Credits: 4
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC132; and minimum grade of C- in MATH141.
Restriction: Must be in a major within the CMNS-Computer Science department; or must be in Engineering: Computer program; or must be in the Computer Science Minor program; and Permission of CMSC - Computer Science department.
Introduction to the interaction between user programs and the operating system/hardware. Major topics include C programming, introductory systems programming, and assembly language. Other concepts covered include UNIX, machine data representation, thread management, optimization, and virtual memory. Programming is done in the Linux Environment.
CMSC250
(Perm Req)
Discrete Structures
Credits: 4
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC131; and minimum grade of C- in MATH141.
Restriction: Must be in a major within the CMNS-Computer Science department; or must be in Engineering: Computer program; or must be in the Computer Science Minor program; and Permissions of CMSC - Computer Science department.
Fundamental mathematical concepts related to computer science, including finite and infinite sets, relations, functions, and propositional logic. Introduction to other techniques, modeling and solving problems in computer science. Introduction to permutations, combinations, graphs, and trees with selected applications.
CMSC250H
(Perm Req)
Discrete Structures
Credits: 4
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC131; and minimum grade of C- in MATH141.
Restriction: Must be in a major within the CMNS-Computer Science department; or must be in Engineering: Computer program; or must be in the Computer Science Minor program; and Permissions of CMSC - Computer Science department.
Fundamental mathematical concepts related to computer science, including finite and infinite sets, relations, functions, and propositional logic. Introduction to other techniques, modeling and solving problems in computer science. Introduction to permutations, combinations, graphs, and trees with selected applications.
Prerequisite: Minimum grade of C- in CMSC131; and minimum grade of C- in MATH141; and permission of CMNS-Computer Science department.
CMSC298A
(Perm Req)
Special Topics in Computer Science
Credits: 1 - 4
Grad Meth: S-F
Contact department for information to register for this course.
CMSC320
(Perm Req)
Introduction to Data Science
Credits: 3
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC216 and CMSC250.
Restriction: Permission of CMNS-Computer Science department.
Credit only granted for: STAT426 or CMSC320.
An introduction to the data science pipeline, i.e., the end-to-end process of going from unstructured, messy data to knowledge and actionable insights. Provides a broad overview of several topics including statistical data analysis, basic data mining and machine learning algorithms, large-scale data management, cloud computing, and information visualization.
CMSC330
(Perm Req)
Organization of Programming Languages
Credits: 3
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC250 and CMSC216.
Restriction: Must be in a major within the CMNS-Computer Science department; or must be in the Computer Science Minor program; or must be in Engineering: Computer program; and Permission of CMSC - Computer Science department.
A study of programming languages, including their syntax, semantics, and implementation. Several different models of languages are discussed, including dynamic, scripting (e.g., Ruby, Python) functional (e.g., OCaml, Haskell, Scheme), and memory safe systems programming (e.g., Rust). Explores language features such as formal syntax, scoping and binding of variables, higher-order programming, typing, and type polymorphism. Introduces finite automata, context free grammar, parsing, lambda calculus, and basics of security attacks and software security.
CMSC335
(Perm Req)
Web Application Development with JavaScript
Credits: 3
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC216 and CMSC250.
Restriction: Permission of CMNS-Computer Science Department.
Credit only granted for: CMSC389N or CMSC335.
Formerly: CMSC389N.
Provides an introduction to modern ways of developing Web Applications/Services using JavaScript for both front-end and back-end. The course covers topics on fundamental JavaScript language constructs, server-side JavaScript, back-end data persistence, and client-side JavaScript to build Web Applications that interact with Web services and back-end databases.
CMSC351
(Perm Req)
Credits: 3
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC250 and CMSC216.
Restriction: Must be in a major within the CMNS-Computer Science department; or must be in Engineering: Computer program; or must be in the Computer Science Minor program; and Permission from the CMSC - Computer Science department.
Credit only granted for: CMSC251 or CMSC351.
A systematic study of the complexity of some elementary algorithms related to sorting, graphs and trees, and combinatorics. Algorithms are analyzed using mathematical techniques to solve recurrences and summations.
CMSC388J
(Perm Req)
Special Topics in Computer Science; Building Secure Web Applications with Python and Flask
Credits: 1
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC216 and CMSC250; and permission of CMNS-Computer Science department.

Flask is a widely used web framework written in Python. Students will first get an introduction to Python and Flask and transition to web application security, where they'll learn about different types of security vulnerabilities and best practices to patch up these vulnerabilities in their own apps. We'll also cover building and authenticating an API, andhow to deploy an app!

A student-led course through Student-Initiated Courses (STICs) @ UMD: http://stics.umd.edu/ Click here to learn more about STICs.
CMSC388Y
(Perm Req)
Special Topics in Computer Science; History of Computer Science and Digital Technologies
Credits: 1
Grad Meth: Reg
An investigation of the history and evolution of computer science from its early foundations through the atomic age, the Y2K Bug, the internet revolution, the present day, and beyond. This course will cover not only the people and work behind the advances in computing, but also the technologies of yesteryear that eventually evolved into the devices that have become ubiquitous today. We will observe how computing has impacted society throughout time, and the reactions to its advances through the normalization of digital technologies.

A student-led course through Student-Initiated Courses (STICs) @ UMD: http://stics.umd.edu/ Click here to learn more about STICs.
CMSC389G
(Perm Req)
Special Topics in Computer Science; What to do After Landing a SWE Job
Credits: 1
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC250 and CMSC216; and permission of CMNS-Computer Science department.

Students are given a scoped experience of a Software Engineering industry job and relevant tools/practices to accelerate acclimation to a future SWE Intern or Full-Time role. Topics/Skills covered include: Git, Code Reviews, AWS basics, Design Docs, unit testing, virtual machines, etc. Students will contribute to a complex code base to simulate designing, implementing, and testing new features in a professional setting.

A student-led course through Student-Initiated Courses (STICs) @ UMD: http://stics.umd.edu/ Click here to learn more about STICs.
CMSC389O
(Perm Req)
Special Topics in Computer Science; The Coding Interview
Credits: 1
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC216 and CMSC250; and permission of CMNS-Computer Science department.

Technical interviewing is a critical skill for acquiring internships and jobs. Students will gain a comprehensive, practical introduction to technical interviews. Students will be introduced to basic topics such as Big O and String Manipulation and later move into more complex topics such as Graphs and Dynamic Programming. Most in-class time will be spent on mock interviews to give real interview practice. The course facilitators are experienced in interviewing and have received internship/job offers from companies like Meta, Optiver, Bloomberg, Amazon, Apple, Microsoft, Databricks, Capital One, and more.

A student-led course through Student-Initiated Courses (STICs) @ UMD: http://stics.umd.edu/ Click here to learn more about STICs.
CMSC389P
(Perm Req)
Special Topics in Computer Science; Mastering the PM Interview
Credits: 1
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC216 and CMSC250; and permission of CMNS-Computer Science department.

Product Management is an interesting intersection of technology and business that students are given the opportunity to learn more about in this class. Students are introduced to the tools, techniques, and resources to nail their PM (Product Management) interviews. We'll be providing hands-on practice with PM specific topics including product design, analytical, and case questions. By the end of the class, you should be acing all your PM interviews!

A student-led course through Student-Initiated Courses (STICs) @ UMD: http://stics.umd.edu/ Click here to learn more about STICs.
CMSC389T
(Perm Req)
Special Topics in Computer Science; Introduction to Git, Github and Project Management
Credits: 1
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC216 and CMSC250; and permission of CMNS-Computer Science department.

Version control and collaboration are essential skills for developers to learn. Students will learn how to use Git for basic and advanced workflows, GitHub for team and project management, and explore tools to help them excel in a DevOps environment.

A student-led course through Student-Initiated Courses (STICs) @ UMD: http://stics.umd.edu/ Click here to learn more about STICs.
CMSC398D
(Perm Req)
Special Topics in Computer Science; Introduction to Artificial Intelligence in Healthcare
Credits: 1
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC216 and CMSC250; and permission of CMNS-Computer Science department.

A student-led course through Student-Initiated Courses (STICs) @ UMD: http://stics.umd.edu/ Click here to learn more about STICs.
CMSC398E
(Perm Req)
Special Topics in Computer Science; Essential Data Science Skills & Techniques
Credits: 1
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC216 and CMSC250; and permission of CMNS-Computer Science department.

Students will learn the tools and techniques needed to succeed in the field of data science. They will engage in simulations that allow them to develop SQL/R coding skills, and learn how to effectively present these findings. They will also utilize analytical thinking to solve real-world data science problems.

A student-led course through Student-Initiated Courses (STICs) @ UMD: http://stics.umd.edu/ Click here to learn more about STICs.
CMSC398F
(Perm Req)
Special Topics in Computer Science; Introduction to Blockchain and Cryptocurrency
Credits: 1
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC216 and CMSC250; and permission of CMNS-Computer Science department.

A student-led course through Student-Initiated Courses (STICs) @ UMD: http://stics.umd.edu/ Click here to learn more about STICs.
CMSC398I
(Perm Req)
Special Topics in Computer Science; Introduction to Shell Scripting
Credits: 1
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC216 and CMSC250; and permission of CMNS-Computer Science department.

Students will be introduced to shell scripting, the glue between various utilities and the method of choice of many programmers to interact with their systems. The differences between shell languages and their more mainstream counterparts will be explored. Topics include composing programs, concurrency, error handling, customizing one's shell, security vulnerabilities. Projects will be based on reimplementing common utilities.

A student-led course through Student-Initiated Courses (STICs) @ UMD: http://stics.umd.edu/ Click here to learn more about STICs.
CMSC398K
(Perm Req)
Special Topics in Computer Science; Basic Shaders in Three.js
Credits: 1
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC216 and CMSC250; and permission of CMNS-Computer Science department.

Students will learn about shaders and how they contribute to the underlying processes that make visualizing 3D games and simulations possible. This course will cover basic concepts of linear algebra and goover creating scenes and shaders using the popular JavaScript library, Three.js. We will then cover basic lighting systems as well as the normal, flat, goraud, phong, blinn-phong, cel, and contour shading techniques and explore the various visual effects they achieve.

A student-led course through Student-Initiated Courses (STICs) @ UMD: http://stics.umd.edu/ Click here to learn more about STICs.
CMSC401
Algorithms for Geospatial Computing
Credits: 3
Grad Meth: Reg
Prerequisite: GEOG276; or a minimum grade of C- in CMSC330 and CMSC351; or permission of instructor.
Cross-listed with: GEOG470.
Jointly offered with: GEOG770.
Credit only granted for: CMSC498Q, CMSC401, CMSC788I, GEOG470, GEOG498I, GEOG770, or GEOG788I.
Formerly: GEOG498I.
An introduction to fundamental geospatial objects and geometric algorithms for spatio-temporal data processing and analysis. Point data representation and analysis: spatial data models and data structures, algorithms for spatial queries, point clustering algorithms. Surface and scalar field modeling, such as terrains: raster and triangle-based models (TINs), algorithms for building and querying TINs. Algorithms for natural and urban terrain analysis: morphology computation and visibility analysis. Applications to processing and analysis of LiDAR (Light Detection And Ranging) data in the context of terrain reconstruction, urban modeling, forest management and bathymetry reconstruction for coastal data management. Road network computation and analysis: algorithms for route computation in road networks, and for road network reconstruction from GPS and satellite data.
CMSC411
(Perm Req)
Computer Systems Architecture
Credits: 3
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC330; or must be in the (Computer Science (Doctoral), Computer Science (Master's)) program.
Restriction: Permission of CMNS-Computer Science department.
Credit only granted for: ENEE446 or CMSC411.
Input/output processors and techniques. Intra-system communication, buses, caches. Addressing and memory hierarchies. Microprogramming, parallelism, and pipelining.
CMSC412
(Perm Req)
Credits: 4
Grad Meth: Reg
CORE: CS
Prerequisite: Minimum grade of C- in CMSC330 and CMSC351; and 1 course with a minimum grade of C- from (CMSC414, CMSC417, CMSC420, CMSC430, CMSC433, CMSC435, ENEE440, ENEE457).
Restriction: Permission of CMNS-Computer Science department; or must be in one of the following programs (Computer Science (Master's); Computer Science (Doctoral)).
Credit only granted for: CMSC412 or ENEE447.
A hands-on introduction to operating systems, including topics in: multiprogramming, communication and synchronization, memory management, IO subsystems, and resource scheduling polices. The laboratory component consists of constructing a small kernel, including functions for device IO, multi-tasking, and memory management.
CMSC414
(Perm Req)
Computer and Network Security
Credits: 3
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC330 and CMSC351; or must be in the (Computer Science (Doctoral), Computer Science (Master's)) program.
Restriction: Permission of CMNS-Computer Science department.
Credit only granted for: CMSC414, ENEE459C, or ENEE457.
An introduction to the topic of security in the context of computer systems and networks. Identify, analyze, and solve network-related security problems in computer systems. Fundamentals of number theory, authentication, and encryption technologies, as well as the practical problems that have to be solved in order to make those technologies workable in a networked environment, particularly in the wide-area Internet environment.
CMSC416
(Perm Req)
Introduction to Parallel Computing
Credits: 3
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC330 and CMSC351; or permission of instructor.
Restriction: Permission of CMNS-Computer Science department.
Credit only granted for: CMSC416 or CMSC498X.
Formerly: CMSC498X.
Introduction to parallel computing. Topics include programming for shared memory and distributed memory parallel architectures, and fundamental issues in design, development, and performance analysis of parallel programs.
CMSC417
(Perm Req)
Credits: 3
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC351 and CMSC330; and permission of CMNS-Computer Science department. Or must be in the (Computer Science (Doctoral), Computer Science (Master's)) program.
Computer networks and architectures. The OSI model including discussion and examples of various network layers. A general introduction to existing network protocols. Communication protocol specification, analysis, and testing.
CMSC420
(Perm Req)
Advanced Data Structures
Credits: 3
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC351 and CMSC330; and permission of CMNS-Computer Science department. Or must be in the (Computer Science (Doctoral), Computer Science (Master's)) program.
Description, properties, and storage allocation functions of data structures including balanced binary trees, B-Trees, hash tables, skiplists, tries, KD-Trees and Quadtrees. Algorithms for manipulating structures. Applications from areas such as String Processing, Computer Graphics, Information Retrieval, Computer Networks, Computer Vision, and Operating Systems.
CMSC421
(Perm Req)
Introduction to Artificial Intelligence
Credits: 3
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC351 and CMSC330; and permission of CMNS-Computer Science department. Or must be in the (Computer Science (Doctoral), Computer Science (Master's)) program.
Introduces a range of ideas and methods in AI, varying semester to semester but chosen largely from: automated heuristic search, planning, games, knowledge representation, logical and statistical inference, learning, natural language processing, vision, robotics, cognitive modeling, and intelligent agents. Programming projects will help students obtain a hands-on feel for various topics.
CMSC422
(Perm Req)
Introduction to Machine Learning
Credits: 3
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC320, CMSC330, and CMSC351; and 1 course with a minimum grade of C- from (MATH240, MATH341, MATH461); and permission of CMNS-Computer Science department.
Machine Learning studies representations and algorithms that allow machines to improve their performance on a task from experience. This is a broad overview of existing methods for machine learning and an introduction to adaptive systems in general. Emphasis is given to practical aspects of machine learning and data mining.
Credit only granted for CMSC422 or CMSC498M.
CMSC423
(Perm Req)
Bioinformatic Algorithms, Databases, and Tools
Credits: 3
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC351 and CMSC330; and permission of CMNS-Computer Science department. Or must be in the (Computer Science (Doctoral), Computer Science (Master's)) program.
An introduction to the main algorithms, databases, and tools used in bioinformatics. Topics may include assembly and analysis of genome sequences, reconstructing evolutionary histories, predicting protein structure, and clustering of biological data. Use of scripting languages to perform analysis tasks on biological data. No prior knowledge of biology is assumed.
CMSC424
(Perm Req)
Credits: 3
Grad Meth: Reg
CORE: CS
Prerequisite: Minimum grade of C- in CMSC351 and CMSC330; and permission of CMNS-Computer Science department. Or must be in the (Computer Science (Doctoral), Computer Science (Master's)) program.
Students are introduced to database systems and motivates the database approach as a mechanism for modeling the real world. An in-depth coverage of the relational model, logical database design, query languages, and other database concepts including query optimization, concurrency control; transaction management, and log based crash recovery. Distributed and Web database architectures are also discussed.
CMSC425
(Perm Req)
Credits: 3
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC330 and CMSC351.
Restriction: Permission of CMNS-Computer Science department.
An introduction to the principles and practice of computer game programming and design. This includes an introduction to game hardware and systems, the principles of game design, object and terrain modeling, game physics, artificial intelligence for games, networking for games, rendering and animation, and aural rendering. Course topics are reinforced through the design and implementation of a working computer game.
CMSC426
(Perm Req)
Credits: 3
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC330 and CMSC351 and 1 course with a minimum grade of C- from (MATH240, MATH341, MATH461); or must be in the (Computer Science (Doctoral), Computer Science (Master's)) program; or permission of the instructor.
Restriction: Permission of CMNS-Computer Science department.
An introduction to basic concepts and techniques in computervision. This includes low-level operations such as image filtering and edge detection, 3D reconstruction of scenes using stereo and structure from motion, and object detection, recognition and classification.
CMSC430
(Perm Req)
Introduction to Compilers
Credits: 3
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC330 and CMSC351; and permission of CMNS-Computer Science department. Or must be in the (Computer Science (Doctoral), Computer Science (Master's)) program.
Topics include lexical analysis, parsing, intermediate representations, program analysis, optimization, and code generation.
CMSC433
(Perm Req)
Programming Language Technologies and Paradigms
Credits: 3
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC330; or must be in the (Computer Science (Doctoral), Computer Science (Master's)) program.
Restriction: Permission of CMNS-Computer Science department.
Programming language technologies (e.g., object-oriented programming), their implementations and use in software design and implementation.
CMSC434
(Perm Req)
Introduction to Human-Computer Interaction
Credits: 3
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC330 and CMSC351; and permission of CMNS-Computer Science department. Or must be in the (Computer Science (Doctoral), Computer Science (Master's)) program.
Assess usability by quantitative and qualitative methods. Conduct task analyses, usability tests, expert reviews, and continuing assessments of working products by interviews, surveys, and logging. Apply design processes and guidelines to develop professional quality user interfaces. Build low-fidelity paper mockups, and a high-fidelity prototype using contemporary tools such as graphic editors and a graphical programming environment (eg: Visual Basic, Java).
CMSC435
(Perm Req)
Software Engineering
Credits: 3
Grad Meth: Reg
CORE: CS
Prerequisite: 1 course with a minimum grade of C- from (CMSC412, CMSC417, CMSC420, CMSC430, CMSC433, ENEE447); and permission of CMNS-Computer Science department.
State-of-the-art techniques in software design and development. Laboratory experience in applying the techniques covered. Structured design, structured programming, top-down design and development, segmentation and modularization techniques, iterative enhancement, design and code inspection techniques, correctness, and chief-programmer teams. The development of a large software project.
CMSC436
(Perm Req)
Programming Handheld Systems
Credits: 3
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC330 and CMSC351; or must be in the (Computer Science (Doctoral), Computer Science (Master's)) program.
Restriction: Permission of CMNS-Computer Science department.
Fundamental principles and concepts that underlie the programming of handheld systems, such as mobile phones, personal digital assistants, and tablet computers. Particular emphasis will be placed on concepts such as limited display size, power, memory and CPU speed; and new input modalities, where handheld systems differ substantially from non-handheld systems, and thus require special programming tools and approaches. Students will apply these concepts and principles in the context of an existing handset programming platform.
CMSC451
(Perm Req)
Design and Analysis of Computer Algorithms
Credits: 3
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC351; and permission of CMNS-Computer Science department. Or must be in the (Computer Science (Doctoral), Computer Science (Master's)) program.
Fundamental techniques for designing efficient computer algorithms, proving their correctness, and analyzing their complexity. General topics include graph algorithms, basic algorithm design paradigms (such as greedy algorithms, divide-and-conquer, and dynamic programming), network flows, NP-completeness, and other selected topics in algorithms.
CMSC456
(Perm Req)
Credits: 3
Grad Meth: Reg
Prerequisite: (CMSC106, CMSC131, or ENEE150; or equivalent programming experience); and (2 courses from (CMSC330, CMSC351, ENEE324, or ENEE380); or any one of these courses and a 400-level MATH course, or two 400-level MATH courses); and Permission of CMNS-Mathematics department or permission of instructor .
Cross-listed with: MATH456, ENEE456.
Credit only granted for: MATH456, CMSC456 or ENEE456.
The theory, application, and implementation of mathematical techniques used to secure modern communications. Topics include symmetric and public-key encryption, message integrity, hash functions, block-cipher design and analysis, number theory, and digital signatures.
CMSC457
(Perm Req)
Introduction to Quantum Computing
Credits: 3
Grad Meth: Reg
Prerequisite: 1 course with a minimum grade of C- from (MATH240, MATH341, MATH461, PHYS274); and 1 course with a minimum grade of C- from (CMSC351, PHYS373).
Restriction: Permission of CMNS-Computer Science department.
An introduction to the concept of a quantum computer, including algorithms that outperform classical computation and methods for performing quantum computation reliably in the presence of noise. As this is a multidisciplinary subject, the course will cover basic concepts in theoretical computer science and physics in addition to introducing core quantum computing topics.
Cross-listed with PHYS457. Credit only granted for CMSC457 or PHYS457.
CMSC460
(Perm Req)
Computational Methods
Credits: 3
Grad Meth: Reg
Prerequisite: 1 course with a minimum grade of C- from (MATH240, MATH341, MATH461); and 1 course with a minimum grade of C- from (MATH241, MATH340); and 1 course with a minimum grade of C- from (CMSC106, CMSC131); and minimum grade of C- in MATH246.
Cross-listed with: AMSC460.
Credit only granted for: AMSC460, AMSC466, CMSC460, or CMSC466.
Basic computational methods for interpolation, least squares, approximation, numerical quadrature, numerical solution of polynomial and transcendental equations, systems of linear equations and initial value problems for ordinary differential equations. Emphasis on methods and their computational properties rather than their analytic aspects. Intended primarily for students in the physical and engineering sciences.
CMSC466
(Perm Req)
Introduction to Numerical Analysis I
Credits: 3
Grad Meth: Reg
Prerequisite: 1 course with a minimum grade of C- from (MATH240, MATH341, MATH461); and 1 course with a minimum grade of C- from (MATH241, MATH340); and 1 course with a minimum grade of C- from (CMSC106, CMSC131); and minimum grade of C- in MATH410.
Cross-listed with: AMSC466.
Credit only granted for: AMSC460, CMSC460, AMSC466, or CMSC466.
Floating point computations, direct methods for linear systems, interpolation, solution of nonlinear equations.
CMSC470
(Perm Req)
Introduction to Natural Language Processing
Credits: 3
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC320, CMSC330, and CMSC351; and 1 course with a minimum grade of C- from (MATH240, MATH341, MATH461).
Restriction: Permission of CMNS-Computer Science department.
Introduction to fundamental techniques for automatically processing and generating natural language with computers. Machine learning techniques, models, and algorithms that enable computers to deal with the ambiguity and implicit structure of natural language. Application of these techniques in a series of assignments designed to address a core application such as question answering or machine translation.
CMSC471
(Perm Req)
Introduction to Data Visualization
Credits: 3
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC330 and CMSC351; and permission of CMNS-Computer Science Department.
Restriction: Permission of the CMNS-Computer Science Department.
Credit only granted for: CMSC471 or CMSC498O.
Formerly: CMSC498O.
Datasets are becoming increasingly large and complex, requiring intuitive ways to explore and interpret them quickly and efficiently. In this case, a picture is worth a thousand words: visualizations enable us to transform data into images that are easier to understand and reason about, compared to raw numbers and raw text. Visualizations are critical tools in externalizing and organizing our knowledge and insights, whether to explore collected datasets to improve our understanding of the physical world, to assess and debug analysis/experimental workflows, or to present new and interesting results to diverse audiences. In this course we will study techniques and algorithms for creating effective visualizations based on principles from graphic design, perceptual psychology, and cognitive science. Students will learn how to design and build interactive visualizations for the web, using the D3.js (Data-Driven Documents) framework.
CMSC472
(Perm Req)
Introduction to Deep Learning
Credits: 3
Grad Meth: Reg
Prerequisite: Minimum grade of C- or higher in CMSC330 and CMSC351; and 1 course with a minimum grade of C- or higher from (MATH240, MATH461).
Restriction: Permission of the CMNS-Computer Science department. Or must be in the (Computer Science (Doctoral), Computer Science (Master's) program.
Credit only granted for: CMSC498L or CMSC472.
Formerly: CMSC498L.
An introduction to deep learning, a machine learning technique, as well as its applications to a variety of domains. Provides a broad overview of deep learning concepts including neural networks, convolutional neural networks, recurrent neural networks, generative models, and deep reinforcement learning, and an intuitive introduction to basics of machine learning such as simple models, learning paradigms, optimization, overfitting, importance of data, and training caveats.
CMSC475
(Perm Req)
Combinatorics and Graph Theory
Credits: 3
Grad Meth: Reg
Prerequisite: 1 course with a minimum grade of C- from (MATH240, MATH341, MATH461); and 1 course with a minimum grade of C- from (MATH241, MATH340). And permission of CMNS-Computer Science department; or permission of CMNS-Mathematics department.
Cross-listed with MATH475 .
General enumeration methods, difference equations, generating functions. Elements of graph theory, matrix representations of graphs, applications of graph theory to transport networks, matching theory and graphical algorithms.
CMSC477
(Perm Req)
Robotics Perception and Planning
Credits: 3
Grad Meth: Reg
Prerequisite: 1 course from (MATH240, MATH341, MATH461); and (ENEE467 or CMSC420).
Restriction: Must be in the Robotics and Autonomous Systems minor; and permission of Computer Science department.
A hands-on introduction to perception and planning for robotics, including rigid body transformations and rotations, dynamics and control of mobile robots/drones, graph based and sampling based planning algorithms, Bayseian and Kalman filtering, camera models and calibration, projective geometry, visual features, optical flow, pose estimation, RANSAC and Hough transform, structure from motion, visual odometry, machine learning basics, visual recognition and learning.
CMSC498A
(Perm Req)
Selected Topics in Computer Science
Credits: 1 - 3
Grad Meth: Reg
Contact department for information to register for this course.
CMSC498F
(Perm Req)
Selected Topics in Computer Science; Advances in XR
Credits: 3
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC330, CMSC351, and CMSC425 or CMSC427.

AR, VR, and MR, collectively referred to as XR, are becoming ubiquitous for human-computer interaction with limitless applications and potential use.

This course examines advances on real-time multi-modal XR systems in which the user is 'immersed' in and interacts with a simulated 3D environment. The topics will include display, modeling, 3D graphics, haptics, audio, locomotion, animation, applications, immersion and presence.
CMSC499A
(Perm Req)
Independent Undergraduate Research
Credits: 1 - 3
Grad Meth: Reg
Contact department for information to register for this course.
CMSC661
(Perm Req)
Scientific Computing II
Credits: 3
Grad Meth: Reg
Prerequisite: Must have knowledge of C or Fortran. And CMSC466, AMSC466, AMSC460, or CMSC460; or (must have knowledge of basic numerical analysis (linear equations, nonlinear equations, integration, interpolation); and permission of instructor).
Cross-listed with: AMSC661.
Credit only granted for: AMSC661 or CMSC661.
Fourier and wavelet transform methods, numerical methods for elliptic partial differential equations, numerical linear algebra for sparse matrices, Finite element methods, numerical methods for time dependent partial differential equations. Techniques for scientific computation with an introduction to the theory and software for each topic. Course is part of a two course sequence (660 and 661), but can be taken independently.
CMSC664
(Perm Req)
Advanced Scientific Computing II
Credits: 3
Grad Meth: Reg
Prerequisite: AMSC663 or CMSC663.
Restriction: Permission of instructor.
Cross-listed with: AMSC664.
Credit only granted for: AMSC664 or CMSC664.
In the sequence Advanced Scientific Computing I & Advanced Scientific Computing II, (AMSC663/CMSC663 and CMSC664/CMSC664, respectively) students work on a year-long individual project to develop software for a scientific task in a high performance computing environment. Lectures will be given on available computational environments, code development, implementation of parallel algorithms.
CMSC701
Computational Genomics
Credits: 3
Grad Meth: Reg, Aud, S-F
An introduction to the algorithms and heuristics used in the analysis of biological sequences. Includes an introduction to string matching and alignment algorithms, phylogenetic analysis, string reconstruction (genome assembly), and sequence pattern recognition (gene and motif finding). A particular emphasis will be placed on the design of efficient algorithms and on techniques for analyzing the time and space complexity of these algorithms. Computational concepts will be presented in the context of current biological applications. No prior knowledge of biology necessary.
CMSC711
Credits: 3
Grad Meth: Reg, Aud
Prerequisite: CMSC412; or students who have taken courses with comparable content may contact the department.
Priciples, design, and performance evaluation of computer networks. Network architectures including the ISO model and local area networks (LANs). Communication protocols and network topology.
CMSC722
Artificial Intelligence Planning
Credits: 3
Grad Meth: Reg, Aud
Prerequisite: CMSC421; or students who have taken courses with comparable content may contact the department; or permission of CMNS-Computer Science department.
Automated planning of actions to accomplish some desired goals. Basic algorithms, important systems, and new directions in the field of artificial intelligence planning systems.
CMSC742
Algorithms in Machine Learning: Guarantees and Analyses
Credits: 3
Grad Meth: Reg, Aud
Prerequisite: CMSC422 or equivalent; or permission of instructor.
Credit only granted for: CMSC828U or CMSC732.
Formerly: CMSC828U.
Machine learning studies automatic methods for learning to make accurate predictions, to understand patterns in observed features and to make useful decisions based on past observations. This course introduces theoretical machine learning, including mathematical models of machine learning, and the design and rigorous analysis of learning algorithms. Topics include: (1) Learning theory (traditional and modern), including PAC learning basics, Boosting theory and PAC learning in neural nets. (2) Latent variable graphical models, including spectral methods for learning latent variable models. (3) Reinforcement learning theory, including algorithms, sample complexity and analyses.
CMSC764
Advanced Numerical Optimization
Credits: 3
Grad Meth: Reg, Aud
Prerequisite: MATH410; or permission of instructor.
Cross-listed with: AMSC607.
Credit only granted for: AMSC607 or CMSC764.
Formerly: CMSC878O.
Modern numerical methods for solving unconstrained and constrained nonlinear optimization problems in finite dimensions. Design of computational algorithms and the analysis of their properties.
CMSC798
(Perm Req)
Master's Non-Thesis Research
Credits: 1 - 3
Grad Meth: Reg
Contact department for information to register for this course.
CMSC799
(Perm Req)
Master's Thesis Research
Credits: 1 - 6
Grad Meth: S-F
Contact department for information to register for this course.
CMSC800
How to Conduct Great Research
Credits: 1
Grad Meth: S-F, Aud
Restriction: Must be in the Computer Science doctoral program.
Credit only granted for: CMSC798F or CMSC800.
Formerly: CMSC798F.
Develop research skills so as to promote high quality and high impact.
CMSC818J
Advanced Topics in Computer Systems; Domain Specific Architectures
Credits: 3
Grad Meth: Reg, Aud
Explores recent advances in both academia and industry in designing DSAs. Overviews the characteristics of applications that enable them to greatly benefit from DSAs and the source of speedup in DSAs that mainly includes parallelism, memory access optimization, and data specialization. Students will get familiar with the common techniques such as using systolic arrays and near-data processing in state-of-the-art DSAs to enable efficient computation.
CMSC818L
Advanced Topics in Computer Systems; Fantastic Zero-Knowledge Proofs and How to Use Them
Credits: 3
Grad Meth: Reg, Aud
A non-interactive zero-knowledge proof allows Alice to convince anyone that some statement is true without revealing why. For example, Alice can show that f(x,y) = z without revealing anything about x or y. Zero-knowledge proofs have undergone incredible advances in the past tenyears with billions of dollars invested in industrial development, primarily in blockchains. This class will cover recent advances in zero-knowledge proofs with a focus on using them in applications beyond just blockchains.
CMSC828A
Advanced Topics in Information Processing; Fantastic Machine Learning Paradigms and Where to use Them
Credits: 3
Grad Meth: Reg, Aud
There exist so many machine learning paradigms, like isolated villages hidden in a jungle. But how do they differ from each other? How can we relate them? What are their fundamental assumptions, formulations, and motivations? Where to use them? How to formulate your problem into one of them, or, when and how to create your own learning paradigms? In this course, we will take an in-depth tour in the jungle of machine learning paradigms.
CMSC828O
Advanced Topics in Information Processing; Computational and Mathematical Analysis for Networks Across Scales
Credits: 3
Grad Meth: Reg, Aud, S-F
CMSC828T
Advanced Topics in Information Processing; Sorting in Space and Words and Foundations of Multidimensional and Metric Data Structures
Credits: 3
Grad Meth: Reg, Aud
CMSC838C
Advanced Topics in Programming Languages; Advances in XR
Credits: 3
Grad Meth: Reg, Aud
Cross-listed with ENEE759N. Credit only granted for CMSC838C or ENEE759N.

AR, VR, and MR, collectively referred to as XR, are becoming ubiquitous for human-computer interaction with limitless applications and potential use. This course examines advances on real-time multi-modal XR systems in which the user is 'immersed' in and interacts with a simulated 3D environment. The topics will include display, modeling, 3D graphics, haptics, audio, locomotion, animation, applications, immersion and presence.
CMSC838E
Advanced Topics in Programming Languages; Compiler Construction
Credits: 3
Grad Meth: Reg, Aud
CMSC848D
Selected Topics in Information Processing; Explainable Natural Language Processing
Credits: 3
Grad Meth: Reg, Aud
CMSC848E
Selected Topics in Information Processing; Machine Learning for Data Management Systems
Credits: 3
Grad Meth: Reg, Aud
CMSC858C
Advanced Topics in Theory of Computing; Randomized Algorithms
Credits: 3
Grad Meth: Reg, Aud
CMSC858L
Advanced Topics in Theory of Computing; Quantum Complexity
Credits: 3
Grad Meth: Reg, Aud
CMSC858N
Advanced Topics in Theory of Computing; Scalable Parallel Algorithms and Data Structures
Credits: 3
Grad Meth: Reg, Aud
CMSC858Z
Advanced Topics in Theory of Computing; Modern Discrete Probability
Credits: 3
Grad Meth: Reg, Aud, S-F
Cross-listed with ENEE729P and MATH729P. Credit only granted for ENEE729P, MATH729P, or CMSC858Z.
CMSC898
Pre-Candidacy Research
Credits: 1 - 8
Grad Meth: Reg
Contact department for information to register for this course.
CMSC899
(Perm Req)
Doctoral Dissertation Research
Credits: 6
Grad Meth: S-F
Contact department for information to register for this course.