Courses - Spring 2022
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
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
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.
Credit only granted for: IMDM127 or CMSC125.
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 or CMSC133.
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
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
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
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
Special Topics in Computer Science
Credits:
1 - 4
Grad Meth:
S-F
CMSC320
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: CMSC320, DATA320 or STAT426.
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
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
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
Algorithms
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.
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
Special Topics in Computer Science; Building Secure Web Applications with Python and Flask
Credits:
1
Grad Meth:
Reg
Prerequisites: Minimum grade of C- in CMSC250 and CMSC216; and permission of CMNS-Computer Science department.
Students are introduced to building secure, full-stack web applications with Python and Flask. Different types of security vulnerabilities and best practices to patch in students own applications will be examined.
Students are introduced to building secure, full-stack web applications with Python and Flask. Different types of security vulnerabilities and best practices to patch in students own applications will be examined.
A student-led course through Student-Initiated Courses (STICs) @ UMD: http://stics.umd.edu/ Please click here for more information.
CMSC388U
Special Topics in Computer Science; Introduction to Ethical Hacking (Hack the Class)
Credits:
1
Grad Meth:
Reg
Prerequisites: Minimum grade of C- in CMSC250 and CMSC216; and permission of CMNS-Computer Science department.
A student-led course through Student-Initiated Courses (STICs) @ UMD: http://stics.umd.edu/ Please click here for more information.
CMSC388X
Special Topics in Computer Science; Introduction to Programming Language Theory
Credits:
2
Grad Meth:
Reg
Prerequisite: Minimum grade of C- in CMSC250 and CMSC216; and permission of CMNS-Computer Science department. CMSC330 is also strongly recommended as a prerequisite or co-requisite.
A student-led course through Student-Initiated Courses (STICs) @ UMD: http://stics.umd.edu/ Please click here for more information.
CMSC389E
Special Topics in Computer Science; Digital Logic Design through Minecraft
Credits:
1
Grad Meth:
Reg
Prerequisites: Minimum grade of C- in CMSC250 and CMSC216; and permission of CMNS-Computer Science department.
Explores the fundamentals of digital logic design using Minecraft's Redstone. Using the low-level and intuitive visualization of circuitry Redstone provides, you will create a series of projects that apply principles of digital logic design learned in class.
Explores the fundamentals of digital logic design using Minecraft's Redstone. Using the low-level and intuitive visualization of circuitry Redstone provides, you will create a series of projects that apply principles of digital logic design learned in class.
A student-led course through Student-Initiated Courses (STICs) @ UMD: http://stics.umd.edu/ Please click here for more information.
CMSC389F
Special Topics in Computer Science; Reinforcement Learning
Credits:
1
Grad Meth:
Reg
Prerequisite: Minimum grade of C- in CMSC250 and CMSC216; and permission of CMNS-Computer Science department.
A student-led course through Student-Initiated Courses (STICs) @ UMD: http://stics.umd.edu/ Please click here for more information.
CMSC389G
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.
A student-led course through Student-Initiated Courses (STICs) @ UMD: http://stics.umd.edu/ Please click here for more information.
CMSC389O
Special Topics in Computer Science; The Coding Interview
Credits:
1
Grad Meth:
Reg
Prerequisites: Minimum grade of C- in CMSC250 and CMSC216; and permission of CMNS-Computer Science department.
A student-led course through Student-Initiated Courses (STICs) @ UMD: http://stics.umd.edu/ Please click here for more information.
CMSC389P
Special Topics in Computer Science; Mastering the PM Interview
Credits:
1
Grad Meth:
Reg
Prerequisites: Minimum grade of C- in CMSC250 and CMSC216; and permission of CMNS-Computer Science department.
A student-led course through Student-Initiated Courses (STICs) @ UMD: http://stics.umd.edu/ Please click here for more information.
CMSC389T
Special Topics in Computer Science; Introduction to Git, Github and Project Management
Credits:
1
Grad Meth:
Reg
Prerequisite: Minimum grade of C- in CMSC250 and CMSC216; and permission of CMNS-Computer Science department.
A student-led course through Student-Initiated Courses (STICs) @ UMD: http://stics.umd.edu/ Please click here for more information.
CMSC395
Teaching Techniques for Computer Science
Credits:
1
Grad Meth:
Reg, P-F
Restriction: Students must be hired as a teaching assistant in the Computer Science Department for the semester they are registered for the course; and permission of the Computer Science Department.
This course will assure that teaching assistants become better skilled at applying effective teaching practices that improve the classroom environment while learning methods to implement mechanisms to improve diversity and inclusion. Legal and ethical aspects of the role will also be considered. Students in the class will be currently working as a teaching assistant and, therefore, be able to apply what they are learning immediately in their own context.
CMSC411
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
Operating Systems
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
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.
CMSC417
Computer Networks
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
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
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
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
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
Database Design
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
Game Programming
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
Computer Vision
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
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
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
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
Software Engineering
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
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
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.
CMSC452
Elementary Theory of Computation
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.
Techniques are developed to determine the difficulty of a problem relative to a model of computation. Topics include Finite Automata, P, NP, decidability, undecidability, and communication complexity.
CMSC454
Algorithms for Data Science
Credits:
3
Grad Meth:
Reg
Prerequisite: Minimum grade of C- in CMSC330 and CMSC351.
Restriction: Permission of CMSC-Computer Science department.
Fundamental methods for processing a high volume of data. Methods include stream processing, locally sensitive hashing, web search methods, page rank computation, network and link analysis, dynamic graph algorithms as well as methods to handle high dimensional data/dimensionality reduction.
CMSC456
Cryptography
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
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
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
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
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
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.
CMSC475
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.
CMSC488B
Special Topics in Computer Science; Advanced Functional Programming
Credits:
3
Grad Meth:
Reg
Prerequisite: Minimum grade of C- in CMSC330 and CMSC351.
Advanced functional programming using Haskell. Students will be introduced to a range of modern software engineering practices, in particular those embodied in typed, functional programming languages. Basic knowledge of functional programming in the form of OCaml (from 330) is assumed, but not prior knowledge of Haskell. Basic topics will include typeclasses, monads, and property-based testing; advanced topics may include high-level type system features such as GADTs, verification with Liquid Haskell, and practical application development, with invited talks from industry and academia experts.
Advanced functional programming using Haskell. Students will be introduced to a range of modern software engineering practices, in particular those embodied in typed, functional programming languages. Basic knowledge of functional programming in the form of OCaml (from 330) is assumed, but not prior knowledge of Haskell. Basic topics will include typeclasses, monads, and property-based testing; advanced topics may include high-level type system features such as GADTs, verification with Liquid Haskell, and practical application development, with invited talks from industry and academia experts.
CMSC498A
Selected Topics in Computer Science
Credits:
1 - 3
Grad Meth:
Reg
CMSC498F
Selected Topics in Computer Science; Advances in XR
Credits:
3
Grad Meth:
Reg
Prerequisite: Minimum grade of C- in CMSC330 and CMSC351.
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.
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.
CMSC498Q
Selected Topics in Computer Science; Algorithms for Geospatial Computing
Credits:
3
Grad Meth:
Reg
Prerequisite: GEOG276 or minimum grade of C- in CMSC330 and CMSC351 or permission of instructor. Jointly offered with: GEOG470 and GEOG770. Credit only granted for: CMSC498Q, GEOG470, GEOG498I, GEOG770, or GEOG788I.
CMSC498T
Selected Topics in Computer Science; Applied Mechanism Design for Social Good
Credits:
3
Grad Meth:
Reg
Prerequisite: CMSC351. Recommended: MATH240, CMSC320, or CMSC422.
How do we allocate food to food banks, children to schools, organs to patients, residents to hospitals, security forces to patrol routes, and credit to multiple authors of an open source project-all in the face of competing incentives affecting selfish participants? Can we design mechanisms for these problems that perform well in practice, are computationally tractable, and whose workings and results are understandable by humans? To answer these questions, we devise models and solutions at the intersection of artificial intelligence, economics, and theoretical computer science.
How do we allocate food to food banks, children to schools, organs to patients, residents to hospitals, security forces to patrol routes, and credit to multiple authors of an open source project-all in the face of competing incentives affecting selfish participants? Can we design mechanisms for these problems that perform well in practice, are computationally tractable, and whose workings and results are understandable by humans? To answer these questions, we devise models and solutions at the intersection of artificial intelligence, economics, and theoretical computer science.
CMSC498Y
Selected Topics in Computer Science; Statistical Inference and Machine Learning Methods for Genomics Data
Credits:
3
Grad Meth:
Reg
Prerequisite: Minimum grade of C- in CMSC330 and CMSC351.
Covers statistical inference and machine learning methods for analyzing genomic data. Examples of topics covered will include maximum likelihood (including composite and pseudo-likelihood functions), expectation-maximization, clustering algorithms, hidden markov models, statistical testing, MCMC and variational inference. Our focus will be on how these techniques are utilized to solve biological problems and the practical challenges that arise when analyzing large genomic data sets.
Covers statistical inference and machine learning methods for analyzing genomic data. Examples of topics covered will include maximum likelihood (including composite and pseudo-likelihood functions), expectation-maximization, clustering algorithms, hidden markov models, statistical testing, MCMC and variational inference. Our focus will be on how these techniques are utilized to solve biological problems and the practical challenges that arise when analyzing large genomic data sets.
CMSC499A
Independent Undergraduate Research
Credits:
1 - 3
Grad Meth:
Reg
CMSC661
Scientific Computing II
Credits:
3
Grad Meth:
Reg
Prerequisite: Must have knowledge of Matlab or Python. Must have basic knowledge of ordinary and partial differential equations (MATH246 and MATH462 or equivalent, or permission of instructor).
Cross-listed with: AMSC661.
Credit only granted for: AMSC661 or CMSC661.
Numerical methods for solving ordinary and partial differential equations (elliptic, parabolic, hyperbolic, and dispersive): motivation, analysis, and implementation. Finite difference methods, finite element methods, Fourier and Chebyshev spectral methods, and meshless methods.
CMSC664
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.
CMSC711
Computer Networks
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.
CMSC724
Database Management Systems
Credits:
3
Grad Meth:
Reg, Aud
Restriction: Must be in one of the following programs (Computer Science (Master's); Computer Science (Doctoral)) ; or permission of instructor; or permission of CMNS-Computer Science department.
Theoretical and implementation issues in advanced database systems. Topics include distributed databases, parallel databases, database client-server architectures, multimedia access methods, advanced query optimization techniques, data semantics and models, object-oriented databases, and deductive and expert database systems.
CMSC725
Geographical Information Systems and Spatial Databases
Credits:
3
Grad Meth:
Reg, Aud
Prerequisite: CMSC424 and CMSC420; or permission of instructor.
Topics in geographic information systems and spatial databases. Integrates related results from databases, cartography, geography, computer graphics, file access methods, computational geometry, image processing, data structures, and programming languages. Topics include: cartographic modeling, principles of cartography, methods from computational geometry, principles of spatial databases, access methods, and spatial data structures. The architecture of some existing spatial databases and geographic information systems will be examined in greater detail.
CMSC727
Neural Modeling
Credits:
3
Grad Meth:
Reg, Aud
Prerequisite: CMSC421; or students who have taken courses with comparable content may contact the department; or permission of instructor.
Fundamental methods of neural modeling. Surveys historical development and recent research results from both the computational and dynamical systems perspective. Logical neurons, perceptrons, linear adaptive networks, attractor neural networks, competitive activation methods, error back-propagation, self-organizing maps, and related topics. Applications in artificial intelligence, cognitive science, and neuroscience.
CMSC733
Computer Processing of Pictorial Information
Credits:
3
Grad Meth:
Reg, Aud
Prerequisite: CMSC420.
Input, output, and storage of pictorial information. Pictures as information sources, efficient encoding, sampling, quantization, approximation. Position-invariant operations on pictures, digital and optical implementations, the pax language, applications to matched and spatial frequency filtering. Picture quality, image enhancement and image restoration. Picture properties and pictorial pattern recognition. Processing of complex pictures; figure extraction, properties of figures. Data structures for pictures description and manipulation; picture languages. Graphics systems for alphanumeric and other symbols, line drawings of two- and three-dimensional objects, cartoons and movies.
CMSC752
Ramsey Theory and its Applications
Credits:
3
Grad Meth:
Reg, Aud
Prerequisite: Any CMSC45X course or any 400-level math course.
Credit only granted for: CMSC858R or CMSC752.
Formerly: CMSC858R.
Theorems about when a coloring of a graph (or other objects) has to yield a nice monochromatic object. Applications will be to computer science theory and to mathematics.
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
Master's Non-Thesis Research
Credits:
1 - 3
Grad Meth:
Reg
CMSC799
Master's Thesis Research
Credits:
1 - 6
Grad Meth:
S-F
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.
CMSC818G
Advanced Topics in Computer Systems; Information-Centric Design of Systems
Credits:
3
Grad Meth:
Reg, Aud, S-F
CMSC828I
Advanced Topics in Information Processing; Multilingual Natural Language Processing
Credits:
3
Grad Meth:
Reg, Aud
CMSC828L
Advanced Topics in Information Processing; Deep Learning
Credits:
3
Grad Meth:
Reg, Aud
CMSC828O
Advanced Topics in Information Processing; Computational and Mathematical Analysis for Networks Across Scales
Credits:
3
Grad Meth:
Reg, Aud, S-F
CMSC838C
Advanced Topics in Programming Languages; Advances in XR
Credits:
3
Grad Meth:
Reg, Aud, S-F
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
CMSC848Q
Selected Topics in Information Processing; How and Why Artificial Intelligence Answers Questions
Credits:
3
Grad Meth:
Reg, Aud
CMSC858D
Advanced Topics in Theory of Computing; Algorithms, Data Structures and Inference for High-throughput Genomics
Credits:
3
Grad Meth:
Reg, Aud
Restriction: Must be a graduate student in CMSC or BISI program.
CMSC858F
Advanced Topics in Theory of Computing; Algorithmic Lower Bounds: Fun with Hardness Proofs
Credits:
3
Grad Meth:
Reg, Aud
CMSC858Q
Advanced Topics in Theory of Computing; Classical and Quantum Codes
Credits:
3
Grad Meth:
Reg, Aud
Prerequisites: MATH405 or MATH461, and ENEE324; or students who have taken courses with comparable content may contact the department. Cross-listing with MATH729C and ENEE729C and PHYS889C. Credit only granted forENEE729C, CMSC858Q, MATH729C, or PHYS899C.
The course will cover topics in classical and quantum coding theory from the unified perspective of protecting information in classical communication and supporting fault-tolerant computations in quantum computers. Topics in classical codes include: Reed-Solomon codes, codes on algebraic curves, Reed-Muller codes, polar codes, rank metric codes. Topics in quantum codes include: stabilizer codes, CSS codes, GKP codes, polynomial codes, toric code. See www.ece.umd.edu/~abarg/CQC for further details.
The course will cover topics in classical and quantum coding theory from the unified perspective of protecting information in classical communication and supporting fault-tolerant computations in quantum computers. Topics in classical codes include: Reed-Solomon codes, codes on algebraic curves, Reed-Muller codes, polar codes, rank metric codes. Topics in quantum codes include: stabilizer codes, CSS codes, GKP codes, polynomial codes, toric code. See www.ece.umd.edu/~abarg/CQC for further details.
CMSC898
Pre-Candidacy Research
Credits:
1 - 8
Grad Meth:
Reg
CMSC899
Doctoral Dissertation Research
Credits:
6
Grad Meth:
S-F
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