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Courses - Fall 2021
CMSC
Computer Science Department Site
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, P-F, Aud
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.
CMSC131
Object-Oriented Programming I
Credits: 4
Grad Meth: Reg
Corequisite: MATH140.
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.
CMSC133
Object Oriented Programming I Beyond Fundamentals
Credits: 2
Grad Meth: Reg
Corequisite: MATH140.
Restriction: Permission of CMNS-Computer Science department; and student must have earned a 4 on the AP Computer Science A exam or a satisfactory score on the CMSC131 department placement exam.
Credit only granted for: CMSC131 or CMSC133.
An introduction to computer science and object-oriented programming for students with prior Java programming knowledge (conditionals, loops, methods). Program design, implementation, and testing using object-oriented techniques. All programming will be done in Java using a graphical IDE.
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.
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.
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.
Additional information: CMSC351 may not count as one of the required upper level CMSC courses for students who are required to have 24 upper level CMSC credits for graduation, i.e. for students who became computer science majors prior to Fall, 2002.
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.
CMSC389N
(Perm Req)
Special Topics in Computer Science; Introduction to PHP and Javascript
Credits: 3
Grad Meth: Reg
Prerequisite: Minimum grade of C- in CMSC250 and CMSC216; and permission of CMNS-Computer Science department.
CMSC396H
(Perm Req)
Computer Science Honors Seminar
Credits: 1
Grad Meth: Reg
Prerequisite: Must have admission into Computer Science Departmental Honors Program.
Restriction: Permission of CMNS-Computer Science department.
Credit only granted for: CMSC297 or CMSC396.
Formerly: CMSC297.
Overview of computer science research activities, techniques, and tools. Diverse research areas will be covered, including systems, networks, artificial intelligence, human-computer interaction, software engineering, graphics, vision, and theory.
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, 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.
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 CMSC420.
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; or must be in the (Computer Science (Doctoral), Computer Science (Master's)) program.
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.
CMSC427
(Perm Req)
Credits: 3
Grad Meth: Reg
Prerequisite: MATH240; and minimum grade of C- in CMSC420; and permission of CMNS-Computer Science department. Or must be in the (Computer Science (Doctoral), Computer Science (Master's)) program.
An introduction to 3D computer graphics, focusing on the underlying building blocks and algorithms for applications such as 3D computer games, and augmented and virtual reality (AR/VR). Covers the basics of 3D image generation and 3D modeling, with an emphasis on interactive applications. Discusses the representation of 3D geometry, 3D transformations, projections, rasterization, basics of color spaces, texturing and lighting models, as well as programming of modern Graphics Processing Units (GPUs). Includes programming projects where students build their own 3D rendering engine step-by-step.
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); and permission of CMNS-Computer Science department. Or must be in the (Computer Science (Doctoral), Computer Science (Master's)) program.
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.
CMSC454
(Perm Req)
Algorithms for Data Science
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 (STAT400, STAT410); and permission of CMNS-Computer Science department.
Credit only granted for: CMSC454 or CMSC498U.
Formerly: CMSC498U.
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
(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). Or permission of instructor.
Also offered as: 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.
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.
Also offered as: 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.
Also offered as: 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, 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.
CMSC473
(Perm Req)
Capstone in Machine Learning
Credits: 3
Grad Meth: Reg
Prerequisite: Minimum grade of C- or higher in CMSC421 or CMSC422.
Recommended: Background or exposure to machine learning topics is strongly encouraged.
Restriction: Permission of instructor and Permission of CMSC - Computer Science department.
Credit only granted for: CMSC498P or CMSC473.
Formerly: CMSC498P.
Additional information: Students will be paired with project advisors from the UMD faculty or alternatively, an industry advisor. Students are encouraged to plan for projects results that can be published at academic conferences or will impact academic research.
Semester-long project course in which each student will identify and carry out a project related to machine learning, with the goal of publishing a research paper or software tool.
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.
Credit only granted for MATH475 or CMSC475.
CMSC498A
(Perm Req)
Selected Topics in Computer Science
Credits: 1 - 3
Grad Meth: Reg
Contact department for information to register for this course.
CMSC499A
(Perm Req)
Independent Undergraduate Research
Credits: 1 - 3
Grad Meth: Reg
Contact department for information to register for this course.
CMSC624
Database System Architecture and Implementation
Credits: 3
Grad Meth: Reg, Aud
Prerequisite: CMSC424; or students who have taken courses with comparable content may contact the department.
Credit only granted for: CMSC624 or CMSC828N.
Formerly: CMSC828N.
In-depth overview of database architectures--both the mainstream traditional architecture and more modern architectures that are especially prevalent in cloud implementations. Topics include different architectural choices for different application spaces and the tradeoffs inherent in choices and building different parts of database systems.
CMSC631
Program Analysis and Understanding
Credits: 3
Grad Meth: Reg, Aud, S-F
Prerequisite: CMSC330; or students who have taken courses with comparable content may contact the department; or permission of instructor.
Techniques for static analysis of source code and modern programming paradigms. Analysis techniques: data flow analysis, program dependence graphs, program slicing, abstract interpretation. The meaning of programs: denotational semantics, partial evaluation. Advanced treatment of abstraction mechanisms: polymorphic types, operation overloading, inheritance, object-oriented programming and ML-like programming languages.
CMSC657
Introduction to Quantum Information Processing
Credits: 3
Grad Meth: Reg
Prerequisite: Familiarity with complex numbers and basic concepts in linear algebra (e.g.
Credit only granted for: CMSC657 or CMSC858K.
Formerly: CMSC858K.
Additional information: Previous background in quantum mechanics or theory of computation is not required.
An introduction to the field of quantum information processing. Students will be prepared to pursue further study in quantum computing, quantum information theory, and related areas.
CMSC660
Scientific Computing I
Credits: 3
Grad Meth: Reg, Aud
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 AMSC66 0.
Credit only granted for: AMSC660 or CMSC660.
Monte Carlo simulation, numerical linear algebra, nonlinear systems and continuation method, optimization, ordinary differential equations. Fundamental techniques in scientific computation with an introduction to the theory and software for each topic.
CMSC663
(Perm Req)
Advanced Scientific Computing I
Credits: 3
Grad Meth: Reg
Prerequisite: AMSC660 or CMSC660; and (AMSC661 or CMSC661).
Restriction: Permission of instructor.
Cross-listed with AMSC663.
Credit only granted for: AMSC663 or CMSC663.
In the sequence Advanced Scientific Computing I & Advanced Scientific Computing II, (AMSC663/CMSC663 and AMSC664/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.
CMSC666
Numerical Analysis I
Credits: 3
Grad Meth: Reg, Aud
Prerequisite: CMSC466 or AMSC466; and MATH410.
Cross-listed with: AMSC666.
Credit only granted for: AMSC666 or CMSC666.
Approximation theory, numerical solution of initial-value problems, iterative methods for linear systems, optimization.
CMSC715
Wireless and Mobile Systems for the IoT
Credits: 3
Grad Meth: Reg, Aud
Prerequisite: CMSC417.
Recommended: STAT100, MATH141, MATH240, and CMSC106; or equivalent courses.
Credit only granted for: CMSC818W or CMSC715.
Formerly: CMSC818W.
Research on the Internet of Things (IoT), from the perspective of wireless networking and mobile sensing. Various techniques, algorithms, and systems that leverage the sensors in smartphones, smartwatches, drones, and IoT devices, to deliver real-world applications
CMSC730
Interactive Technologies in Human-Computer Interaction
Credits: 3
Grad Meth: Reg, Aud
Restriction: Must be in the Computer Science Master's or Doctoral program; or permission of instructor.
Credit only granted for: CMSC838J or CMSC730.
Formerly: CMSC838J.
Ubiquitous and mobile computing, wearables, virtual/augmented reality, natural user interfaces, tangible UIs, interactive fabrication.
CMSC732
Human Factors in Security and Privacy
Credits: 3
Grad Meth: Reg, Aud
Recommended: Previous coursework in human-computer interaction, security and privacy.
Credit only granted for: CMSC818D or CMSC732.
Formerly: CMSC818D.
Introducing a variety of important topics at the intersection of human factors and privacy and security, and developing skills in designing human-subjects studies to evaluate problems and solutions related to these topics.
CMSC734
Information Visualization
Credits: 3
Grad Meth: Reg, Aud, S-F
Prerequisite: CMSC434; or students who have taken courses with comparable content may contact the department; or permission of instructor.
Information visualization defined in relation to graphics, scientific visualization, databases, data mining, and human-computer interaction. Visualizations for dimensional, temporal, hierarchical and network data. Examines design alternatives, algorithms and data structures, coordinated views, and human factors evaluations of efficacy.
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.
CMSC754
Computational Geometry
Credits: 3
Grad Meth: Reg, Aud, S-F
Prerequisite: CMSC451 and CMSC420; or permission of instructor.
Introduction to algorithms and data structures for computational problems in discrete geometry (for points, lines, and polygons) primarily in two and three dimensions. Topics include triangulations and planar subdivisions, geometric search and intersection, convex hulls, Voronoi diagrams, Delaunay triangulations, line arrangements, visibility, and motion planning.
CMSC756
Credits: 3
Grad Meth: Reg, Aud
Prerequisite: CMSC420, CMSC106, CMSC466, and MATH240; or equivalent.
Restriction: Must be in the Computer Science Master's or Doctoral programs.
Credit only granted for: CMSC818N or CMSC756.
Formerly: CMSC818N.
Overview on fundamental components of robotic systems, including the sensing and actuation, control and modeling of motion and perception, dynamics and kinematics, motion planning and manipulation of robots.
CMSC763
Advanced Linear Numerical Analysis
Credits: 3
Grad Meth: Reg, Aud
Prerequisite: AMSC666 or CMSC666; or permission of instructor.
Also offered as: AMSC763.
Credit only granted for: AMSC600, AMSC763, CMSC760, or CMSC763.
Formerly: AMSC600 and CMSC760.
Advanced topics in numerical linear algebra, such as dense eigenvalue problems, sparse elimination, iterative methods, and other topics.
CMSC798
(Perm Req)
Master's Non-Thesis Research
Credits: 1 - 3
Grad Meth: Reg
Contact department for information to register for this course.
CMSC798P
Master's Non-Thesis Research; Machine Learning Capstone
Credits: 3
Grad Meth: Reg, Aud, S-F
CMSC799
(Perm Req)
Master's Thesis Research
Credits: 1 - 6
Grad Meth: S-F
Contact department for information to register for this course.
CMSC801
Department Internal Research Seminar
Credits: 1
Grad Meth: Reg
Credit only granted for: CMSC798E or CMSC801.
Formerly: CMSC798E.
Research overviews from faculty to help introduce departmental research to graduate students.
CMSC818E
Advanced Topics in Computer Systems; Clouds, Consistency, & Consensus
Credits: 3
Grad Meth: Reg, Aud
The guiding philosophy of this course is that the best way to learn about real systems is to build them. We will cover peer-to-peer systems, microservices, multi-threading, consensus, and the protocols underlying cloud services.
CMSC818F
Advanced Topics in Computer Systems; Cryptography and Hostile Governments
Credits: 3
Grad Meth: Reg, Aud, S-F
CMSC828C
Advanced Topics in Information Processing; Statistical Pattern Recognition
Credits: 3
Grad Meth: Reg, Aud
CMSC828I
Advanced Topics in Information Processing; Advanced Techniques in Visual Learning and Recognition
Credits: 3
Grad Meth: Reg, Aud
Prerequisite: CMSC422, CMSC426, or equivalent; or permission of instructor.
CMSC828J
Advanced Topics in Information Processing; Common-sense Reasoning and Natural Language Understanding
Credits: 3
Grad Meth: Reg, Aud
CMSC828V
Advanced Topics in Information Processing; Numerical Methods for Data Science and Machine Learning
Credits: 1 - 3
Grad Meth: Reg, Aud, S-F
CMSC828W
Advanced Topics in Information Processing; Foundations of Deep Learning
Credits: 3
Grad Meth: Reg, Aud
Restricted to Computer Science (Master's/Doctoral) students; or permission of instructor.

In this course, we are going to explore empirically-relevant theoretical foundations of deep learning (DL). We will cover topics including DL optimization, DL generaliation, Neural Tangent Kernels, Deep Generative Models, DL Robustness, DL Interpretability, Domain Adaptation and Generalization, Self-Supervised Learning and Deep Reinforcement Learning.
CMSC828Z
Advanced Topics in Information Processing; Just Machine Learning
Credits: 3
Grad Meth: Reg, Aud, S-F
Data-driven systems are increasingly deployed in settings that directly or indirectly people's rights, lives, and well-being. This raises urgent needs to understand how such models lead to more, or less, justice in the world. This course introduces a range of notions around justice, rights, and equity, as well as their computation implementations in machine learning systems. Students are welcome who have backgrounds in machine learning, or in ethics and justice, or both.
CMSC838G
Advanced Topics in Programming Languages; Testing and Verification
Credits: 3
Grad Meth: Reg, Aud, S-F
This course will focus on establishing software correctness using advanced formal verification, random-testing, and fuzzing techniques. Knowledge of at least one functional programming language (e.g. OCaml, Haskell, or Coq) is strongly recommended.
CMSC838X
Advanced Topics in Programming Languages; Personal Health Informatics & Visualization
Credits: 3
Grad Meth: Reg, Aud
Jointly offered with INST682. Credit only granted for INST682 or CMSC838 X.
CMSC858O
Advanced Topics in Theory of Computing; The Foundation of End-to-End Quantum Applications
Credits: 1 - 3
Grad Meth: Reg, Aud, S-F
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.