Jun 22, 2024  
USC Catalogue 2020-2021 
    
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USC Catalogue 2020-2021 [ARCHIVED CATALOGUE]

Courses of Instruction

The terms indicated are expected but are not guaranteed. For the courses offered during any given term, consult the Schedule of Classes.
 

Computer Science
  

  • CSCI 491aL Final Game Project

    Units: 4
    Terms Offered: FaSpSm
    Design, iterative prototyping, and development of a 1st playable level.
    Registration Restriction: Open only to seniors.
    Instruction Mode: Lecture, Lab Required
    Grading Option: Letter

  

  • CSCI 491bL Final Game Project

    Units: 2
    Terms Offered: FaSpSm
    Design, iterative stage 2 prototyping and development of a refined game.
    Instruction Mode: Lecture, Lab Required
    Grading Option: Letter

  

  • CSCI 495 Senior Project

    Units: 3
    (Enroll in PHYS 495 )
  

  • CSCI 499 Special Topics

    Units: 2, 3, 4
    Max Units: 08
    Selected topics in computer science.
    Instruction Mode: Lecture, Discussion
    Grading Option: Letter

  

  • CSCI 501 Numerical Analysis and Computation

    Units: 3
    (Enroll in MATH 501 )
  

  • CSCI 502a Numerical Analysis

    Units: 3
    (Enroll in MATH 502a )
  

  • CSCI 502b Numerical Analysis

    Units: 3
    (Enroll in MATH 502b )
  

  • CSCI 504a Numerical Solutions of Ordinary and Partial Differential Equations

    Units: 3
    (Enroll in MATH 504a )
  

  • CSCI 504b Numerical Solutions of Ordinary and Partial Differential Equations

    Units: 3
    (Enroll in MATH 504b )
  

  • CSCI 505a Applied Probability

    Units: 3
    (Enroll in MATH 505a )
  

  • CSCI 505b Applied Probability

    Units: 3
    (Enroll in  MATH 505b )
  

  • CSCI 510 Software Management and Economics

    Units: 4
    Theories of management and their application to software projects. Economic analysis of software products and processes. Software cost and schedule estimation, planning and control.
    Instruction Mode: Lecture
    Grading Option: Letter

    Crosslisted as ISE 512
  

  • CSCI 511 Personal Software Process (PSP) and Project

    Units: 3
    Terms Offered: Sp
    Individual analysis, planning, development and maintenance of a software product or development artifact, using the principles and practices of PSP. Analysis of project’s lessons learned.
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 512 Testing and Analysis of Software Systems

    Units: 4
    Introduces students to the topic of automated testing and analysis of large-scale modern software systems.
    Recommended Preparation: CSCI 571 ; Java programming skills; Linux system administration.
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 513 Autonomous Cyber-Physical Systems

    Units: 4
    Terms Offered: FaSp
    Components, software and applications of cyber-physical systems; autonomy; control techniques; development and testing; artificial intelligence and machine learning algorithms.
    Recommended Preparation: Fundamentals of control and automata theory; familiarity with Matlab, Simulink, and R
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 520 Computer Animation and Simulation

    Units: 4
    Fundamental techniques of computer animation and simulation, knowledge and/or experience in the design, scripting, production and post-production stages of computer animation.
    Prerequisite: CSCI 420  or CSCI 580  
    Recommended Preparation: Familiarity with calculus, linear algebra, and numerical computation; C/C++ programming skills
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 521 Optimization: Theory and Algorithms

    Units: 3
    Terms Offered: Fa
    (Enroll in ISE 520 )
  

  • CSCI 522 Game Engine Development

    Units: 4
    Terms Offered: Fa
    The principles of developing game engines targeted at modern PC and game console hardware.
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 523L Networked Games

    Units: 4
    Terms Offered: FaSpSm
    Design and implementation of networked games, from the origins of the supporting technologies in distributed systems, visual simulations, networked virtual environments, and shipped games.
    Recommended Preparation: CSCI 420  or CSCI 580  or an equivalent course in graphics.
    Instruction Mode: Lecture, Lab Required
    Grading Option: Letter

  

  • CSCI 524 Networked Artificial Intelligence

    Units: 4
    Networked game communication architectures, protocol development, architecting networked game AI clients/services. Character following, knowledge representation and reasoning, dynamic play strategies, search, learning, and planning.
    Recommended Preparation: CSCI 420  or CSCI 580  or an equivalent course in graphics
    Instruction Mode: Lecture, Lab
    Grading Option: Letter

  

  • CSCI 526 Advanced Mobile Devices and Game Consoles

    Units: 4
    Terms Offered: FaSpSm
    Explore the complex engineering process required to design and build a real-time graphics engine to support physical realism on mobile devices.
    Recommended Preparation: CSCI 420  or CSCI 580  or an equivalent course in graphics
    Instruction Mode: Lecture, Lab Required
    Grading Option: Letter

  

  • CSCI 527 Applied Machine Learning for Games

    Units: 4
    Terms Offered: FaSp
    Application of machine learning for AI-bot creation, gameplay analysis, and real-time game player understanding. Duplicates credit in CSCI 566 Deep Learning and Its Applications .
    Prerequisite: CSCI 561  or CSCI 567 
    Duplicates Credit in CSCI 566 
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 529a Advanced Game Projects

    Units: 4
    Terms Offered: FaSp
    Team projects intended to address the multifaceted technical and creative challenges that are inherent to comprehensive game development.
    Recommended Preparation: CSCI 522  or CTIN 488 .
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 529b Advanced Game Projects

    Units: 2
    Terms Offered: FaSpSm
    Provides students in various areas of game specialization the practice of design, iterative stage 2 prototyping and development of a refined game.
    Prerequisite: CSCI 529a  
    Instruction Mode: Lecture, Lab
    Grading Option: Letter

  

  • CSCI 530 Security Systems

    Units: 4
    Terms Offered: FaSp
    Protecting computer networks and systems using cryptography, authentication, authorization, intrusion detection and response. Includes lab to provide practical experience working with such systems.
    Prerequisite: CSCI 402 .
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 531 Applied Cryptography

    Units: 4
    Intensive overview of cryptography for practitioners, historical perspective on early systems, number theoretic foundations of modern day cryptosystems and basic cryptanalysis.
    Recommended Preparation: Programming in C/C++ (CSCI 103), Data structures (CSCI 104) 
    Instruction Mode: Lecture, Discussion
    Grading Option: Letter

  

  • CSCI 533 Algebraic Combinatorics

    Units: 3
    Terms Offered: Irregular
    (Enroll in MATH 533 )
  

  • CSCI 534 Affective Computing

    Units: 4
    Terms Offered: Sp
    Overview of the theory of human emotion, techniques for recognizing and synthesizing emotional behavior, and design application.
    Recommended Preparation: CSCI 561 
    Instruction Mode: Lecture
    Grading Option: Letter

    Crosslisted as PSYC 532
  

  • CSCI 535 Multimodal Probabilistic Learning of Human Communication

    Units: 4
    Principles and techniques to understand, build, and utilize multimodal machine learning algorithms through automatically understanding, recognizing, and analyzing phenomena of human communication.
    Recommended Preparation: CSCI 542   or CSCI 567   or CSCI 573   or equivalent
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 536 Linear Programming and Extensions

    Units: 3
    Terms Offered: Fa
    (Enroll in ISE 536 )
  

  • CSCI 538 Augmented, Virtual and Mixed Reality

    Units: 4
    Terms Offered: FaSp
    Technical design and implementation of immersive environments; visual simulations, interactive 3D graphics and games.
    Recommended Preparation: CSCI 420  or CSCI 580 
    Instruction Mode: Lecture, Lab
    Grading Option: Letter

  

  • CSCI 540 Self-Organization

    Units: 4
    Massively distributed systems whose global behavior emerges from local interactions of components. Global to local compilation; robot swarms; formation of shapes/spatial patterns; self-assembly; programmable matter.
    Registration Restriction: Graduate standing in science or engineering
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 542 Neural Computation with Artificial Neural Networks

    Units: 3
    Terms Offered: Sp
    Computation and adaptation in networks of interconnected distributed processing units; classical and statistical approaches to neural nets; stateof- the-art neural network research.
    Recommended Preparation: basic statistics, linear algebra.
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 544 Applied Natural Language Processing

    Units: 4
    Introduction to key components of human language technologies, including: information extraction, sentiment analysis, question answering, machine translation.
    Recommended Preparation: proficiency in programming, algorithms and data structures, basic knowledge of linear algebra.
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 545 Robotics

    Units: 4
    Terms Offered: FaSpSm
    Fundamental skills for modeling and controlling of dynamic systems for robotic applications and graphics animations; control theory; kinematics; dynamics; sensor processing; real-time operating systems; robot labs.
    Recommended Preparation: Basic knowledge in linear algebra (matrices and vectors), calculus, programming in C/C++ or any another language or permission of the instructor
    Instruction Mode: Lecture, Lab
    Grading Option: Letter

    Crosslisted as EE-545
  

  • CSCI 548 Information Integration on the Web

    Units: 4
    Terms Offered: FaSpSm
    Foundations and techniques in information integration as it applies to the Web, including view integration, wrapper learning, record linkage, and streaming dataflow execution.
    Prerequisite: CSCI 561  
    Recommended Preparation: CSCI 585 and some programming experience
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 549 Nanorobotics

    Units: 3
    Terms Offered: Sp
    Introduction to nanotechnology. Nanorobotic systems: sensing; actuation and propulsion; control; communication; power; programming and coordination of robot swarms. Nanomanipulation and nanoassembly with atomic force microscopes.
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 550 Advanced Data Stores

    Units: 4
    Selected topics on highly available, elastic data stores. Topics include non-relational data models, simple interfaces and query languages, weak consistency and benchmarking techniques.
    Prerequisite: CSCI 485  or CSCI 585  
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 551 Computer Networking

    Units: 4
    Protocol design for computer communication networks, network routing, transport protocols, internetworking.
    Prerequisite: CSCI 350  (CSCI 353  or EE 450 ) and (CSCI 350  or CSCI 402 )
    Recommended Preparation: C-language programming 
    Instruction Mode: Lecture, Quiz
    Grading Option: Letter

  

  • CSCI 552 Asynchronous VLSI Design

    Units: 3
    (Enroll in EE 552 )
  

  • CSCI 553 Computational Solution of Optimization Problems

    Units: 3
    Terms Offered: Sp
    (Enroll in EE 553 )
  

  • CSCI 554 Real Time Computer Systems

    Units: 3
    (Enroll in EE 554 )
  

  • CSCI 555L Advanced Operating Systems

    Units: 4
    Advanced topics in operating system research: new OS structures, novel memory management, communication, file system, process management, reliability and security techniques.
    Prerequisite: CSCI 350  or CSCI 402  
    Instruction Mode: Lecture, Lab Required
    Grading Option: Letter

  

  • CSCI 556 Introduction to Cryptography

    Units: 4
    Modern secret codes. Public key cryptosystems of Rivest- Shamir-Adleman, Diffie-Hellman and others. The underlying number theory and computational complexity theory.
    Prerequisite: CSCI 570  or CSCI 581 
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 557 Computer Systems Architecture

    Units: 4
    Terms Offered: FaSp
    (Enroll in EE 557 )
  

  • CSCI 558L Internetworking and Distributed Systems Laboratory

    Units: 3
    Terms Offered: FaSp
    Students complete laboratory exercises in operating system and network management, distributed systems, TCP/IP, SNMP, NFS, DNS, etc. Term project required.
    Prerequisite: CSCI 402  and EE 450 /CSCI 450 ;
    Recommended Preparation: CSCI 551  and CSCI 555 .
    Instruction Mode: Lecture, Lab Required
    Grading Option: Letter

  

  • CSCI 559 Mathematical Pattern Recognition

    Units: 3
    Terms Offered: Sp
    (Enroll in EE 559 )
  

  • CSCI 561 Foundations of Artificial Intelligence

    Units: 4
    Terms Offered: FaSpSm
    Foundations of symbolic intelligent systems, search, logic, knowledge representation, planning, learning.
    Recommended Preparation: good programming and algorithm analysis skills
    Instruction Mode: Lecture, Discussion, Quiz
    Grading Option: Letter

    Crosslisted as EE 561
  

  • CSCI 564 Brain Theory and Artificial Intelligence

    Units: 3
    Terms Offered: Fa
    Introduces neural modeling, distributed artificial intelligence and robotics approaches to vision, motor control and memory.
    Prerequisite: graduate standing.
    Instruction Mode: Lecture
    Grading Option: Letter

    Crosslisted as NEUR-535
  

  • CSCI 565 Compiler Design

    Units: 4
    Terms Offered: Sp
    Formal grammar; parsing methods and lexical analysis; code generation; local and global code optimization; and dynamic allocation.
    Prerequisite: CSCI 455x .
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 566 Deep Learning and Its Applications

    Units: 4
    Terms Offered: Fa
    Deep learning research in computer vision, natural language processing and robotics; neural networks; deep learning algorithms, tools and software.
    Recommended Preparation: Python programming, calculus, linear algebra, probability and statistics, knowledge of machine learning
    Duplicates Credit in CSCI 527
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 567 Machine Learning

    Units: 4
    Terms Offered: Fa
    Statistical methods for building intelligent and adaptive systems that improve performance from experiences; focus on theoretical understanding of these methods and their computational implications.
    Recommended Preparation: Undergraduate level training or course work in linear algebra, multivariate calculus, basic probability and statistics; an undergraduate level course in Artificial Intelligence may be helpful but is not required.
    Instruction Mode: Lecture, Discussion
    Grading Option: Letter

    Crosslisted as ISE-568
  

  • CSCI 568 Requirements Engineering

    Units: 4
    Techniques for successful requirements analysis and requirements engineering (RE) of software-intensive systems. Systematic process of developing requirements through cooperative problem analysis, representation, and validation.
    Prerequisite: CSCI 577a
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 569 Social Media Analytics

    Units: 4
    Introduction to quantitative analysis of social data. Topics include social network analysis, text analysis, machine learning and statistical methods and they are used to study influence, information diffusion, sentiment analysis and prediction of individual and social behavior online.
    Recommended Preparation: statistics, AI and/or machine learning, knowledge of at least one programming language (Java, C++, Python)
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 570 Analysis of Algorithms

    Units: 4
    Terms Offered: FaSpSm
    Explores fundamental techniques such as recursion, Fourier transform ordering, dynamic programming for efficient algorithm construction. Examples include arithmetic, algebraic, graph, pattern matching, sorting, searching algorithms.
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 571 Web Technologies

    Units: 4
    Terms Offered: FaSpSm
    Advanced study of programming languages with application to the Web. Languages for client-side and server-side processing. Examples taken from: HTML, Java, JavaScript, Perl, XML and others.
    Recommended Preparation: knowledge of at least two programming languages.
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 572 Information Retrieval and Web Search Engines

    Units: 4
    Terms Offered: FaSpSm
    Examines key aspects of information retrieval as they apply to search engines; web crawling, indexing, querying and quality of results are studied.
    Recommended Preparation: Familiarity in programming in multiple languages, C, C++, and/or Java and experience with a database
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 573 Probabilistic Reasoning

    Units: 3
    Terms Offered: Fa
    Reasoning under uncertainty, statistical directed and undirected graphical models, temporal modeling, inference in graphical models, parameter learning, decisions under uncertainty.
    Recommended Preparation: An undergraduate level course in probability theory.
    Instruction Mode: Lecture
    Grading Option: Letter

    Crosslisted as ISE-574
  

  • CSCI 574 Computer Vision

    Units: 3
    Terms Offered: Fa
    Description and recognition of objects, shape analysis, edge and region segmentation, texture, knowledge based systems, image understanding.
    Prerequisite: CSCI 455x .
    Instruction Mode: Lecture
    Grading Option: Letter

    Crosslisted as EE-574
  

  • CSCI 576 Multimedia Systems Design

    Units: 4
    End-to-end multimedia systems -  content creation, compression, distribution using modern standards, DRM solutions,  Digital-Cinema pipeline, multimedia classification, virtual-augmented reality, natural-language multimedia queries, multimodal media analysis, stereoscopic-holographic  technologies.
    Recommended Preparation: familiarity with C or C++
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 577a Software Engineering

    Units: 4
    Terms Offered: FaSp
    Software life cycle processes; planning considerations for product definition, development, test, implementation, maintenance. Software requirements elicitation and architecture synthesis. Team project.
    Prerequisite: graduate standing.
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 577b Software Engineering

    Units: 4
    Terms Offered: FaSp
    Software development, test, implementation, and maintenance methods. CASE tools and software environments. Software product engineering, configuration management, quality engineering, documentation. Application via projects.
    Prerequisite: CSCI 577a .
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 578 Software Architectures

    Units: 4
    Study of concepts, principles and scope of software system architectures, including architectural styles, languages, connectors, middleware, dynamism, analysis, testing and domain-specific approaches.
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 580 3-D Graphics and Rendering

    Units: 4
    Course outlines the process of creating images from 3D models. Includes transformations, shading, lighting, rastorization, texturing, and other topics.
    Instruction Mode: Lecture, Discussion
    Grading Option: Letter

  

  • CSCI 581 Logic and its Applications

    Units: 3
    Formal systems, first order logic, truth, completeness, compactness, Godel incompleteness, recursive functions, undecidability. Selected applications, e.g., theorem proving, artificial intelligence, program verification, databases, computational complexity.
    Prerequisite: CSCI 430  and MATH 470.
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 582 Geometric Modeling

    Units: 3
    Terms Offered: Sp
    Mathematical models and computer representations for three-dimensional solids; underlying topics from set theory, geometry, and topology. Fundamental algorithms; applications to CAD/CAM and robotics.
    Recommended Preparation: Linear algebra and data structures.
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 583 Machine Learning Theory

    Units: 4
    Developing the core concepts and techniques, inherent abilities, and limitations of learning algorithms in well-defined learning models.
    Recommended Preparation: CSCI 270 , CSCI 567 
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 585 Database Systems

    Units: 4
    Terms Offered: FaSpSm
    Database system architecture; conceptual database models; semantic, object-oriented, logic-based, and relational databases; user and program interfaces; database system implementation; integrity, security, concurrency and recovery.
    Recommended Preparation: Knowledge of relational databases, SQL, relational algebra and physical database design is required
    Registration Restriction: Open only to graduate students.
    Instruction Mode: Lecture, Discussion, Quiz
    Grading Option: Letter

  

  • CSCI 586 Database Systems Interoperability

    Units: 4
    Federated and multi-database systems, database networking, conceptual and schematic diversity, information sharing and exchange, knowledge discovery, performance issues.
    Prerequisite: CSCI 585 
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 587 Geospatial Information Management

    Units: 4
    Techniques to efficiently store, manipulate, index and query geospatial information in support of real-world geographical and decision-making applications.
    Prerequisite: CSCI 485  or CSCI 585  or SSCI 582
    Recommended Preparation: Familiarity with conceptual data modeling tools such as Entity-Relationship (ER) data model, logical data models such as the relational and object-relational data model, SQL3 as a commercial query language, normal forms and logical data design. Familiarity with the physical design of a database using persistent data structures such as B+-tree and Hash indexes
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 589 Software Engineering for Embedded Systems

    Units: 4
    Terms Offered: FaSpSm
    Software engineering methods and techniques for embedded, resource constrained, and mobile environments. Applications to real-time operating systems and wireless networking systems. Class project.
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 590 Directed Research

    Units: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12
    Research leading to the master’s degree. Maximum units which may be applied to the degree to be determined by the department.
    Instruction Mode: Lecture
    Grading Option: Credit/No Credit

  

  • CSCI 591 Computer Science Research Colloquium

    Units: 1
    Max Units: 2
    Exploration and critical assessment of research activities in computer science. Course will serve as a forum for current research presentations from academia and industry
    Instruction Mode: Lecture
    Grading Option: Credit/No Credit

  

  • CSCI 593 Mathematical Foundations for System Design: Modeling, Analysis, and Synthesis

    Units: 3
    (Enroll in EE 581 )
  

  • CSCI 594a Master’s Thesis

    Units: 2
    Terms Offered: FaSpSm
    Credit on acceptance of thesis.
    Instruction Mode: Lecture
    Grading Option: In-progress to Credit/No Credit

  

  • CSCI 594b Master’s Thesis

    Units: 2
    Terms Offered: FaSpSm
    Credit on acceptance of thesis.
    Instruction Mode: Lecture
    Grading Option: In-progress to Credit/No Credit

  

  • CSCI 594z Master’s Thesis

    Units: 0
    Terms Offered: FaSpSm
    Credit on acceptance of thesis.
    Instruction Mode: Lecture
    Grading Option: In-progress to Credit/No Credit

  

  • CSCI 596 Scientific Computing and Visualization

    Units: 4
    Hands-on training on the basics of parallel computing and scientific visualization in the context of computer simulations in science and engineering.
    Recommended Preparation: CSCI 455x  and MATH 458 .
    Instruction Mode: Lecture, Discussion
    Grading Option: Letter

  

  • CSCI 598 Professional Writing and Communication for Computer Scientists

    Units: 1
    Instruction in discipline-specific workplace writing and communication skills for computer science graduate students.
    Registration Restriction: Open only to graduate students in Computer Science
    Instruction Mode: Lecture
    Grading Option: Credit/No Credit

  

  • CSCI 599 Special Topics

    Units: 2, 3, 4
    Max Units: 9.0
    Course content to be selected each semester from recent developments in computer science.
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 610 Advanced Program Analysis and Verification

    Units: 4
    Advanced techniques for analyzing and verifying software systems; topics include program analysis, automated verification, and software testing.
    Recommended Preparation: CSCI 512 , Java Programming Skills
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 620 Computer Animation and Simulation

    Units: 4
    Animation and Simulation techniques for computer games, virtual reality, and film visual effects. Research methods, SIGGRAPH papers. Deformable objects, fluids, sound, collision detection, haptics, rigid bodies, GPUs.
    Prerequisite: CSCI 420   or CSCI 520   or CSCI 580  
    Recommended Preparation: Familiarity with calculus, linear algebra, and numerical computation and C++ programming skills
    Registration Restriction: Open only to doctoral students
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 621 Digital Geometry Processing

    Units: 4
    Digital geometry processing (subfield of computer graphics), that covers the full pipeline from 3D scanning, processing, to 3D printing.
    Recommended Preparation: Solid background in linear algebra, numerical optimization, and C/C++ programming. CSCI 420  Computer Graphics is recommended. Open only to Computer Science doctoral students.
    Registration Restriction: Open only to Computer Science doctoral students.
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 631 Privacy in the World of Big Data

    Units: 4
    Privacy challenges that arise in the world driven by data. An overview of algorithmic and technical approaches to addressing them.
    Recommended Preparation: thorough understanding of algorithms, proof-based mathematics, and basic probability
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 644 Natural Language Dialogue Systems

    Units: 4
    Computational models of natural language dialogue; conversational interfaces to artificial systems; dialogue system architectures and applications; Reinforcement learning of dialogue policies.
    Recommended Preparation: CSCI 544  or CSCI 561  or CSCI 662  or EE 619 ; Java, C++ or Python
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 646 Coordinated Mobile Robotics

    Units: 4
    State-of-the-art techniques for coordinating robot teams. Distributed approaches; task allocation; control and stability; network topology; coverage and monitoring; caging; bio-inspired approaches; persistence; probabilistic methods.
    Recommended Preparation: Solid background in linear algebra, programming and algorithm analysis skills.
    Registration Restriction: Open only to Computer Science doctoral students.
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 648 Advanced Information Integration

    Units: 4
    Focus on foundations and techniques for information integration. Topics include Semantic Web, linked data, data integration, entity linkage, source modeling, and information extraction.
    Prerequisite: CSCI 561 ;
    Recommended Preparation: CSCI 585  and programming experience.
    Registration Restriction: Open only to Computer Science doctoral students.
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 651 Advanced Computer Networking

    Units: 4
    Computer communication protocols and systems, including classic and contemporary literature. The emphasis is on conceptual issues in the design and implementation of computer internetworks.
    Prerequisite: EE 450  (CSCI 353  or CSCI 350 ) and (CSCI 350  or CSCI 402 )
    Registration Restriction: Open to PhD students in Computer Science
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 652 Internet Measurement

    Units: 4

    The investigation of problems, techniques, results, and challenges that arise in measuring the Internet, including what measurements tell us about the Internet and how to improve Internet services.
    Prerequisite: CSCI 551 
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 653 High Performance Computing and Simulations

    Units: 4
    Terms Offered: FaSpSm
    Advanced high-performance computer simulation techniques; multiscale deterministic and stochastic simulation algorithms on parallel and distributed computing platforms; immersive and interactive visualization of simulation data.
    Prerequisite: CSCI 596  
    Instruction Mode: Lecture, Discussion
    Grading Option: Letter

  

  • CSCI 655 Advanced Topics in Operating Systems

    Units: 4
    Terms Offered: Fa
    Advanced OS architectures; methods in design and evaluation of process management and concurrency; reliable distributed file systems; memory management, for cloud and virtualized environments.
    Prerequisite: CSCI 350  or CSCI 402 
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 656 Networked Systems in Cloud Computing

    Units: 4
    Systems and network design and protocols in cloud computing and data centers networks.  
    Prerequisite: CSCI 551  or CSCI 651 
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 657 Advanced Distributed Systems

    Units: 4
    The foundations and modern applications of distributed systems. Topics include: logical time, fault tolerance, group communication, consensus, consistency, transactions, and peer-to-peer.
    Recommended Preparation: Proficiency in a high-level language, ideally C++, and familiarity with Git.
    Registration Restriction: Open only to Computer Science doctoral students.
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 658 Diagnosis and Design of Reliable Digital Systems

    Units: 3
    (Enroll in EE 658 )
  

  • CSCI 659 Introduction to Online Optimization

    Units: 4
    Foundation and advances of the theory of online learning/online convex optimization/sequential decision making.
    Recommended Preparation: Familiarity with probability, convex analysis, calculus, and analysis of algorithms
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 662 Advanced Natural Language Processing

    Units: 4
    Computational models of natural language. Formalisms for describing structures of human language, and algorithms for learning language structures from data.
    Recommended Preparation: proficiency in programming, algorithms and data structures, discrete math, probability theory, and calculus.
    Registration Restriction: Open only to doctoral students
    Duplicates Credit in former CSCI 562.
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 663 Artificial Intelligence for Social Good

    Units: 4
    Terms Offered: Fa
    Deployment of artificial intelligence tools in various social good contexts such as health, environmental sustainability, public safety and public welfare.
    Recommended Preparation: Familiarity with: linear programming and optimization; Excel, CPLEX, R or other optimization software or statistical analysis techniques; and Amazon Mechanical Turk
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 668 Search and Planning

    Units: 4
    Foundations of the design and implementation of search and planning techniques from artificial intelligence, including their theory and applications.
    Prerequisite: CSCI 561  
    Recommended Preparation: undergraduate introduction to algorithms and data structures undergraduate or graduate introduction to artificial intelligence ability to program in C/C++                  
    Registration Restriction: Open only to doctoral students
    Instruction Mode: Lecture
    Grading Option: Letter

  

  • CSCI 670x Advanced Analysis of Algorithms

    Units: 4
    Terms Offered: FaSpSm
    Fundamental techniques for design and analysis of algorithms. Dynamic programming; network flows; theory of NP-completeness; linear programming; approximation, randomized, and online algorithms; basic cryptography.
    Prerequisite: CSCI 570 ;
    Recommended Preparation: familiarity with algorithms and discrete mathematics.
    Registration Restriction: Open only to doctoral students.
    Instruction Mode: Lecture
    Grading Option: Letter

    Crosslisted as ISE-670
  

  • CSCI 671 Randomized Algorithms

    Units: 4
    Standard techniques in the design and analysis of randomized algorithms and random structures. Topics include tail bounds, Markov Chains, VC-dimension, probabilistic method.
    Prerequisite: CSCI 570  or CSCI 670  
    Recommended Preparation: Basic background in probability and linear algebra
    Instruction Mode: Lecture
    Grading Option: Letter

    Crosslisted as ISE-671
 

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