Course Recommender Individuals Ontology
type: Ontology
abstract: This ontology captures Individuals relevant to course recommendation, including a large selection of Courses, CourseSections, and some Students with PlanOfStudys.
creator: Jacob Shomstein
creator: Kelly Fellenzer
creator: Owen Xie
creator: Sola Shirai
license: License - to be updated with an appropriate license.
modified: 2020-11-20T23:59:59
publisher: Course Recommender Team
copyright: Copyright - to be updated with an appropriate copyright statement.
depends on: https://spec.edmcouncil.org/fibo/ontology/BE/
depends on: https://spec.edmcouncil.org/fibo/ontology/FND/
depends on: https://www.omg.org/spec/LCC/
imports: FormalBusinessOrganizations
imports: LegalPersons
imports: People
imports: ClassificationSchemes
imports: IdentifiersAndIndices
imports: BusinessDates
imports: FinancialDates
imports: Occurrences
imports: Parties
imports: Roles
imports: Addresses
imports: Locations
imports: VirtualPlaces
imports: Relations
imports: AnnotationVocabulary
imports: course-recommender
imports: CountryRepresentation
imports: ISO3166-1-CountryCodes
imports: ISO3166-2-SubdivisionCodes-US
imports: LanguageRepresentation
version IRI: course-recommender-individuals

PLACEHOLDER-ADVISOR-URI
type: NamedIndividual
type: Advisor
has name: Placeholder advisor name

PLACEHOLDER-DEGREE-1
type: NamedIndividual
type: Degree
has name: placeholder BS
has planned major: PLACEHOLDER-MAJOR-1

PLACEHOLDER-MAJOR-1
type: NamedIndividual
type: Major
has department: dpt0026
has name: placeholder computer science major

Rensselaer Polytechnic Institute
type: NamedIndividual
type: University
definition: globally recognized university situated on 275 acres in Troy NY, offering 746 labs, studios, and technology spaces used for research
has identity: Rensselaer Polytechnic Institute as legal entity
abbreviation: RPI
abbreviation: Rensselaer
adapted from: https://rpi.edu/about/

Rensselaer Polytechnic Institute address
type: NamedIndividual
type: PhysicalAddress
definition: physical street address for Rensselaer Polytechnic Institute
has address line1: 110 8th Street
has postal code: 12180-3522
has city name: Troy
has country: UnitedStates
has subdivision: NewYork

Rensselaer Polytechnic Institute as legal entity
type: NamedIndividual
type: LegalEntity
definition: legal entity that is Rensselaer Polytechnic Institute
has headquarters address: Rensselaer Polytechnic Institute address

ccr000001
type: NamedIndividual
type: CourseCodeRestriction
has valid department code tag: ARTS
has valid department code tag: COGS
has valid department code tag: COMM
has valid department code tag: ECON
has valid department code tag: IHSS
has valid department code tag: LANG
has valid department code tag: LITR
has valid department code tag: PHIL
has valid department code tag: PSYC
has valid department code tag: STSH
has valid department code tag: STSS
has valid department code tag: WRIT
has valid level max: 2000

ccr000002
type: NamedIndividual
type: CourseCodeRestriction
has valid department code tag: ARTS
has valid department code tag: COMM
has valid department code tag: IHSS
has valid department code tag: LANG
has valid department code tag: LITR
has valid department code tag: PHIL
has valid department code tag: STSH
has valid department code tag: WRIT

ccr000003
type: NamedIndividual
type: CourseCodeRestriction
has valid department code tag: COGS
has valid department code tag: ECON
has valid department code tag: IHSS
has valid department code tag: PSYC
has valid department code tag: STSS

ccr000004
type: NamedIndividual
type: CourseCodeRestriction
has valid department code tag: ARTS
has valid department code tag: COGS
has valid department code tag: COMM
has valid department code tag: ECON
has valid department code tag: IHSS
has valid department code tag: LANG
has valid department code tag: LITR
has valid department code tag: PHIL
has valid department code tag: PSYC
has valid department code tag: STSH
has valid department code tag: STSS
has valid department code tag: WRIT
has valid level min: 4000

ccr000005
type: NamedIndividual
type: CourseCodeRestriction
has special tag: communication intensive

ccr000006
type: NamedIndividual
type: CourseCodeRestriction
has valid department code tag: ARTS
has valid department code tag: COGS
has valid department code tag: COMM
has valid department code tag: ECON
has valid department code tag: IHSS
has valid department code tag: LANG
has valid department code tag: LITR
has valid department code tag: PHIL
has valid department code tag: PSYC
has valid department code tag: STSH
has valid department code tag: STSS
has valid department code tag: WRIT

ccr000007
type: NamedIndividual
type: CourseCodeRestriction
has valid course code tag: IHSS-1140
has valid course code tag: IHSS-1235
has valid course code tag: IHSS-1972

ccr000008
type: NamedIndividual
type: CourseCodeRestriction
has valid course code tag: COGS-2120

ccr000009
type: NamedIndividual
type: CourseCodeRestriction
has valid course code tag: COGS-4210
has valid course code tag: COGS-4410
has valid course code tag: COGS-4420
has valid course code tag: COGS-4640
has valid course code tag: COGS-4880
has valid course code tag: COGS-4960
has valid course code tag: PHIL-4960
has valid course code tag: PHIL-4961

COGS-2120
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000016
has credits: 4
has department: dpt0002
has description: This course is an introduction to the new and quickly growing field of cognitive science. Cognitive Science is a highly interdisciplinary field of study of mind at the intersection of philosophy, psychology, computer science, neuroscience, linguistics, and anthropology. This is a communication-intensive course.
has name: Introduction to Cognitive Science
has topic: placeholder for topic

crs000016
type: NamedIndividual
type: CourseCode
has department code: dptc0002
has level: 2120
has tag: COGS-2120

COGS-2340
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000021
has credits: 4
has department: dpt0002
has description: This course offers a survey of scientific and applied approaches to the study of human language, highlighting the endlessly surprising nature of this sophisticated mode of communication. A sampling of the topics to be covered: phonology, morphology, syntax, semantics, lexicography, psycholinguistics, and historical linguistics. Lecture course.
has name: Introduction to Linguistics
has topic: placeholder for topic

crs000021
type: NamedIndividual
type: CourseCode
has department code: dptc0002
has level: 2340
has tag: COGS-2340

COGS-4210
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000027
has credits: 4
has department: dpt0002
has description: Recent advances in Cognitive Science, Computer Science and Mathematics, have resulted in the ability to develop computer programs that implement Probabilistic Cognitive Models (PCMs). The cognitive models that this course covers are based on approximate Bayesian Inference implemented by Markov Chain Monte Carlo and Variational techniques that have made this approach tractable. The objective of this course is to enable the student to develop models of cognition in a Bayesian framework.
has name: Cognitive Modeling
has required prerequisite: CSCI-2300
has topic: placeholder for topic

crs000027
type: NamedIndividual
type: CourseCode
has department code: dptc0002
has level: 4210
has tag: COGS-4210

COGS-4330
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000030
has credits: 4
has department: dpt0002
has description: This survey course is intended as an introduction to Cognitive Neuroscience. The topics covered will focus on exploring the neural underpinnings for cognitive processes, such as sensation, language, attention, motor control, executive functions, social communication, emotions, consciousness, and learning/memory. Basic aspects of nervous system function and neuroanatomy, brain development/evolution, structural and functional imaging techniques, and other research methods used in Cognitive Neuroscience will be discussed.
has name: Introduction to Cognitive Neuroscience
has required prerequisite: COGS-2120
has topic: placeholder for topic

crs000030
type: NamedIndividual
type: CourseCode
has department code: dptc0002
has level: 4330
has tag: COGS-4330

COGS-4360
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000036
has credits: 4
has department: dpt0002
has description: This course is an introduction to the role of physiological mechanisms in behavioral processes. There will be detailed examination and discussion of the involvement of biological systems in feeding and drinking, sexual behavior, sleep and arousal, learning and memory, psychopathology and psychopharmacology.
has name: Behavioral Neuroscience
has topic: placeholder for topic

crs000036
type: NamedIndividual
type: CourseCode
has department code: dptc0002
has level: 4360
has tag: COGS-4360

COGS-4550
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000040
has credits: 4
has department: dpt0002
has topic: placeholder for topic

crs000040
type: NamedIndividual
type: CourseCode
has department code: dptc0002
has level: 4550
has tag: COGS-4550

COGS-4610
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000043
has credits: 4
has department: dpt0002
has description: This seminar course is a detailed examination of the mind-brain relationship, through study of the stress response. Stress is simply defined as any challenge to an individual's homeostasis or balance. This course will explore the neurobiological underpinnings of the stress response, with particular focus on how stressors can alter perception, affective and cognitive processing in the individual, which can in turn feedback to alter the general health of the individual (body and mind/brain).
has name: Stress and the Brain
has topic: placeholder for topic

crs000043
type: NamedIndividual
type: CourseCode
has department code: dptc0002
has level: 4610
has tag: COGS-4610

COGS-4960
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000046
has credits: 4
has department: dpt0002
has description: An advanced course concerned with selected topics in cognitive science.
has name: Topics in Cognitive Science
has topic: placeholder for topic

crs000046
type: NamedIndividual
type: CourseCode
has department code: dptc0002
has level: 4960
has tag: COGS-4960

COGS-4990
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000049
has credits: 4
has department: dpt0002
has description: Students conduct original scholarly projects: original research, theoretical or analytical reviews of the literature, or computer simulations. Students prepare written reports relating to this project, under the supervision of a faculty member. This is a communication-intensive course.
has name: Undergraduate Thesis
has topic: placeholder for topic

crs000049
type: NamedIndividual
type: CourseCode
has department code: dptc0002
has level: 4990
has tag: COGS-4990

COGS-6210
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000062
has credits: 4
has department: dpt0002
has description: This is a graduate level course that introduces the student to computational cognitive modeling. Cognitive modeling is the simulation of human cognitive, perceptual, and motor processes based on a cognitive architecture. The benefit of cognitive modeling is that it facilitates the testing of ideas about human processes through comparison of model data with empirical data. This course covers ACT-R, a symbolic architecture and LEABRA, a neural-level architecture.
has name: Cognitive Modeling I
has topic: placeholder for topic

crs000062
type: NamedIndividual
type: CourseCode
has department code: dptc0002
has level: 6210
has tag: COGS-6210

COGS-6960
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000065
has credits: 4
has department: dpt0002
has description: An advanced course concerned with selected topics in cognitive science.
has name: Topics in Cognitive Science
has topic: placeholder for topic

crs000065
type: NamedIndividual
type: CourseCode
has department code: dptc0002
has level: 6960
has tag: COGS-6960

COGS-6961
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000068
has credits: 2
has department: dpt0002
has topic: placeholder for topic

crs000068
type: NamedIndividual
type: CourseCode
has department code: dptc0002
has level: 6961
has tag: COGS-6961

COGS-6962
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000071
has credits: 4
has department: dpt0002
has topic: placeholder for topic

crs000071
type: NamedIndividual
type: CourseCode
has department code: dptc0002
has level: 6962
has tag: COGS-6962

COGS-6963
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000074
has credits: 4
has department: dpt0002
has topic: placeholder for topic

crs000074
type: NamedIndividual
type: CourseCode
has department code: dptc0002
has level: 6963
has tag: COGS-6963

COGS-6980
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000077
has credits: 1
has department: dpt0002
has description: Active participation in a master's-level project, under the supervision of a faculty adviser, leading to a master's project report. Grades S or U are assigned at the end of the semester. If recommended by the adviser, the master's project may be accepted by the Office of Graduate Education to be archived in the library.
has name: Master's Project
has topic: placeholder for topic

crs000077
type: NamedIndividual
type: CourseCode
has department code: dptc0002
has level: 6980
has tag: COGS-6980

COGS-6990
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000083
has credits: 1
has department: dpt0002
has description: Active participation in research, under the supervision of a faculty adviser, leading to a master's thesis. Grades of S or U are assigned by the adviser each term to reflect the student's research progress for the given semester. Once the thesis has been presentend, approved by the adviser, and accepted by the Office of Graduate Education, it will be archived in a standard format in the library.
has name: Master's Thesis
has topic: placeholder for topic

crs000083
type: NamedIndividual
type: CourseCode
has department code: dptc0002
has level: 6990
has tag: COGS-6990

COGS-9990
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000089
has credits: 1
has department: dpt0002
has description: Active participation in research, under the supervision of a faculty adviser, leading to a doctoral dissertation. Grades of S or U are assigned by the adviser each term to reflect the student's research progress for the given semester. Once the dissertation has been publicly defended, approved by the doctoral committee, and accepted by the Office of Graduate Education, it will be archived in a standard format in the library.
has name: Doctoral Thesis
has topic: placeholder for topic

crs000089
type: NamedIndividual
type: CourseCode
has department code: dptc0002
has level: 9990
has tag: COGS-9990

CSCI-1100
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000103
has credits: 4
has department: dpt0026
has description: An introduction to computer programming algorithm design and analysis. Additional topics include basic computer organization; internal representation of scalar and array data; use of top-down design and subprograms to tackle complex problems; abstract data types. Enrichment material as time allows. Interdisciplinary case studies, numerical and nonnumerical applications. Students who have passed CSCI 1200 cannot register for this course.
has name: Computer Science I
has topic: placeholder for topic

crs000103
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 1100
has tag: CSCI-1100

CSCI-1190
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000129
has credits: 1
has department: dpt0026
has description: This course teaches elementary programming concepts using the MATLAB environment for engineering students with little or no prior programming experience. Concepts include variables, looping, and function calls. Students cannot get credit for CSCI 1190 after earning credit for CSCI 1100 or any higher-level CSCI course.
has name: Beginning Programming for Engineers
has topic: placeholder for topic

crs000129
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 1190
has tag: CSCI-1190

CSCI-1200
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000139
has credits: 4
has department: dpt0026
has description: Programming concepts: functions, parameter passing, pointers, arrays, strings, structs, classes, templates. Mathematical tools: sets, functions, and relations, order notation, complexity of algorithms, proof by induction. Data structures and their representations: data abstraction and internal representation, sequences, trees, binary search trees, associative structures. Algorithms: searching and sorting, generic algorithms, iterative and recursive algorithms. Methods of testing correctness and measuring performance.
has name: Data Structures
has required prerequisite: CSCI-1100
has topic: placeholder for topic

crs000139
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 1200
has tag: CSCI-1200

CSCI-2200
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000189
has credits: 4
has department: dpt0026
has description: This course introduces important mathematical and theoretical tools for computer science, including topics from set theory, combinatorics, and probability theory, and then proceeds to automata theory, the Turing Machine model of computation, and notions of computational complexity. The course will emphasize formal reasoning and proof techniques.
has name: Foundations of Computer Science
has required prerequisite: CSCI-1200
has topic: placeholder for topic

crs000189
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 2200
has tag: CSCI-2200

CSCI-2300
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000206
has credits: 4
has department: dpt0026
has description: Data structures and algorithms, and the mathematical techniques necessary to design and analyze them. Basic data structures: lists, associative structures, trees. Mathematical techniques for designing algorithms and analyzing worst-case and expected-case algorithm efficiency. Advanced data structures: balanced trees, tries, heaps, priority queues, graphs. Searching, sorting. Algorithm design techniques: dynamic programming, greedy algorithms, divide-and-conquer, backtracking. Example graph, string, geometric, and numeric algorithms.
has name: Introduction to Algorithms
has required prerequisite: CSCI-1200
has required prerequisite: CSCI-2200
has topic: placeholder for topic

crs000206
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 2300
has tag: CSCI-2300

CSCI-2500
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000232
has credits: 4
has department: dpt0026
has description: Introduction to computer organization, assembler language, and operating systems. Computer systems organization: processors, memory, I/O. Digital logic: gates, Boolean algebra, digital logic circuits, memory, buses. Microprogramming. Machine level: instruction formats, addressing modes, instruction types, flow of control. Operating systems: virtual memory, virtual I/O instructions, processes, interprocess communication. Numeric representation. Assembler language: the assembly process, macros, linking, loading. Advanced architectures: RISC architectures, parallel architectures.
has name: Computer Organization
has required prerequisite: CSCI-1200
has topic: placeholder for topic

crs000232
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 2500
has tag: CSCI-2500

CSCI-2600
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000252
has credits: 4
has department: dpt0026
has description: A study of important concepts in software design, implementation, and testing. Topics include specification, abstraction with classes, design principles and patterns, testing, refactoring, the software development process, GUI and event-driven programming, and cloud-based programming. The course also introduces implementation and testing tools, including IDEs, revision control systems, and other frameworks. The overarching goal of the course is for students to learn how to write correct and maintainable software.
has name: Principles of Software
has required prerequisite: CSCI-1200
has required prerequisite: CSCI-2200
has topic: placeholder for topic

crs000252
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 2600
has tag: CSCI-2600

CSCI-2960
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000256
has credits: 1
has department: dpt0026
has topic: placeholder for topic

crs000256
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 2960
has tag: CSCI-2960

CSCI-4020
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000269
has credits: 4
has department: dpt0026
has description: This course presents fundamental ideas and techniques of modern algorithm design and analysis. After completing this course, students should be able to formally analyze and design efficient algorithms for a variety of computational problems. Topics covered include Greedy Algorithms, Dynamic Programming, Network Flow, NP-Completeness, Linear Programming, Network Algorithms, as well as probabilistic and approximate algorithms.
has name: Design and Analysis of Algorithms
has required prerequisite: CSCI-2300
has topic: placeholder for topic

crs000269
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 4020
has tag: CSCI-4020

CSCI-4150
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000272
has credits: 4
has department: dpt0026
has description: Topics and techniques of artificial intelligence using the language LISP. Topics include search, knowledge representation, expert systems, theorem proving, natural language interfaces, learning, game playing, and computer vision. Techniques include pattern matching, data-driven programming, substitution rules, frames, heuristic search, transition networks, neural networks, and evolutionary computation. Development of programming proficiency in LISP is emphasized.
has name: Introduction to Artificial Intelligence
has required prerequisite: CSCI-2300
has topic: placeholder for topic

crs000272
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 4150
has tag: CSCI-4150

CSCI-4210
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000275
has credits: 4
has department: dpt0026
has description: Discussion of various aspects of computer operating systems design and implementation. Topics include I/O programming, concurrent processes and synchronization problems, process management and scheduling of processes, virtual memory management, device management, file systems, deadlock problems, system calls, and interprocess communication. Programming projects are required.
has name: Operating Systems
has required prerequisite: CSCI-2300
has required prerequisite: CSCI-2500
has topic: placeholder for topic

crs000275
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 4210
has tag: CSCI-4210

CSCI-4260
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000278
has credits: 4
has department: dpt0026
has description: Fundamental concepts and methods of graph theory and its applications to computing and the social and natural sciences. Topics include graphs as models, representation of graphs, trees, distances, matchings, connectivity, flows in networks, graph colorings, Hamiltonian cycles, traveling salesman problem, planarity. All concepts, methods, and applications are presented through a sequence of exercises and problems, many of which are done with the help of novel software systems for combinatorial computing.
has name: Graph Theory
has required prerequisite: CSCI-1100
has required prerequisite: CSCI-2200
has topic: placeholder for topic

crs000278
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 4260
has tag: CSCI-4260

CSCI-4320
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000281
has credits: 4
has department: dpt0026
has description: Techniques and methods for parallel programming: models of parallel machines and programs, efficiency and complexity of parallel algorithms. Paradigms of parallel programming and corresponding extensions to sequential programming languages. Overview of parallel languages and coordination languages and models; programming on networks of workstations. Basic parallel algorithms: elementary computation, matrix multiplication, sorting; sample scientific application.
has name: Parallel Programming
has required prerequisite: CSCI-2300
has required prerequisite: CSCI-2500
has topic: placeholder for topic

crs000281
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 4320
has tag: CSCI-4320

CSCI-4380
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000284
has credits: 4
has department: dpt0026
has description: Discussion of the state of practice in modern database systems, with an emphasis on relational systems. Topics include database design, database system architecture, SQL, normalization techniques, storage structures, query processing, concurrency control, recovery, security, and new directions such as object-oriented and distributed database systems. Students gain hands-on experience with commercial database systems and interface building tools. Programming projects are required.
has name: Database Systems
has required prerequisite: CSCI-2300
has topic: placeholder for topic

crs000284
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 4380
has tag: CSCI-4380

CSCI-4400
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000287
has credits: 3
has department: dpt0026
has description: Informatics covers a broad range of disciplines addressing challenges in the explosion of data and information resources. Xinformatics provides commonality for implementations in specific disciplines, e.g. X=astro, geo. Informatics' theoretical bases are information and computer science, cognitive science, social science, library science, aggregating these studies and adding the practice of information processing, and the engineering of information systems. This course grounds the material that students will learn in discipline areas by coursework and project assignments.
has name: X-informatics
has required prerequisite: CSCI-1200
has topic: placeholder for topic

crs000287
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 4400
has tag: CSCI-4400

CSCI-4440
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000290
has credits: 4
has department: dpt0026
has description: Software system design methodology emphasizing use of object oriented modeling of application domains and of software systems and emphasizing the roles of written and oral communication in software engineering. Project management and software testing. Individual and team projects include specification, software architecture, user interfaces, and documentation of the phases of a project. This is a communication-intensive course.
has name: Software Design and Documentation
has required prerequisite: CSCI-2300
has topic: placeholder for topic

crs000290
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 4440
has tag: CSCI-4440

CSCI-4450
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000295
has credits: 4
has department: dpt0026
has description: The goal of this course is to introduce students to program analysis and its many applications in software engineering, particularly in improving software quality and software productivity. Concretely, students who successfully complete this course should be able to: (1) understand and apply program analysis techniques, such as dataflow analysis and type-based analysis; (2) implement program analysis; (3) understand and apply software testing techniques, such as black-box testing and white-box testing; and (4) understand and apply refactoring techniques.
has name: Principles of Program Analysis
has required prerequisite: CSCI-4430
has topic: placeholder for topic

crs000295
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 4450
has tag: CSCI-4450

CSCI-4540
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000298
has credits: 4
has department: dpt0026
has description: This course follows Game Development I. Students work in interdisciplinary teams to create one large-scale 3D game, working from concept to public release. Projects may include games, educational games, serious games and simulations, and interactive artworks, and will focus on creative design, technical execution, and use of game design principles. The course builds on skills and knowledge in previous courses in the GSAS core, including game design, game mechanics, game programming, art, and narrative.
has name: Game Development II
has topic: placeholder for topic

crs000298
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 4540
has tag: CSCI-4540

CSCI-4550
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000302
has credits: 4
has department: dpt0026
has description: Visualizing data is a key step in understanding many problems. This course is designed to introduce students to methods of visualizing many different types of data, such as images, three-dimensional surfaces, flow fields, and medical data. Both existing visualization software and program custom visualizations using C++ and OpenGL will be used. Course activities include discussion of recent and classic research papers, weekly homework assignments, in-class critiques of visualization artifacts, and a final project to explore creative uses of these techniques. This is a communication-intensive course.
has name: Interactive Visualization
has required prerequisite: CSCI-2300
has required prerequisite: CSCI-2600
has topic: placeholder for topic

crs000302
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 4550
has tag: CSCI-4550

CSCI-4800
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000305
has credits: 4
has department: dpt0026
has description: A survey of numerical methods for scientific and engineering problems. Topics include numerical solution of linear and nonlinear algebraic equations, interpolation and least squares approximations, numerical integration and differentiation, eigenvalue problems, and an introduction to the numerical solution of ordinary differential equations. Emphasis is placed on efficient computational procedures including the use of library and student written procedures using high-level software such as MATLAB.
has name: Numerical Computing
has required prerequisite: CSCI-1100
has topic: placeholder for topic

crs000305
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 4800
has tag: CSCI-4800

CSCI-4820
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000309
has credits: 4
has department: dpt0026
has description: Derivation, analysis, and use of computational procedures for solving differential equations. Topics covered include ordinary differential equations (both initial value and boundary value problems) and partial differential equations. Runge-Kutta and multistep methods for initial value problems. Finite difference methods for partial differential equations including techniques for heat conduction, wave propagation, and potential problems. Basic convergence and stability theory.
has name: Introduction to Numerical Methods for Differential Equations
has required prerequisite: CSCI-4800
has topic: placeholder for topic

crs000309
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 4820
has tag: CSCI-4820

CSCI-4961
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000312
has credits: 4
has department: dpt0026
has topic: placeholder for topic

crs000312
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 4961
has tag: CSCI-4961

CSCI-4962
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000315
has credits: 4
has department: dpt0026
has topic: placeholder for topic

crs000315
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 4962
has tag: CSCI-4962

CSCI-4964
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000318
has credits: 4
has department: dpt0026
has topic: placeholder for topic

crs000318
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 4964
has tag: CSCI-4964

CSCI-4967
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000321
has credits: 4
has department: dpt0026
has topic: placeholder for topic

crs000321
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 4967
has tag: CSCI-4967

CSCI-4969
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000324
has credits: 4
has department: dpt0026
has topic: placeholder for topic

crs000324
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 4969
has tag: CSCI-4969

CSCI-4976
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000327
has credits: 4
has department: dpt0026
has topic: placeholder for topic

crs000327
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 4976
has tag: CSCI-4976

CSCI-6360
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000330
has credits: 4
has department: dpt0026
has description: A survey of fundamental issues in design of efficient programs for parallel computers. The topics discussed include models of parallel machines and programs, efficiency of parallel algorithms, programming styles for shared memory, message passing, data parallelism, and using MPI in scientific parallel programs. Parallel programming project required.
has name: Parallel Computing
has required prerequisite: CSCI-4210
has topic: placeholder for topic

crs000330
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 6360
has tag: CSCI-6360

CSCI-6400
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000333
has credits: 3
has department: dpt0026
has description: Informatics covers a broad range of disciplines addressing challenges in the explosion of data and information resources. Xinformatics provides commonality for implementations in specific disciplines, e.g. X=astro, geo. Informatics' theoretical bases are information and computer science, cognitive science, social science, library science, aggregating these studies and adding the practice of information processing, and the engineering of information systems. This course grounds the material that students will learn in discipline areas by coursework and project assignments.
has name: X-informatics
has required prerequisite: CSCI-1200
has topic: placeholder for topic

crs000333
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 6400
has tag: CSCI-6400

CSCI-6450
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000336
has credits: 4
has department: dpt0026
has description: The goal of this course is to introduce students to program analysis and its many applications in software engineering, particularly in improving software quality and software productivity. Concretely, students who successfully complete this course should be able to: (1) understand and apply program analysis techniques, such as dataflow analysis and type-based analysis; (2) implement program analysis; (3) understand and apply software testing techniques, such as black-box testing and white-box testing; and (4) understand and apply refactoring techniques.
has name: Principles of Program Analysis
has required prerequisite: CSCI-4430
has topic: placeholder for topic

crs000336
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 6450
has tag: CSCI-6450

CSCI-6550
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000339
has credits: 4
has department: dpt0026
has description: Visualizing data is a key step in understanding many problems. This course is designed to introduce students to methods of visualizing many different types of data, such as images, three-dimensional surfaces, flow fields, and medical data. Both existing visualization software and program custom visualizations using C++ and OpenGL will be used. Course activities include discussion of recent and classic research papers, weekly homework assignments, in-class critiques of visualization artifacts, and a final project to explore creative uses of these techniques. This is a communication-intensive course.
has name: Interactive Visualization
has required prerequisite: CSCI-2300
has required prerequisite: CSCI-2600
has topic: placeholder for topic

crs000339
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 6550
has tag: CSCI-6550

CSCI-6840
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000342
has credits: 4
has department: dpt0026
has description: Numerical methods and analysis for linear and nonlinear PDEs with applications from heat conduction, wave propagation, solid and fluid mechanics, and other areas. Basic concepts of stability and convergence (Lax equivalence theorem, CFL condition, energy methods). Methods for parabolic problems (finite differences, method of lines, ADI, operator splitting), methods for hyperbolic problems (vector systems and characteristics, dissipation and dispersion, shocks capturing and tracking schemes), methods for elliptic problems (finite difference and finite volume methods).
has name: Numerical Solution of Partial Differential Equations
has required prerequisite: CSCI-4800
has topic: placeholder for topic

crs000342
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 6840
has tag: CSCI-6840

CSCI-6900
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000345
has credits: 0
has department: dpt0026
has description: Presentation of current developments in computer science. Reports by students.
has name: Computer Science Seminar
has topic: placeholder for topic

crs000345
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 6900
has tag: CSCI-6900

CSCI-6960
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000348
has credits: 0
has department: dpt0026
has name: Topics in Computer Science
has topic: placeholder for topic

crs000348
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 6960
has tag: CSCI-6960

CSCI-6961
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000351
has credits: 3
has department: dpt0026
has topic: placeholder for topic

crs000351
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 6961
has tag: CSCI-6961

CSCI-6962
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000354
has credits: 4
has department: dpt0026
has topic: placeholder for topic

crs000354
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 6962
has tag: CSCI-6962

CSCI-6964
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000357
has credits: 4
has department: dpt0026
has topic: placeholder for topic

crs000357
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 6964
has tag: CSCI-6964

CSCI-6967
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000360
has credits: 4
has department: dpt0026
has topic: placeholder for topic

crs000360
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 6967
has tag: CSCI-6967

CSCI-6969
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000363
has credits: 4
has department: dpt0026
has topic: placeholder for topic

crs000363
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 6969
has tag: CSCI-6969

CSCI-6970
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000366
has credits: 1
has department: dpt0026
has description: Active participation in a semester-long project, under the supervision of a faculty adviser. A Professional Project often serves as a culminating experience for a Professional Master's program but, with departmental or school approval, can be used to fulfill other program requirements. With approval, students may register for more than one Professional Project. Professional Projects must result in documentation established by each department or school, but are not submitted to the Office of Graduate Education and are not archived in the library. Grades of A, B, C, or F are assigned by the faculty adviser at the end of the semester. If not completed on time, a formal Incomplete grade may be assigned by the faculty adviser, listing the work remaining to be completed and the time limit for completing this work.
has name: Professional Project
has topic: placeholder for topic

crs000366
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 6970
has tag: CSCI-6970

CSCI-6980
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000369
has credits: 1
has department: dpt0026
has description: Active participation in a master's-level project, under the supervision of a faculty adviser, leading to a master's project report. Grades S or U are assigned at the end of the semester. If recommended by the adviser, the master's project may be accepted by the Office of Graduate Education to be archived in the library.
has name: Master's Project
has topic: placeholder for topic

crs000369
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 6980
has tag: CSCI-6980

CSCI-6990
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000399
has credits: 1
has department: dpt0026
has description: Active participation in research, under the supervision of a faculty adviser, leading to a master's thesis. Grades of S or U are assigned by the adviser each term to reflect the student's research progress for the given semester. Once the thesis has been presentend, approved by the adviser, and accepted by the Office of Graduate Education, it will be archived in a standard format in the library.
has name: Master's Thesis
has topic: placeholder for topic

crs000399
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 6990
has tag: CSCI-6990

CSCI-9990
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000433
has credits: 1
has department: dpt0026
has description: Active participation in research, under the supervision of a faculty adviser, leading to a doctoral dissertation. Grades of IP are assigned until the dissertation has been publicly defended, approved by the doctoral committee, and accepted by the Office of Graduate Education to be archived in a standard format in the library. Grades will then be listed as S.
has name: Dissertation
has topic: placeholder for topic

crs000433
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 9990
has tag: CSCI-9990

COGS-4410
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000472
has credits: 4
has department: dpt0002
has description: Research in Cognitive Science and Artificial Intelligence (AI) is driven by data. Researchers in these fields collect, manipulate, model and analyze data generated by real-world processes. Since the amount of data available has grown exponentially, the ability to automate these tasks through computer programs is essential. Specifically, probabilistic and statistical computing are needed to learn from the data. The objectives of this course are for the student to perform exploratory data analysis and to acquire the basics of statistical and machine learning in order to model real-world datasets.
has name: Programming for Cognitive Science and Artificial Intelligence
has required prerequisite: CSCI-2300
has topic: placeholder for topic

crs000472
type: NamedIndividual
type: CourseCode
has department code: dptc0002
has level: 4410
has tag: COGS-4410

COGS-4420
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000476
has credits: 4
has department: dpt0002
has description: This course introduces students to basic concepts and methods of artificial intelligence and their applications in computer games. The topics include decision making, movement, path finding, and AI for human-like characters. This course will take the form of a combination of lectures, presentations by students, class discussions, and independent study.
has name: Game AI
has required prerequisite: CSCI-2300
has topic: placeholder for topic

crs000476
type: NamedIndividual
type: CourseCode
has department code: dptc0002
has level: 4420
has tag: COGS-4420

COGS-4430
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000479
has credits: 4
has department: dpt0002
has description: Digital gaming is one of the most rapidly developing fields. The effort required for developing games is not trivial. To make a game fun to play, the design of the game levels and/or the AI-driven opponents need to be intelligent and adaptive to the players' strategies and skills. In this course, students will learn and explore using machine learning techniques to automate the design process of digital games. The course will cover basic and advanced topics in Artificial Intelligence and Learning, such as Decision Trees, Neural Networks, Genetic Algorithms, and Reinforcement Learning. Students will gain hands-on experience in applying these techniques in computer games. The course will also introduce psychological theories and studies about people's decision-making and emotional processes and how they are related to the players' experience in games. This course will take the form of a combination of lectures, presentations by students, class discussions, and independent study.
has name: Learning and Advanced Game AI
has required prerequisite: COGS-4420
has topic: placeholder for topic

crs000479
type: NamedIndividual
type: CourseCode
has department code: dptc0002
has level: 4430
has tag: COGS-4430

COGS-4440
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000482
has credits: 4
has department: dpt0002
has description: "Sensibilities"--a special ART_X@Rensselaer (Art Across the Curriculum) seminar--draws from the tremendous resource of EMPAC to inspire students to cultivate writing skills through the cross-disciplinary theme of the senses/perception. During the semester students will have opportunities to observe unique art/science presentations and performances in an intimate setting at EMPAC, providing rich experiences for discussions and writing. Classes include reading science and art texts, as well as writing workshops to develop authorial voice and experimentation.
has name: Sensibilities
has topic: placeholder for topic

crs000482
type: NamedIndividual
type: CourseCode
has department code: dptc0002
has level: 4440
has tag: COGS-4440

COGS-4560
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000485
has credits: 4
has department: dpt0002
has description: This course will explore the different strategies used by different languages to fulfill the same needs of human communication. A sampling of topics: quickly learning the basics of a new language using linguistic principles; cross-linguistic knowledge elicitation and engineering; principles of generative grammar; space, time, agency, and other linguistic phenomena viewed cross-linguistically.
has name: Cross-linguistic Perspectives
has required prerequisite: COGS-2340
has topic: placeholder for topic

crs000485
type: NamedIndividual
type: CourseCode
has department code: dptc0002
has level: 4560
has tag: COGS-4560

COGS-4961
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000489
has credits: 4
has department: dpt0002
has topic: placeholder for topic

crs000489
type: NamedIndividual
type: CourseCode
has department code: dptc0002
has level: 4961
has tag: COGS-4961

COGS-4962
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000492
has credits: 4
has department: dpt0002
has topic: placeholder for topic

crs000492
type: NamedIndividual
type: CourseCode
has department code: dptc0002
has level: 4962
has tag: COGS-4962

COGS-6410
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000498
has credits: 4
has department: dpt0002
has description: This course is a graduate course that teaches Cognitive Science and Artificial Intelligence concepts by enabling the student to develop and understand computer programs that implement them. It covers data collection and analysis, task environments, natural language, cognitive architectures, and learning. Some previous programming experience is very beneficial but not required.
has name: Programming for Cognitive Science and Artificial Intelligence
has topic: placeholder for topic

crs000498
type: NamedIndividual
type: CourseCode
has department code: dptc0002
has level: 6410
has tag: COGS-6410

COGS-6430
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000502
has credits: 4
has department: dpt0002
has description: Digital gaming is one of the most rapidly developing fields. The effort required for developing games is not trivial. To make a game fun to play, the design of the game levels and/or the AI-driven opponents need to be intelligent and adaptive to the players' strategies and skills. In this course, students will learn and explore using machine learning techniques to automate the design process of digital games. The course will cover basic and advanced topics in Artificial Intelligence and Learning, such as Decision Trees, Neural Networks, Genetic Algorithms, and Reinforcement Learning. Students will gain hands-on experience in applying these techniques in computer games. The course will also introduce psychological theories and studies about people's decision-making and emotional processes and how they are related to the players' experience in games. This course will take the form of a combination of lectures, presentations by students, class discussions, and independent study.
has name: Learning and Advanced Game AI
has topic: placeholder for topic

crs000502
type: NamedIndividual
type: CourseCode
has department code: dptc0002
has level: 6430
has tag: COGS-6430

COGS-6560
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000505
has credits: 3
has department: dpt0002
has description: This course will explore the different strategies used by different languages to fulfill the same needs of human communication. A sampling of topics: quickly learning the basics of a new language using linguistic principles; cross-linguistic knowledge elicitation and engineering; principles of generative grammar; space, time, agency, and other linguistic phenomena viewed cross-linguistically.
has name: Cross-linguistic Perspectives
has topic: placeholder for topic

crs000505
type: NamedIndividual
type: CourseCode
has department code: dptc0002
has level: 6560
has tag: COGS-6560

COGS-6964
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000511
has credits: 4
has department: dpt0002
has topic: placeholder for topic

crs000511
type: NamedIndividual
type: CourseCode
has department code: dptc0002
has level: 6964
has tag: COGS-6964

COGS-6968
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000514
has credits: 2
has department: dpt0002
has topic: placeholder for topic

crs000514
type: NamedIndividual
type: CourseCode
has department code: dptc0002
has level: 6968
has tag: COGS-6968

CSCI-2961
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000683
has credits: 1
has department: dpt0026
has topic: placeholder for topic

crs000683
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 2961
has tag: CSCI-2961

CSCI-4100
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000689
has credits: 4
has department: dpt0026
has description: Introduction to the theory, algorithms, and applications of machine learning (supervised, reinforcement, and unsupervised) from data: What is learning? Is learning feasible? How can we do it? How can we do it well? The course offers a mix of theory, technique, and application with additional selected topics chosen from Pattern Recognition, Decision Trees, Neural Networks, RBF's, Bayesian Learning, PAC Learning, Support Vector Machines, Gaussian processes, and Hidden Markov Models.
has name: Machine Learning from Data
has required prerequisite: CSCI-2300
has topic: placeholder for topic

crs000689
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 4100
has tag: CSCI-4100

CSCI-4220
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000692
has credits: 4
has department: dpt0026
has description: Programming with an overview of the principles of computer networks, including a detailed look at the OSI reference model and various popular network protocol suites. Concentration on Unix interprocess communication (IPC), network programming using TCP and UDP, as well as client-side and mobile programming. Programming projects are required.
has name: Network Programming
has required prerequisite: CSCI-2300
has required prerequisite: CSCI-2500
has topic: placeholder for topic

crs000692
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 4220
has tag: CSCI-4220

CSCI-4250
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000695
has credits: 4
has department: dpt0026
has description: This course will offer an introduction to network science and a review of current research in this area. Classes will interchangeably present chapters from the textbook and related current research. The emphasis will be on the mathematical background of network science: graphs and networks; random networks and various types of scale-free networks; network properties such as assortativity, mobility, robustness, social networks, and communities; and dynamics of spreading in networks.
has name: Frontiers of Network Science
has required prerequisite: CSCI-2300
has topic: placeholder for topic

crs000695
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 4250
has tag: CSCI-4250

CSCI-4310
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000698
has credits: 4
has department: dpt0026
has description: This course introduces Linux kernel programming basics and starts by examining how Berkeley sockets bridge the user-kernel gap. The remainder of the course is spent looking into transport layer (e.g., TCP) and network layer (e.g., IP) implementations. Students do both individual and group programming projects. In addition to coding, there are detailed write-ups and peer reviews in this course. This is a communication-intensive course.
has name: Networking in the Linux Kernel
has required prerequisite: CSCI-4210
has topic: placeholder for topic

crs000698
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 4310
has tag: CSCI-4310

CSCI-4340
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000701
has credits: 4
has department: dpt0026
has description: This course provides an introduction to ontologies, their uses, and an overview of their application in semantically enabled systems. Ontologies encode term meanings and are used to improve communication and enable computer programs to function more effectively. Class participants learn how to use ontologies in Web-based applications and evaluate ontologies for reuse. Participants read relevant papers, learn how to critically review ontology papers and ontologies, and participate in group project(s) designing, using, and evaluating ontologies.
has name: Ontologies
has required prerequisite: CSCI-2300
has topic: placeholder for topic

crs000701
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 4340
has tag: CSCI-4340

CSCI-4350
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000704
has credits: 3
has department: dpt0026
has description: Data science is advancing the inductive conduct of science and is driven by the greater volumes, complexity, and heterogeneity of data being made available over the Internet. It combines aspects of data management, library science, computer science, and physical science. It is changing the way all of these disciplines do both their individual and collaborative work. Key methodologies in application areas based on real research experience are taught.
has name: Data Science
has required prerequisite: CSCI-1200
has required prerequisite: CSCI-4380
has topic: placeholder for topic

crs000704
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 4350
has tag: CSCI-4350

CSCI-4370
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000707
has credits: 4
has department: dpt0026
has description: Data and Society provides a broad overview of how society is leveraging and responding to the social, organizational, policy, and technical opportunities and challenges of a data-driven world. Course themes focus on various aspects of the data ecosystem, data and innovation, and data and the broader community. Assignments build writing, presentation, and critical thinking, and assessment skills, all of which are important for professional success. This is a communication-intensive course.
has name: Data and Society
has required prerequisite: CSCI-4350
has topic: placeholder for topic

crs000707
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 4370
has tag: CSCI-4370

CSCI-4390
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000711
has credits: 4
has department: dpt0026
has description: This course will provide an introductory survey of the main topics in data mining and knowledge discovery in databases (KDD), including: classification, clustering, association rules, sequence mining, similarity search, deviation detection, and so on. Emphasis will be on the algorithmic and system issues in KDD, as well as on applications such as Web mining, multimedia mining, bioinformatics, geographical information systems, etc.
has name: Data Mining
has required prerequisite: CSCI-2300
has topic: placeholder for topic

crs000711
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 4390
has tag: CSCI-4390

CSCI-4430
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000714
has credits: 4
has department: dpt0026
has description: This course is a study of the important concepts found in current programming languages. Topics include language processing (lexical analysis, parsing, type-checking, interpretation and compilation, run-time environment), the role of abstraction (data abstraction and control abstraction), programming paradigms (procedural, functional, object-oriented, logic-oriented, generic), and formal language definition.
has name: Programming Languages
has required prerequisite: CSCI-2300
has required prerequisite: CSCI-2600
has topic: placeholder for topic

crs000714
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 4430
has tag: CSCI-4430

CSCI-4460
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000720
has credits: 4
has department: dpt0026
has description: This course focuses on software development techniques in support of large-scale software projects and maintenance. Specific topics include various programming paradigms and techniques, approaches to testing and automation, debugging, refactoring, and inheriting code. Individual and team assignments are required, including programming assignments. Project topics include text processing, building a search engine, and the like. This is a communication-intensive course.
has name: Large-Scale Programming and Testing
has required prerequisite: CSCI-2300
has topic: placeholder for topic

crs000720
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type: CourseCode
has department code: dptc0026
has level: 4460
has tag: CSCI-4460

CSCI-4480
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type: Course
source: http://catalog.rpi.edu/
has course code: crs000724
has credits: 3
has department: dpt0026
has description: A survey of the fundamental issues necessary for the design, analysis, control, and implementation of robotic systems. The mathematical description of robot manipulators in terms of kinematics and dynamics. Hardware components of a typical robot arm. Path following, control, and sensing. Examples of several currently available manipulators.
has name: Robotics I
has topic: placeholder for topic

crs000724
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 4480
has tag: CSCI-4480

CSCI-4510
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000728
has credits: 4
has department: dpt0026
has description: This course explores the principles of distributed systems, emphasizing fundamental issues underlying the design of such systems: communication, coordination, synchronization, and fault-tolerance. Key algorithms and theoretical results will be studied and students will explore how these foundations play out in modern systems and applications.
has name: Distributed Systems and Algorithms
has required prerequisite: CSCI-4210
has topic: placeholder for topic

crs000728
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type: CourseCode
has department code: dptc0026
has level: 4510
has tag: CSCI-4510

CSCI-4960
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000733
has credits: 3
has department: dpt0026
has name: Topics in Computer Science
has topic: placeholder for topic

crs000733
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type: CourseCode
has department code: dptc0026
has level: 4960
has tag: CSCI-4960

CSCI-4966
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type: Course
source: http://catalog.rpi.edu/
has course code: crs000739
has credits: 4
has department: dpt0026
has topic: placeholder for topic

crs000739
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type: CourseCode
has department code: dptc0026
has level: 4966
has tag: CSCI-4966

CSCI-4968
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type: Course
source: http://catalog.rpi.edu/
has course code: crs000744
has credits: 4
has department: dpt0026
has topic: placeholder for topic

crs000744
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type: CourseCode
has department code: dptc0026
has level: 4968
has tag: CSCI-4968

CSCI-4970
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type: Course
source: http://catalog.rpi.edu/
has course code: crs000748
has credits: 4
has department: dpt0026
has topic: placeholder for topic

crs000748
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type: CourseCode
has department code: dptc0026
has level: 4970
has tag: CSCI-4970

CSCI-6100
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type: Course
source: http://catalog.rpi.edu/
has course code: crs000751
has credits: 4
has department: dpt0026
has description: Introduction to the theory, algorithms, and applications of machine learning (supervised, reinforcement, and unsupervised) from data: What is learning? Is learning feasible? How can it be done? How can it be done well? The course offers a mix of theory, technique, and application with additional selected topics chosen from Pattern Recognition, Decision Trees, Neural Networks, RBF's, Bayesian Learning, PAC Learning, Support Vector Machines, Gaussian processes, and Hidden Markov Models.
has name: Machine Learning from Data
has required prerequisite: CSCI-2300
has topic: placeholder for topic

crs000751
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type: CourseCode
has department code: dptc0026
has level: 6100
has tag: CSCI-6100

CSCI-6250
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type: Course
source: http://catalog.rpi.edu/
has course code: crs000754
has credits: 4
has department: dpt0026
has description: This course will offer an introduction to network science and a review of current research in this area. Classes will interchangeably present chapters from the textbook and related current research. The emphasis will be on the mathematical background of network science: graphs and networks; random networks and various types of scale-free networks; network properties such as assortativity, mobility, robustness, social networks, and communities; and dynamics of spreading in networks.
has name: Frontiers of Network Science
has required prerequisite: CSCI-2300
has topic: placeholder for topic

crs000754
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type: CourseCode
has department code: dptc0026
has level: 6250
has tag: CSCI-6250

CSCI-6310
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type: Course
source: http://catalog.rpi.edu/
has course code: crs000757
has credits: 4
has department: dpt0026
has description: This course introduces Linux kernel programming basics and starts by examining how Berkeley sockets bridge the user-kernel gap. The remainder of the course is spent looking into transport layer (e.g., TCP) and network layer (e.g., IP) implementations. Students do both individual and group programming projects. In addition to coding, there are detailed write-ups and peer reviews in this course.
has name: Networking in the Linux Kernel
has required prerequisite: CSCI-4210
has topic: placeholder for topic

crs000757
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type: CourseCode
has department code: dptc0026
has level: 6310
has tag: CSCI-6310

CSCI-6340
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type: Course
source: http://catalog.rpi.edu/
has course code: crs000760
has credits: 4
has department: dpt0026
has description: This course provides an introduction to ontologies, their uses, and an overview of their application in semantically enabled systems. Ontologies encode term meanings and are used to improve communication and enable computer programs to function more effectively. Class participants learn how to use ontologies in web-based applications and evaluate ontologies for reuse. Participants read relevant papers, learn how to critically review ontology papers and ontologies, and participate in group project(s) designing, using, and evaluating ontologies.
has name: Ontologies
has required prerequisite: CSCI-2300
has topic: placeholder for topic

crs000760
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type: CourseCode
has department code: dptc0026
has level: 6340
has tag: CSCI-6340

CSCI-6350
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type: Course
source: http://catalog.rpi.edu/
has course code: crs000763
has credits: 3
has department: dpt0026
has description: Data science is advancing the inductive conduct of science and is driven by the greater volumes, complexity, and heterogeneity of data being made available over the Internet. It combines aspects of data management, library science, computer science, and physical science. It is changing the way all of these disciplines do both their individual and collaborative work. Key methodologies in application areas based on real research experience are taught.
has name: Data Science
has required prerequisite: CSCI-1200
has required prerequisite: CSCI-4380
has topic: placeholder for topic

crs000763
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type: CourseCode
has department code: dptc0026
has level: 6350
has tag: CSCI-6350

CSCI-6390
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type: Course
source: http://catalog.rpi.edu/
has course code: crs000766
has credits: 4
has department: dpt0026
has description: This course will provide an introductory survey of the main topics in data mining and knowledge discovery in databases (KDD), including: classification, clustering, association rules, sequence mining, similarity search, deviation detection, and so on. Emphasis will be on the algorithmic and system issues in KDD, as well as on applications such as Web mining, multimedia mining, bioinformatics, geographical information systems, etc.
has name: Data Mining
has required prerequisite: CSCI-2300
has topic: placeholder for topic

crs000766
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type: CourseCode
has department code: dptc0026
has level: 6390
has tag: CSCI-6390

CSCI-6460
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type: Course
source: http://catalog.rpi.edu/
has course code: crs000769
has credits: 4
has department: dpt0026
has description: This course focuses on software development techniques in support of large-scale software projects and maintenance. Specific topics include various programming paradigms and techniques, approaches to testing and automation, debugging, refactoring, and inheriting code. Individual and team assignments are required, including programming assignments. Project topics include text processing, building a search engine, and the like.
has name: Large-Scale Programming and Testing
has required prerequisite: CSCI-2300
has topic: placeholder for topic

crs000769
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type: CourseCode
has department code: dptc0026
has level: 6460
has tag: CSCI-6460

CSCI-6510
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type: Course
source: http://catalog.rpi.edu/
has course code: crs000773
has credits: 4
has department: dpt0026
has description: This course explores the principles of distributed systems, emphasizing fundamental issues underlying the design of such systems: communication, coordination, synchronization, and fault-tolerance. Key algorithms and theoretical results will be studied and students will explore how these foundations play out in modern systems and applications.
has name: Distributed Systems and Algorithms
has required prerequisite: CSCI-4210
has topic: placeholder for topic

crs000773
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type: CourseCode
has department code: dptc0026
has level: 6510
has tag: CSCI-6510

CSCI-6800
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type: Course
source: http://catalog.rpi.edu/
has course code: crs000776
has credits: 4
has department: dpt0026
has description: Gaussian elimination, special linear systems (such as positive definite, banded, or sparse), introduction to parallel computing, iterative methods for linear systems (such as conjugate gradient and preconditioning), QR factorization and least squares problems, and eigenvalue problems.
has name: Computational Linear Algebra
has required prerequisite: CSCI-4800
has topic: placeholder for topic

crs000776
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type: CourseCode
has department code: dptc0026
has level: 6800
has tag: CSCI-6800

CSCI-6860
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type: Course
source: http://catalog.rpi.edu/
has course code: crs000779
has credits: 4
has department: dpt0026
has description: Galerkin's method and extremal principles, finite element approximations (Lagrange, hierarchical and 3-D approximations, interpolation errors), mesh generation and assembly, adaptivity (h-, p-, hp-refinement). Error analysis and convergence rates. Perturbations resulting from boundary approximation, numerical integration, etc. Time dependent problems including parabolic and hyperbolic PDEs. Applications will be selected from several areas including heat conduction, wave propagation, potential theory, and solid and fluid mechanics.
has name: Finite Element Analysis
has required prerequisite: CSCI-4800
has topic: placeholder for topic

crs000779
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 6860
has tag: CSCI-6860

COGS-4600
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type: Course
source: http://catalog.rpi.edu/
has course code: crs000860
has credits: 4
has department: dpt0002
has description: Perception and thought are considered in terms of processes represented in the brain. The localization and lateralization of function are examined, drawing upon research on the behavioral effects of brain damage as well as brain-imaging studies and other approaches. Examples of topics include object recognition, memory, language, emotion, spatial ability, and motor processes.
has name: Cognition and the Brain
has topic: placeholder for topic

crs000860
type: NamedIndividual
type: CourseCode
has department code: dptc0002
has level: 4600
has tag: COGS-4600

CSCI-4230
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000883
has credits: 4
has department: dpt0026
has description: A self-contained course that includes topics from number theory, basic cryptography, and protocol security. This is a hybrid course with sufficient depth in both theory and hands-on experience with network protocols. Topics include: Classical Cryptography, Block Ciphers (DES, AES), Information Theoretical Cryptography, Randomness, RNG and Stream Ciphers, Hash and MAC Algorithms, Public-Key Cryptography, Elliptic Curve Cryptography, Digital Signatures and Identification, Internet Attacks, Web Security, SSL and PGP. This is a communication-intensive course.
has name: Cryptography and Network Security I
has required prerequisite: CSCI-2300
has required prerequisite: CSCI-4210
has required prerequisite: CSCI-4220
has topic: placeholder for topic

crs000883
type: NamedIndividual
type: CourseCode
has department code: dptc0026
has level: 4230
has tag: CSCI-4230

CSCI-4963
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000887
has credits: 4
has department: dpt0026
has topic: placeholder for topic

crs000887
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type: CourseCode
has department code: dptc0026
has level: 4963
has tag: CSCI-4963

CSCI-4965
type: NamedIndividual
type: Course
source: http://catalog.rpi.edu/
has course code: crs000891
has credits: 4
has department: dpt0026
has topic: placeholder for topic

crs000891
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type: CourseCode
has department code: dptc0026
has level: 4965
has tag: CSCI-4965

dpt0001
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type: Department
has name: Arts

dpt0002
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type: Department
has name: Cognitive Science

dpt0003
type: NamedIndividual
type: Department
has name: Science and Technology Studies - Humanities

dpt0004
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type: Department
has name: Science and Technology Studies - Social Sciences

dpt0005
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type: Department
has name: Communication

dpt0006
type: NamedIndividual
type: Department
has name: Economics

dpt0007
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type: Department
has name: Games and Simulations Arts and Sciences

dpt0008
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type: Department
has name: Interdisciplinary H&SS

dpt0009
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type: Department
has name: Languages

dpt0010
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type: Department
has name: Literature

dpt0011
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type: Department
has name: Philosophy

dpt0012
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type: Department
has name: Psychology

dpt0013
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type: Department
has name: Writing

dpt0014
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type: Department
has name: Biomedical Engineering

dpt0015
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type: Department
has name: Chemical Engineering

dpt0016
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type: Department
has name: Electrical and Computer Systems Engineering

dpt0017
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type: Department
has name: Environmental and Energy Engineering

dpt0018
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type: Department
has name: Mechanical, Aerospace, and Nuclear Engineering

dpt0019
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type: Department
has name: Materials Science and Engineering

dpt0020
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type: Department
has name: Civil Engineering

dpt0021
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dpt0022
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type: Department
has name: Engineering Science

dpt0023
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type: Department
has name: Industrial and Systems Engineering

dpt0024
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type: Department
has name: Electric Power Engineering

dpt0025
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type: Department
has name: Biochemistry and Biophysics

dpt0026
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type: Department
has name: Computer Science

dpt0027
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type: Department
has name: Earth and Environmental Science

dpt0028
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type: Department
has name: Interdisciplinary Environmental

dpt0029
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type: Department
has name: Interdisciplinary Science

dpt0030
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type: Department
has name: Math Programming, Probability, and Statistics

dpt0031
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has name: Physics

dpt0032
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type: Department
has name: Astronomy

dpt0033
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type: Department
has name: Biology

dpt0034
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has name: Chemistry

dpt0035
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type: Department
has name: Mathematics

dpt0036
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type: Department
has name: Information Technology and Web Science

dpt0037
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dpt0038
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has name: Lighting

dpt0039
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dpt0040
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has name: Administrative Courses

dpt0041
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has name: Aerospace Studies (Air Force ROTC)

dpt0042
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has name: Naval Science (Navy ROTC)

dpt0043
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has name: Military Science (Army ROTC)

dpt0044
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has name: Co-Ops

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dptc0002
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dptc0007
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dptc0012
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has tag: WRIT

dptc0014
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dptc0015
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dptc0035
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pos000919
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has planned degree: PLACEHOLDER-DEGREE-1
has planned major: PLACEHOLDER-MAJOR-1

pos000930
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pos000940
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has completed course: crsSec000193
has completed course: crsSec000194
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has completed course: crsSec000203
has completed course: crsSec000204
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