COMP 112-01 30403 |
Introduction to Data Science |
Days: T R
|
Time: 08:00 am-09:30 am
|
Room: THEATR 200
|
Instructor: Lisa Lendway
|
Avail./Max.: Closed 0 / 24
|
*First day attendance required; cross-listed with STAT 112-01*
Details
This course provides an introduction to the handling, analysis, and interpretation of the big datasets now routinely being collected in science, commerce, and government. Students achieve facility with a sophisticated, technical computing environment. The course aligns with techniques being used in several courses in the natural and social sciences, statistics, and mathematics. The course is intended to be accessible to all students, regardless of background.
General Education Requirements:
Quantitative Thinking Q2
Distribution Requirements:
Natural science and mathematics
Course Materials
|
COMP 112-02 30404 |
Introduction to Data Science |
Days: T R
|
Time: 09:40 am-11:10 am
|
Room: THEATR 200
|
Instructor: Lisa Lendway
|
Avail./Max.: Closed 1 / 24
|
*First day attendance required; cross-listed with STAT 112-02*
Details
This course provides an introduction to the handling, analysis, and interpretation of the big datasets now routinely being collected in science, commerce, and government. Students achieve facility with a sophisticated, technical computing environment. The course aligns with techniques being used in several courses in the natural and social sciences, statistics, and mathematics. The course is intended to be accessible to all students, regardless of background.
General Education Requirements:
Quantitative Thinking Q2
Distribution Requirements:
Natural science and mathematics
Course Materials
|
COMP 112-03 30405 |
Introduction to Data Science |
Days: T R
|
Time: 01:20 pm-02:50 pm
|
Room: THEATR 200
|
Instructor: Lauren Milne
|
Avail./Max.: Closed 3 / 24
|
*First day attendance required; cross-listed with STAT 112-03*
Details
This course provides an introduction to the handling, analysis, and interpretation of the big datasets now routinely being collected in science, commerce, and government. Students achieve facility with a sophisticated, technical computing environment. The course aligns with techniques being used in several courses in the natural and social sciences, statistics, and mathematics. The course is intended to be accessible to all students, regardless of background.
General Education Requirements:
Quantitative Thinking Q2
Distribution Requirements:
Natural science and mathematics
Course Materials
|
COMP 123-01 30409 |
Core Concepts in Computer Science |
Days: M W F
|
Time: 09:40 am-10:40 am
|
Room: OLRI 258
|
Instructor: Lauren Milne
|
Avail./Max.: Closed 3 / 25
|
*First day attendance required*
Details
This course introduces the field of computer science, including central concepts such as the design and implementation of algorithms and programs, testing and analyzing programs, the representation of information within the computer, and the role of abstraction and metaphor in computer science. The exploration of these central ideas will draw examples from a range of application areas including multimedia processing, turtle graphics, and text processing. Course work will use the Python programming language.
General Education Requirements:
Distribution Requirements:
Natural science and mathematics
Course Materials
|
COMP 123-02 30410 |
Core Concepts in Computer Science |
Days: M W F
|
Time: 10:50 am-11:50 am
|
Room: OLRI 258
|
Instructor: Lauren Milne
|
Avail./Max.: Closed -1 / 25
|
*First day attendance required*
Details
This course introduces the field of computer science, including central concepts such as the design and implementation of algorithms and programs, testing and analyzing programs, the representation of information within the computer, and the role of abstraction and metaphor in computer science. The exploration of these central ideas will draw examples from a range of application areas including multimedia processing, turtle graphics, and text processing. Course work will use the Python programming language.
General Education Requirements:
Distribution Requirements:
Natural science and mathematics
Course Materials
|
COMP 123-04 30412 |
Core Concepts in Computer Science |
Days: M W F
|
Time: 01:10 pm-02:10 pm
|
Room: OLRI 258
|
Instructor: Elizabeth Ernst
|
Avail./Max.: 4 / 25
|
*First day attendance required*
Details
This course introduces the field of computer science, including central concepts such as the design and implementation of algorithms and programs, testing and analyzing programs, the representation of information within the computer, and the role of abstraction and metaphor in computer science. The exploration of these central ideas will draw examples from a range of application areas including multimedia processing, turtle graphics, and text processing. Course work will use the Python programming language.
General Education Requirements:
Distribution Requirements:
Natural science and mathematics
Course Materials
|
COMP 123-05 30880 |
Core Concepts in Computer Science |
Days: M W F
|
Time: 02:20 pm-03:20 pm
|
Room: OLRI 258
|
Instructor: Elizabeth Ernst
|
Avail./Max.: 2 / 25
|
*First day attendance required*
Details
This course introduces the field of computer science, including central concepts such as the design and implementation of algorithms and programs, testing and analyzing programs, the representation of information within the computer, and the role of abstraction and metaphor in computer science. The exploration of these central ideas will draw examples from a range of application areas including multimedia processing, turtle graphics, and text processing. Course work will use the Python programming language.
General Education Requirements:
Distribution Requirements:
Natural science and mathematics
Course Materials
|
COMP 127-01 30413 |
Object-Oriented Programming and Abstraction |
Days: M W F
|
Time: 09:40 am-10:40 am
|
Room: OLRI 256
|
Instructor: Benjamin Hillmann
|
Avail./Max.: Closed -2 / 16
|
*First day attendance required*
Details
What happens as software grows in complexity? How do we break a program into manageable pieces? How do we write readable, maintainable code? This course is an introduction to the building blocks of software design: abstraction, decomposition, and encapsulation. Using object-oriented programming in Java, we will create graphics, games, and simulations, and explore natural language processing. Topics may include: classes, objects, polymorphism, inheritance, testing, refactoring, events, closures, streams, immutability, parallel programming, and version control. The course culminates in a student-designed project. There is a required 1.5 hour laboratory section associated with this course. Prerequisite(s): COMP 123 or permission of instructor.
General Education Requirements:
Distribution Requirements:
Natural science and mathematics
Course Materials
|
COMP 127-02 30414 |
Object-Oriented Programming and Abstraction |
Days: M W F
|
Time: 10:50 am-11:50 am
|
Room: OLRI 256
|
Instructor: Benjamin Hillmann
|
Avail./Max.: Closed 1 / 16
|
*First day attendance required*
Details
What happens as software grows in complexity? How do we break a program into manageable pieces? How do we write readable, maintainable code? This course is an introduction to the building blocks of software design: abstraction, decomposition, and encapsulation. Using object-oriented programming in Java, we will create graphics, games, and simulations, and explore natural language processing. Topics may include: classes, objects, polymorphism, inheritance, testing, refactoring, events, closures, streams, immutability, parallel programming, and version control. The course culminates in a student-designed project. There is a required 1.5 hour laboratory section associated with this course. Prerequisite(s): COMP 123 or permission of instructor.
General Education Requirements:
Distribution Requirements:
Natural science and mathematics
Course Materials
|
COMP 127-03 30415 |
Object-Oriented Programming and Abstraction |
Days: M W F
|
Time: 01:10 pm-02:10 pm
|
Room: OLRI 256
|
Instructor: Joslenne Pena
|
Avail./Max.: Closed 2 / 16
|
*First day attendance required*
Details
What happens as software grows in complexity? How do we break a program into manageable pieces? How do we write readable, maintainable code? This course is an introduction to the building blocks of software design: abstraction, decomposition, and encapsulation. Using object-oriented programming in Java, we will create graphics, games, and simulations, and explore natural language processing. Topics may include: classes, objects, polymorphism, inheritance, testing, refactoring, events, closures, streams, immutability, parallel programming, and version control. The course culminates in a student-designed project. There is a required 1.5 hour laboratory section associated with this course. Prerequisite(s): COMP 123 or permission of instructor.
General Education Requirements:
Distribution Requirements:
Natural science and mathematics
Course Materials
|
COMP 127-04 30881 |
Object-Oriented Programming and Abstraction |
Days: M W F
|
Time: 02:20 pm-03:20 pm
|
Room: OLRI 256
|
Instructor: Benjamin Hillmann
|
Avail./Max.: Closed 5 / 16
|
*First day attendance required; registration limits will be adjusted to save 4 seats for First-Years*
Details
What happens as software grows in complexity? How do we break a program into manageable pieces? How do we write readable, maintainable code? This course is an introduction to the building blocks of software design: abstraction, decomposition, and encapsulation. Using object-oriented programming in Java, we will create graphics, games, and simulations, and explore natural language processing. Topics may include: classes, objects, polymorphism, inheritance, testing, refactoring, events, closures, streams, immutability, parallel programming, and version control. The course culminates in a student-designed project. There is a required 1.5 hour laboratory section associated with this course. Prerequisite(s): COMP 123 or permission of instructor.
General Education Requirements:
Distribution Requirements:
Natural science and mathematics
Course Materials
|
COMP 127-L1 30416 |
Object-Oriented Programming and Abstraction Lab |
Days: R
|
Time: 08:00 am-09:30 am
|
Room: OLRI 256
|
Instructor: Benjamin Hillmann
|
Avail./Max.: 5 / 16
|
*First day attendance required*
Details
What happens as software grows in complexity? How do we break a program into manageable pieces? How do we write readable, maintainable code? This course is an introduction to the building blocks of software design: abstraction, decomposition, and encapsulation. Using object-oriented programming in Java, we will create graphics, games, and simulations, and explore natural language processing. Topics may include: classes, objects, polymorphism, inheritance, testing, refactoring, events, closures, streams, immutability, parallel programming, and version control. The course culminates in a student-designed project. There is a required 1.5 hour laboratory section associated with this course. Prerequisite(s): COMP 123 or permission of instructor.
General Education Requirements:
Distribution Requirements:
Natural science and mathematics
Course Materials
|
COMP 127-L2 30417 |
Object-Oriented Programming and Abstraction Lab |
Days: R
|
Time: 09:40 am-11:10 am
|
Room: OLRI 256
|
Instructor: Benjamin Hillmann
|
Avail./Max.: Closed -1 / 16
|
*First day attendance required*
Details
What happens as software grows in complexity? How do we break a program into manageable pieces? How do we write readable, maintainable code? This course is an introduction to the building blocks of software design: abstraction, decomposition, and encapsulation. Using object-oriented programming in Java, we will create graphics, games, and simulations, and explore natural language processing. Topics may include: classes, objects, polymorphism, inheritance, testing, refactoring, events, closures, streams, immutability, parallel programming, and version control. The course culminates in a student-designed project. There is a required 1.5 hour laboratory section associated with this course. Prerequisite(s): COMP 123 or permission of instructor.
General Education Requirements:
Distribution Requirements:
Natural science and mathematics
Course Materials
|
COMP 127-L3 30418 |
Object-Oriented Programming and Abstraction Lab |
Days: R
|
Time: 01:20 pm-02:50 pm
|
Room: OLRI 256
|
Instructor: Joslenne Pena
|
Avail./Max.: Closed 1 / 16
|
*First day attendance required; registration limit will be adjusted to save 4 seats for First-Years*
Details
What happens as software grows in complexity? How do we break a program into manageable pieces? How do we write readable, maintainable code? This course is an introduction to the building blocks of software design: abstraction, decomposition, and encapsulation. Using object-oriented programming in Java, we will create graphics, games, and simulations, and explore natural language processing. Topics may include: classes, objects, polymorphism, inheritance, testing, refactoring, events, closures, streams, immutability, parallel programming, and version control. The course culminates in a student-designed project. There is a required 1.5 hour laboratory section associated with this course. Prerequisite(s): COMP 123 or permission of instructor.
General Education Requirements:
Distribution Requirements:
Natural science and mathematics
Course Materials
|
COMP 127-L4 30882 |
Object-Oriented Programming and Abstraction |
Days: R
|
Time: 03:00 pm-04:30 pm
|
Room: OLRI 256
|
Instructor: Benjamin Hillmann
|
Avail./Max.: Closed 1 / 16
|
*First day attendance required*
Details
What happens as software grows in complexity? How do we break a program into manageable pieces? How do we write readable, maintainable code? This course is an introduction to the building blocks of software design: abstraction, decomposition, and encapsulation. Using object-oriented programming in Java, we will create graphics, games, and simulations, and explore natural language processing. Topics may include: classes, objects, polymorphism, inheritance, testing, refactoring, events, closures, streams, immutability, parallel programming, and version control. The course culminates in a student-designed project. There is a required 1.5 hour laboratory section associated with this course. Prerequisite(s): COMP 123 or permission of instructor.
General Education Requirements:
Distribution Requirements:
Natural science and mathematics
Course Materials
|
COMP 128-01 30419 |
Data Structures |
Days: M W F
|
Time: 09:40 am-10:40 am
|
Room: OLRI 245
|
Instructor: Irene Yuan
|
Avail./Max.: Closed -2 / 20
|
*First day attendance required*
Details
This course familiarizes students with the fundamental data structures in computer science. Using the Java programming language, students will study existing data structure implementations, implement their own data structures, and develop data-intensive applications. The course covers stacks, queues, lists, trees, heaps, hash tables, graphs, and the common algorithms that use these data structures. Students will also receive an introduction to basic complexity analysis (Big-O), learn the time complexity of different data structure operations, and gain experience in calculating the time complexity of programs that use data structures. Prerequisite(s): COMP 127 or permission of instructor.
General Education Requirements:
Distribution Requirements:
Natural science and mathematics
Course Materials
|
COMP 128-02 30420 |
Data Structures |
Days: M W F
|
Time: 10:50 am-11:50 am
|
Room: OLRI 245
|
Instructor: Irene Yuan
|
Avail./Max.: Closed -1 / 20
|
*First day attendance required*
Details
This course familiarizes students with the fundamental data structures in computer science. Using the Java programming language, students will study existing data structure implementations, implement their own data structures, and develop data-intensive applications. The course covers stacks, queues, lists, trees, heaps, hash tables, graphs, and the common algorithms that use these data structures. Students will also receive an introduction to basic complexity analysis (Big-O), learn the time complexity of different data structure operations, and gain experience in calculating the time complexity of programs that use data structures. Prerequisite(s): COMP 127 or permission of instructor.
General Education Requirements:
Distribution Requirements:
Natural science and mathematics
Course Materials
|
COMP 221-01 30421 |
Algorithm Design and Analysis |
Days: M W F
|
Time: 09:40 am-10:40 am
|
Room: THEATR 202
|
Instructor: Lian Duan
|
Avail./Max.: 15 / 25
|
*Permission of instructor required; first day attendance required*
Details
This course offers an in-depth introduction to the design and analysis of algorithms. Students will work with algorithms in pseudocode, and will learn formal and informal methods for analyzing algorithm efficiency and correctness. Topics may include recursion, divide and conquer, dynamic programming, greedy methods, branch and bound, randomized, probabilistic, and parallel algorithms. Application areas include string processing, graphs, geometric problems, and optimization. This course will introduce computability topics including regular expressions, grammars and parsing, automata, nondeterminism, and NP completeness. Prerequisite(s): COMP 128 (or COMP 124, if previously taken) and MATH 279, or permission of instructor.
General Education Requirements:
Distribution Requirements:
Natural science and mathematics
Course Materials
|
COMP 221-02 30422 |
Algorithm Design and Analysis |
Days: M W F
|
Time: 10:50 am-11:50 am
|
Room: THEATR 202
|
Instructor: Lian Duan
|
Avail./Max.: 1 / 25
|
*Permission of instructor required; first day attendance required*
Details
This course offers an in-depth introduction to the design and analysis of algorithms. Students will work with algorithms in pseudocode, and will learn formal and informal methods for analyzing algorithm efficiency and correctness. Topics may include recursion, divide and conquer, dynamic programming, greedy methods, branch and bound, randomized, probabilistic, and parallel algorithms. Application areas include string processing, graphs, geometric problems, and optimization. This course will introduce computability topics including regular expressions, grammars and parsing, automata, nondeterminism, and NP completeness. Prerequisite(s): COMP 128 (or COMP 124, if previously taken) and MATH 279, or permission of instructor.
General Education Requirements:
Distribution Requirements:
Natural science and mathematics
Course Materials
|
COMP 225-01 30423 |
Software Design and Development |
Days: M W F
|
Time: 01:10 pm-02:10 pm
|
Room: OLRI 245
|
Instructor: Paul Cantrell
|
Avail./Max.: 0 / 16
|
*Permission of instructor required; first day attendance required*
Details
This course is an introduction to the problem of building software with humans and for humans. Students work in teams to design and implement a semester-long user-facing software project of their own invention. There are no limitations on topic or technology; on the contrary, students are responsible for imagining possibilities, articulating goals, and researching and selecting suitable technologies. The format resembles a studio art class, with in-class discussion guided by sharing and critiquing classmates' ongoing work. Topics include communication, division of labor, user-centered design, human-computer interaction, product management, project management, iterative development, engineering tradeoffs, separation of concerns, code readability and maintainability, refactoring, testing, and version control. Teams give a public demonstration of their working projects at the end of the semester. Prerequisite(s): COMP 127 (COMP 128 recommended), or COMP 124 if previously taken, or permission of instructor.
General Education Requirements:
Distribution Requirements:
Natural science and mathematics
Course Materials
|
COMP 225-02 30424 |
Software Design and Development |
Days: M W F
|
Time: 02:20 pm-03:20 pm
|
Room: OLRI 245
|
Instructor: Paul Cantrell
|
Avail./Max.: 3 / 16
|
*Permission of instructor required; first day attendance required*
Details
This course is an introduction to the problem of building software with humans and for humans. Students work in teams to design and implement a semester-long user-facing software project of their own invention. There are no limitations on topic or technology; on the contrary, students are responsible for imagining possibilities, articulating goals, and researching and selecting suitable technologies. The format resembles a studio art class, with in-class discussion guided by sharing and critiquing classmates' ongoing work. Topics include communication, division of labor, user-centered design, human-computer interaction, product management, project management, iterative development, engineering tradeoffs, separation of concerns, code readability and maintainability, refactoring, testing, and version control. Teams give a public demonstration of their working projects at the end of the semester. Prerequisite(s): COMP 127 (COMP 128 recommended), or COMP 124 if previously taken, or permission of instructor.
General Education Requirements:
Distribution Requirements:
Natural science and mathematics
Course Materials
|
COMP 240-01 30425 |
Computer Systems Organization |
Days: M W F
|
Time: 01:10 pm-02:10 pm
|
Room: THEATR 001
|
Instructor: Getiria Onsongo
|
Avail./Max.: 0 / 20
|
*Permission of instructor required; first day attendance required*
Details
This course familiarizes the student with the internal design and organization of computers. Topics include number systems, internal data representations, microarchitectures, the functional units of a computer system, memory, processor, and input/output structures, instruction sets and assembly language, addressing techniques, system software, and concurrency and parallelism. Prerequisite(s): COMP 127 (or COMP 124 if previously taken) or permission of instructor.
General Education Requirements:
Distribution Requirements:
Natural science and mathematics
Course Materials
|
COMP 240-02 30426 |
Computer Systems Organization |
Days: M W F
|
Time: 02:20 pm-03:20 pm
|
Room: THEATR 001
|
Instructor: Getiria Onsongo
|
Avail./Max.: 0 / 20
|
*Permission of instructor required; first day attendance required*
Details
This course familiarizes the student with the internal design and organization of computers. Topics include number systems, internal data representations, microarchitectures, the functional units of a computer system, memory, processor, and input/output structures, instruction sets and assembly language, addressing techniques, system software, and concurrency and parallelism. Prerequisite(s): COMP 127 (or COMP 124 if previously taken) or permission of instructor.
General Education Requirements:
Distribution Requirements:
Natural science and mathematics
Course Materials
|
COMP 302-01 30427 |
Introduction to Database Management Systems |
Days: M W F
|
Time: 02:20 pm-03:20 pm
|
Room: OLRI 254
|
Instructor: Libby Shoop
|
Avail./Max.: -1 / 15
|
*Permission of instructor required; first day attendance required*
Details
This course will introduce students to the design, implementation, and analysis of databases stored in database management systems (DBMS). Topics include implementation-neutral data modeling, database design, database implementation, and data analysis using relational algebra and SQL. Students will generate data models based on real-world problems, and implement a database in a state-of-the-art DBMS. Students will master complex data analysis by learning to first design database queries and then implement them in a database query language such as SQL. Advanced topics include objects in databases, indexing for improved performance, distributed databases, and data warehouses.
General Education Requirements:
Distribution Requirements:
Natural science and mathematics
Course Materials
|
COMP 302-02 30428 |
Introduction to Database Management Systems |
Days: M W F
|
Time: 03:30 pm-04:30 pm
|
Room: OLRI 254
|
Instructor: Libby Shoop
|
Avail./Max.: -2 / 15
|
*Permission of instructor required; first day attendance required*
Details
This course will introduce students to the design, implementation, and analysis of databases stored in database management systems (DBMS). Topics include implementation-neutral data modeling, database design, database implementation, and data analysis using relational algebra and SQL. Students will generate data models based on real-world problems, and implement a database in a state-of-the-art DBMS. Students will master complex data analysis by learning to first design database queries and then implement them in a database query language such as SQL. Advanced topics include objects in databases, indexing for improved performance, distributed databases, and data warehouses.
General Education Requirements:
Distribution Requirements:
Natural science and mathematics
Course Materials
|
COMP 361-01 30429 |
Theory of Computation |
Days: M W F
|
Time: 03:30 pm-04:30 pm
|
Room: OLRI 241
|
Instructor: Susan Fox
|
Avail./Max.: 4 / 30
|
*Permission of instructor required; first day attendance required; cross-listed with MATH 361-01*
Details
This course examines the theoretical foundations of computation. It explores different mathematical models that try to formalize our informal notion of an algorithm. Models include finite automata, regular expressions, grammars, and Turing machines. The course also discusses ideas about what can and cannot be computed. In addition, the course explores the basics of complexity theory, examining broad categories of problems and their algorithms, and their efficiency. The focus is on the question of P versus NP, and the NP-complete set. Prerequisite(s): (COMP 128 or COMP 221 or COMP 124 if previously taken) and MATH 279, or permission of instructor.
General Education Requirements:
Distribution Requirements:
Natural science and mathematics
Course Materials
|
COMP 365-01 30431 |
Computational Linear Algebra |
Days: T R
|
Time: 09:40 am-11:10 am
|
Room: THEATR 206
|
Instructor: David Shuman
|
Avail./Max.: 7 / 24
|
*First day attendance required; cross-listed with MATH 365-01*
Details
A mix of applied linear algebra and numerical analysis, this course covers a central point of contact between mathematics and computer science. Many of the computational techniques important in science, commerce, and statistics are based on concepts from linear algebra, such as subspaces, projections, and matrix decompositions. The course reviews these concepts, adopts them to large scales, and applies them in the core techniques of scientific computing. These include solving systems of linear and nonlinear equations, approximation and statistical function estimation, optimization, interpolation, eigenvalue and singular value decompositions, and compression. Applications throughout the natural sciences, social sciences, statistics, and computer science. Prerequisite(s): COMP 120 or COMP 123, and MATH 236
General Education Requirements:
Writing WP
Distribution Requirements:
Natural science and mathematics
Course Materials
|
COMP 365-02 30432 |
Computational Linear Algebra |
Days: T R
|
Time: 01:20 pm-02:50 pm
|
Room: THEATR 206
|
Instructor: David Shuman
|
Avail./Max.: 7 / 24
|
*First day attendance required; cross-listed with MATH 365-02*
Details
A mix of applied linear algebra and numerical analysis, this course covers a central point of contact between mathematics and computer science. Many of the computational techniques important in science, commerce, and statistics are based on concepts from linear algebra, such as subspaces, projections, and matrix decompositions. The course reviews these concepts, adopts them to large scales, and applies them in the core techniques of scientific computing. These include solving systems of linear and nonlinear equations, approximation and statistical function estimation, optimization, interpolation, eigenvalue and singular value decompositions, and compression. Applications throughout the natural sciences, social sciences, statistics, and computer science. Prerequisite(s): COMP 120 or COMP 123, and MATH 236
General Education Requirements:
Writing WP
Distribution Requirements:
Natural science and mathematics
Course Materials
|
COMP 394-01 30435 |
Computer Science and Social Justice |
Days: M W F
|
Time: 10:50 am-11:50 am
|
Room: OLRI 241
|
Instructor: Joslenne Pena
|
Avail./Max.: 7 / 20
|
*Permission of instructor required; first day attendance required*
Details
This course explores the diversity, equity, and inclusion (DEI) obstacles in computing through an introduction to and analysis of social justice as a construct, its impact on computing entities, and the resulting effect of technology on various identities. The course will examine how technologies continue to reinforce and heighten injustices through critical analysis of several concepts. Should these technologies be redesigned? Or tossed out altogether? Students will engage in class discussions through scenarios and/or case studies. Students will engage in design thinking and programming activities. Semester culminates with a group-based project. Familiarity with a programming language is recommended. Background in social science courses recommended.
General Education Requirements:
Distribution Requirements:
Course Materials
|
COMP 445-01 30861 |
Parallel and Distributed Processing |
Days: T R
|
Time: 03:00 pm-04:30 pm
|
Room: OLRI 245
|
Instructor: Libby Shoop
|
Avail./Max.: 1 / 15
|
*Permission of instructor required; first day attendance required*
Details
Many current computational challenges, such as Internet search, protein folding, and data mining require the use of multiple processes running in parallel, whether on a single multiprocessor machine (parallel processing) or on multiple machines connected together on a network (distributed processing). The type of processing required to solve such problems in adequate amounts of time involves dividing the program and/or problem space into parts that can run simultaneously on many processors. In this course we will explore the various computer architectures used for this purpose and the issues involved with programming parallel solutions in such environments. Students will examine several types of problems that can benefit from parallel or distributed solutions and develop their own solutions for them. This course counts as the capstone. Prerequisite(s): COMP 240 and COMP 221, or permission of instructor.
General Education Requirements:
Distribution Requirements:
Natural science and mathematics
Course Materials
|
COMP 480-01 30436 |
Bodies and Minds: AI Robotics |
Days: T R
|
Time: 01:20 pm-02:50 pm
|
Room: OLRI 258
|
Instructor: Susan Fox
|
Avail./Max.: 0 / 30
|
*Permission of instructor required; first day attendance required*
Details
This course examines two distinct aspects of work in robotics: the physical construction of the robot's "body" and the creation of robot control programs that form the robot's "mind." It will study the strengths and weaknesses of a variety of robot sensors, including sonar, infrared, touch, GPS, and computer vision. It will also examine both reactive and deliberative approaches to robot control programs. The course will include hands-on work with multiple robots, and a semester-long course project in robotics. This course involves programming in Python; students should have a basic familiarity with Python or be prepared to learn Python during the course. This course counts as the capstone. Prerequisite(s): COMP 221 or permission of instructor.
General Education Requirements:
Distribution Requirements:
Natural science and mathematics
Course Materials
|