Fundamental concepts of computing and information science and their application to everyday computer use. Topics include data representation, addressing and mapping, network protocols, standards, data exchange, encryption and security, mathematical modeling, and data modeling. Hands-on labs emphasize problem-solving using software to collect and analyze data, and evaluate and present results.

Introduction to computer models used as tools of scientific investigation, including historically important examples in the natural and social sciences. Lectures cover topics of current public interest, including economics, epidemiology, and ecological sustainability.

Introduction to algorithmic problem solving using the Python programming language. Basic techniques of program development and supportive software tools. Programming projects.

Algorithms, programs, and computing systems. Fundamental techniques of program development and supportive software tools. Programming projects and applications in a structured computer language. Hands-on experience using microcomputers.

Algorithms, programs, and computing systems. Fundamental techniques of program development and supportive software tools. Programming projects and applications in a structured computer language. Hands-on experience using microcomputers.

Software development techniques in an object-oriented computer language. An intermediate programming course emphasizing systems methods, top-down design, testing, modularity, and structured techniques. Applications from areas of numeric and non-numeric processing and data structures.

Software development techniques in an object-oriented computer language. An intermediate programming course in Java emphasizing systems methods, top-down design, testing, modularity, and structured techniques. Applications from areas of numeric and non-numeric processing and data structures. Students in this course are required to complete a final project that utilizes concepts taught throughout the semester.

An introduction to concepts in scientific programming and data science using the Python language. Students are given hands-on opportunities to learn techniques applicable to quantitative analyses across a broad range of fields. Core programming concepts are taught in tandem with real-world applications.

Provides an introduction to concepts in scientific programming and data science using the Python language. Students are given hands-on opportunities to learn techniques applicable to quantitative analysis across a broad range of fields. Core programming concepts are taught in tandem with real-world applications.

Programs and programming techniques used in systems programming in Unix environments. Focus on Unix system call interfaces and the interface between the Unix kernel and application software running in Unix environments. Students will learn the basics of Unix systems programming, including file and directory structures, basic and advanced file I/O, process creation, and inter-process communication.

Programs and programming techniques used in systems programming in Unix environments. Focus on Unix system call interfaces and the interface between the Unix kernel and application software running in Unix environments. Students will learn the basics of Unix systems programming, including file and directory structures, basic and advanced file I/O, process creation, and inter-process communication.

A topic in elementary computer science not covered by any other lower-division computer science course.