Applets variables and computation events and flow of control classes and objects inheritance GUI elements applications arrays, strings, files, and linked structures exceptions threads.Ĭatalog Description: Introduction to the constructs provided in the Python programming language, aimed at students who already know how to program. Productive Use of the UNIX EnvironmentĬatalog Description: Use of UNIX utilities and scripting facilities for customizing the programming environment, organizing files (possibly in more than one computer account), implementing a personal database, reformatting text, and searching for online resources.Ĭatalog Description: Self-paced introduction to the constructs provided in the C++ programming language for procedural and object-oriented programming, aimed at students who already know how to program.Ĭatalog Description: Self-paced course in Java for students who already know how to program. Recursion higher-order functions list processing implementation of rule-based querying. Scheme and Functional Programming for ProgrammersĬatalog Description: Self-paced course in functional programming, using the Scheme programming language, for students who already know how to program. Computation, input and output, flow of control, functions, arrays, and pointers, linked structures, use of dynamic storage, and implementation of abstract data types. Array and matrix operations, functions and function handles, control flow, plotting and image manipulation, cell arrays and structures, and the Symbolic Mathematics toolbox.Ĭatalog Description: Self-paced course in the C programming language for students who already know how to program. It delves into social and legal issues surrounding data analysis, including issues of privacy and data ownership.Ĭatalog Description: Introduction to the constructs in the Matlab programming language, aimed at students who already know how to program. Given data arising from some real-world phenomenon, how does one analyze that data so as to understand that phenomenon? The course teaches critical concepts and skills in computer programming and statistical inference, in conjunction with hands-on analysis of real-world datasets, including economic data, document collections, geographical data, and social networks. The first two units must be taken together.Ĭatalog Description: Foundations of data science from three perspectives: inferential thinking, computational thinking, and real-world relevance. Units assigned depend on amount of work completed. Introduction to Symbolic Programming (Self-Paced)Ĭatalog Description: The same material as 3 but in a self-paced format introduction to computer programming, emphasizing symbolic computation and functional programming style, using the Scheme programming language. Students will write a project of at least 200 lines of code in Scheme (a dialect of the LISP programming language). Introduction to Symbolic ProgrammingĬatalog Description: Introduction to computer programming, emphasizing symbolic computation and functional programming style. Students will write a project of at least 200 lines of code, using the Scheme programming language. Students will be required to give presentations on papers they read and projects they complete. The aim is to give entering undergraduate students a comprehensive view of the field. Catalog Description: This is a seminar course in which computer scientists describe their professional activities and interests.
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