Scott Rixner

 

 


 

Scott Rixner is an Associate Professor in the Computer Science & Electrical and Computer Engineering departments at Rice University. He leads the Rice Computer Architecture Group, and his research interests include media, network, and communications processing; the interaction between operating systems and computer architectures; and memory system architecture. During his doctoral studies, Rixner was the principal architect of the Imagine Stream Processor. His current research focuses on network server architecture, network virtualization, and memory system architecture.


More info: http://www.cs.rice.edu/~rixner/




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Dec 12th 2016

This two-part course is designed to help students with very little or no computing background learn the basics of building simple interactive applications. Our language of choice, Python, is an easy-to learn, high-level computer language that is used in many of the computational courses offered on Coursera. To make learning Python easy, we have developed a new browser-based programming environment that makes developing interactive applications in Python simple. These applications will involve windows whose contents are graphical and respond to buttons, the keyboard and the mouse.

Average: 5.6 (22 votes)
Dec 12th 2016

This two-part course builds upon the programming skills that you learned in our Introduction to Interactive Programming in Python course. We will augment those skills with both important programming practices and critical mathematical problem solving skills. These skills underlie larger scale computational problem solving and programming.

Average: 6.5 (16 votes)
Dec 12th 2016

Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language. This two-part class is designed to train students in the mathematical concepts and process of "Algorithmic Thinking", allowing them to build simpler, more efficient solutions to computational problems.

Average: 6 (6 votes)
Dec 12th 2016

This two-part course introduces the basic mathematical and programming principles that underlie much of Computer Science. Understanding these principles is crucial to the process of creating efficient and well-structured solutions for computational problems. To get hands-on experience working with these concepts, we will use the Python programming language.

Average: 5.8 (11 votes)
Dec 12th 2016

This two-part course is designed to help students with very little or no computing background learn the basics of building simple interactive applications. Our language of choice, Python, is an easy-to learn, high-level computer language that is used in many of the computational courses offered on Coursera.

Average: 5.1 (16 votes)
Dec 12th 2016

Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language. This two-part class is designed to train students in the mathematical concepts and process of "Algorithmic Thinking", allowing them to build simpler, more efficient solutions to computational problems.

Average: 7.3 (8 votes)